python /home/admin/mtr/script_for_cron.py -j coverage -m 9 -a '' -s coverage -M 0 -S 0 -U 100,100,120 import MySQLdb succeeded root_folder /data_2/data_log/job/2025/February/15022025/coverage/ git_velours : /home/admin/workarea/git/Velours/ out_folder_name htmlcov output_folder /data_2/data_log/job/2025/February/15022025/coverage/htmlcov new path : /data_2/data_log/job/2025/February/15022025/coverage/ command : coverage3 run /home/admin/workarea/git/Velours/python/tests/python_tests.py --short_python3 `cat ~/.fotonower_pass/bdd.py.pass` cat: /home/admin/.fotonower_pass/bdd.py.pass: Aucun fichier ou dossier de ce type import MySQLdb succeeded Import error (python version) python version = 3 warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data python version used : 3 #&_# BEGIN OF TEST : tests/mask_test #&_# /home/admin/workarea/git/Velours/python/tests/mask_test.py Test mask-detection python version used : 3 ############################### TEST memory used ################################ free memory at begining : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10774 run mask_detect Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : mask_detect list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.9181075096130371 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:mask_detect Sat Feb 15 05:20:29 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10774 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 /home/admin/workarea/git/Velours/python/tests/python_tests.py:11: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses import imp 2025-02-15 05:20:33.172751: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-15 05:20:33.199246: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-02-15 05:20:33.201279: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f3a88000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-15 05:20:33.201311: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-15 05:20:33.205410: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-15 05:20:33.345600: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x25d4ddb0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-15 05:20:33.345653: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-15 05:20:33.346543: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-15 05:20:33.346916: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:20:33.348995: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:20:33.351149: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-15 05:20:33.351487: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-15 05:20:33.353607: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-15 05:20:33.354838: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-15 05:20:33.359174: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-15 05:20:33.360787: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-15 05:20:33.360872: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:20:33.361625: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-15 05:20:33.361640: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-15 05:20:33.361649: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-15 05:20:33.362930: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9736 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl454 thcls : [{'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 3473 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3473, 'mask_coco_origin', 16384, 25088, 'mask_coco_origin', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 3, 19, 10, 42, 21), datetime.datetime(2018, 3, 19, 10, 42, 21)) {'thcl': {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'], 'list_hashtags_csv': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'svm_hashtag_type_desc': 3473, 'photo_desc_type': 3473, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME mask_coco_origin NUM_CLASSES 81 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 2025-02-15 05:20:45.392848: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-15 05:20:45.392961: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:20:45.392981: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:20:45.392998: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-15 05:20:45.393014: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-15 05:20:45.393029: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-15 05:20:45.393044: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-15 05:20:45.393060: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-15 05:20:45.394039: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-15 05:20:45.395081: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-15 05:20:45.395119: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:20:45.395135: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:20:45.395149: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-15 05:20:45.395163: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-15 05:20:45.395177: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-15 05:20:45.395191: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-15 05:20:45.395205: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-15 05:20:45.396126: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-15 05:20:45.396156: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-15 05:20:45.396165: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-15 05:20:45.396173: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-15 05:20:45.397153: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9736 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : mask_coco_origin model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-02-15 05:20:55.321363: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:20:55.569737: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/mask_coco_origin /data/models_weight/mask_coco_origin/mask_model.h5 size_local : 257557808 size in s3 : 257557808 create time local : 2021-08-09 05:27:17 create time in s3 : 2021-08-06 19:45:17 mask_model.h5 already exist and didn't need to update list_images length : 1 NEW PHOTO Processing 1 images image shape: (480, 640, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 89) min: 0.00000 max: 640.00000 nb d'objets trouves : 5 Detection mask done ! Trying to reset tf kernel 3820747 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 196 tf kernel not reseted sub process len(results) : 1 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 1 len(list_Values) 0 process is alive finish correctly or not : True after detect begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5485 list_Values should be empty [] To do loadFromThcl(), then load ParamDescType : thcl454 Catched exception ! Connect or reconnect ! thcls : [{'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 3473 ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] time for calcul the mask position with numpy : 0.0005564689636230469 nb_pixel_total : 15552 time to create 1 rle with old method : 0.03566288948059082 length of segment : 256 time for calcul the mask position with numpy : 0.003082752227783203 nb_pixel_total : 145328 time to create 1 rle with old method : 0.31200242042541504 length of segment : 371 time for calcul the mask position with numpy : 0.0002791881561279297 nb_pixel_total : 14254 time to create 1 rle with old method : 0.032250404357910156 length of segment : 151 time for calcul the mask position with numpy : 0.000125885009765625 nb_pixel_total : 5613 time to create 1 rle with old method : 0.013035774230957031 length of segment : 48 time for calcul the mask position with numpy : 7.724761962890625e-05 nb_pixel_total : 1824 time to create 1 rle with old method : 0.00460505485534668 length of segment : 39 time spent for convertir_results : 1.3225841522216797 time spend for datou_step_exec : 33.1874315738678 time spend to save output : 4.267692565917969e-05 total time spend for step 1 : 33.18747425079346 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False eke 12-6-18 : saveMask need to be cleaned for new output ! Number saved : None batch 1 Loaded 3268 chid ids of type : 445 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.0190582275390625 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'957285035': [[(957285035, 492601069, 445, 0, 186, 22, 282, 0.9954971, [(140, 26, 6), (135, 27, 15), (133, 28, 18), (131, 29, 22), (127, 30, 27), (10, 31, 1), (120, 31, 35), (8, 32, 13), (27, 32, 3), (115, 32, 41), (7, 33, 52), (109, 33, 48), (6, 34, 70), (103, 34, 55), (5, 35, 154), (4, 36, 155), (3, 37, 156), (3, 38, 156), (3, 39, 156), (2, 40, 157), (2, 41, 157), (2, 42, 157), (2, 43, 157), (2, 44, 157), (2, 45, 157), (1, 46, 158), (1, 47, 158), (1, 48, 158), (1, 49, 157), (1, 50, 157), (1, 51, 156), (1, 52, 156), (1, 53, 155), (1, 54, 154), (1, 55, 152), (1, 56, 149), (1, 57, 145), (1, 58, 141), (1, 59, 136), (1, 60, 133), (1, 61, 130), (1, 62, 127), (1, 63, 126), (1, 64, 124), (1, 65, 123), (1, 66, 121), (1, 67, 120), (1, 68, 118), (1, 69, 117), (1, 70, 116), (1, 71, 115), (1, 72, 114), (1, 73, 113), (1, 74, 112), (1, 75, 111), (1, 76, 110), (1, 77, 108), (1, 78, 108), (1, 79, 107), (1, 80, 106), (1, 81, 106), (2, 82, 104), (2, 83, 103), (2, 84, 103), (2, 85, 102), (2, 86, 102), (2, 87, 101), (2, 88, 100), (2, 89, 99), (2, 90, 99), (2, 91, 98), (2, 92, 97), (2, 93, 96), (2, 94, 95), (2, 95, 93), (2, 96, 91), (2, 97, 90), (2, 98, 89), (2, 99, 87), (2, 100, 86), (2, 101, 86), (2, 102, 85), (2, 103, 84), (2, 104, 83), (2, 105, 83), (2, 106, 82), (2, 107, 81), (2, 108, 80), (2, 109, 80), (2, 110, 79), (2, 111, 78), (2, 112, 77), (2, 113, 76), (1, 114, 76), (1, 115, 75), (1, 116, 74), (1, 117, 73), (1, 118, 72), (1, 119, 71), (1, 120, 71), (1, 121, 70), (1, 122, 69), (1, 123, 69), (1, 124, 68), (1, 125, 68), (1, 126, 67), (1, 127, 67), (1, 128, 66), (1, 129, 66), (1, 130, 66), (1, 131, 65), (1, 132, 65), (1, 133, 64), (1, 134, 63), (1, 135, 63), (1, 136, 62), (1, 137, 61), (1, 138, 60), (1, 139, 60), (1, 140, 59), (1, 141, 58), (1, 142, 58), (1, 143, 57), (1, 144, 56), (1, 145, 56), (1, 146, 55), (1, 147, 54), (1, 148, 54), (1, 149, 53), (1, 150, 52), (1, 151, 52), (1, 152, 51), (1, 153, 50), (1, 154, 49), (1, 155, 48), (1, 156, 47), (1, 157, 46), (1, 158, 45), (1, 159, 45), (1, 160, 44), (1, 161, 43), (1, 162, 42), (1, 163, 41), (1, 164, 41), (1, 165, 40), (1, 166, 40), (1, 167, 39), (1, 168, 38), (1, 169, 37), (1, 170, 36), (1, 171, 35), (1, 172, 34), (1, 173, 34), (1, 174, 33), (1, 175, 33), (1, 176, 32), (1, 177, 32), (1, 178, 32), (1, 179, 32), (1, 180, 31), (1, 181, 31), (1, 182, 31), (1, 183, 30), (1, 184, 30), (1, 185, 30), (1, 186, 29), (1, 187, 29), (1, 188, 29), (1, 189, 28), (1, 190, 28), (1, 191, 27), (1, 192, 27), (1, 193, 26), (1, 194, 26), (1, 195, 26), (1, 196, 26), (1, 197, 26), (1, 198, 26), (1, 199, 26), (1, 200, 25), (1, 201, 25), (1, 202, 25), (1, 203, 25), (1, 204, 25), (1, 205, 25), (1, 206, 25), (1, 207, 25), (1, 208, 25), (1, 209, 25), (1, 210, 25), (1, 211, 25), (1, 212, 25), (1, 213, 25), (1, 214, 25), (1, 215, 25), (1, 216, 25), (1, 217, 25), (1, 218, 25), (1, 219, 25), (1, 220, 24), (1, 221, 24), (1, 222, 24), (1, 223, 24), (1, 224, 24), (1, 225, 24), (1, 226, 25), (1, 227, 25), (1, 228, 25), (2, 229, 24), (2, 230, 24), (2, 231, 24), (2, 232, 23), (2, 233, 23), (2, 234, 23), (2, 235, 23), (2, 236, 23), (2, 237, 23), (2, 238, 23), (2, 239, 23), (2, 240, 23), (2, 241, 23), (2, 242, 23), (2, 243, 23), (2, 244, 23), (2, 245, 23), (2, 246, 23), (2, 247, 23), (2, 248, 23), (2, 249, 24), (2, 250, 24), (2, 251, 23), (2, 252, 23), (2, 253, 23), (2, 254, 23), (2, 255, 23), (2, 256, 23), (2, 257, 23), (2, 258, 23), (2, 259, 23), (2, 260, 23), (2, 261, 23), (3, 262, 22), (3, 263, 22), (3, 264, 22), (3, 265, 22), (4, 266, 21), (4, 267, 21), (5, 268, 20), (5, 269, 20), (6, 270, 19), (7, 271, 17), (8, 272, 16), (8, 273, 16), (9, 274, 13), (11, 275, 9), (15, 276, 2)], ['16,276,8,273,2,261,2,229,1,228,1,114,2,113,2,82,1,81,1,46,3,37,8,32,20,32,21,33,58,33,59,34,75,34,76,35,102,35,114,33,120,31,130,30,135,27,145,26,152,29,158,35,158,48,154,54,141,58,128,61,119,67,109,76,103,86,96,94,89,98,81,109,71,119,65,132,60,138,52,151,45,158,40,166,34,172,29,188,26,193,25,200,25,226,24,232,24,270,23,273']), (957285035, 492601069, 445, 29, 591, 24, 419, 0.9923717, [(315, 37, 25), (272, 38, 86), (253, 39, 130), (238, 40, 151), (199, 41, 196), (189, 42, 213), (180, 43, 238), (175, 44, 250), (172, 45, 257), (169, 46, 265), (166, 47, 274), (162, 48, 284), (159, 49, 294), (157, 50, 304), (155, 51, 310), (153, 52, 317), (151, 53, 323), (149, 54, 330), (148, 55, 334), (146, 56, 337), (144, 57, 341), (142, 58, 344), (140, 59, 347), (138, 60, 350), (136, 61, 353), (134, 62, 356), (132, 63, 358), (130, 64, 361), (128, 65, 364), (126, 66, 367), (124, 67, 370), (122, 68, 373), (120, 69, 376), (118, 70, 379), (117, 71, 381), (115, 72, 385), (114, 73, 387), (113, 74, 389), (112, 75, 391), (112, 76, 393), (111, 77, 395), (110, 78, 397), (109, 79, 399), (109, 80, 400), (108, 81, 402), (107, 82, 404), (107, 83, 404), (106, 84, 406), (105, 85, 408), (105, 86, 409), (104, 87, 410), (104, 88, 411), (103, 89, 413), (102, 90, 415), (101, 91, 417), (100, 92, 420), (98, 93, 423), (97, 94, 426), (96, 95, 428), (94, 96, 431), (93, 97, 433), (92, 98, 435), (91, 99, 437), (90, 100, 439), (89, 101, 441), (89, 102, 441), (89, 103, 442), (89, 104, 443), (89, 105, 444), (89, 106, 444), (89, 107, 445), (89, 108, 446), (89, 109, 447), (89, 110, 448), (89, 111, 449), (89, 112, 450), (89, 113, 451), (89, 114, 453), (89, 115, 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['598,172,591,172,586,170,578,168,573,164,573,162,568,152,568,149,566,145,566,136,565,132,561,125,560,121,556,116,547,109,543,108,536,104,531,99,527,97,491,62,490,54,495,48,496,45,501,40,514,32,517,29,531,25,539,25,540,24,560,24,561,25,579,25,580,26,593,26,594,25,633,25,634,29,634,56,635,57,635,111,634,112,634,129,632,134,629,138,623,141,619,145,617,149,611,155,608,161,604,166']), (957285035, 492601069, 445, 280, 481, 2, 55, 0.8299368, [(292, 3, 128), (284, 4, 146), (282, 5, 151), (281, 6, 154), (281, 7, 156), (281, 8, 157), (281, 9, 158), (281, 10, 160), (281, 11, 162), (281, 12, 165), (281, 13, 167), (281, 14, 169), (281, 15, 171), (281, 16, 173), (281, 17, 174), (281, 18, 175), (281, 19, 177), (281, 20, 178), (281, 21, 179), (281, 22, 180), (281, 23, 181), (281, 24, 182), (281, 25, 183), (281, 26, 184), (281, 27, 185), (281, 28, 185), (281, 29, 185), (282, 30, 185), (283, 31, 27), (337, 31, 131), (371, 32, 97), (401, 33, 68), (409, 34, 61), (419, 35, 52), (424, 36, 48), (429, 37, 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(474, 33, 36), (475, 34, 33), (475, 35, 32), (476, 36, 30), (476, 37, 29), (477, 38, 26), (478, 39, 23), (479, 40, 20), (480, 41, 17), (488, 42, 5)], ['492,42,488,42,487,41,480,41,476,37,475,34,473,32,469,25,465,21,461,20,457,16,457,10,463,10,464,9,466,9,470,12,474,13,476,11,480,10,482,8,500,8,501,9,524,9,525,10,528,10,532,12,539,12,542,15,545,15,545,19,535,20,534,21,529,21,525,23,523,23,513,30,512,30,504,37,496,41,493,41'])], 'temp/1739593229_3820514_957285035_a42482e51c93c8025d243dd179aee85b.jpg']} free memory after detection : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10774 ############################### TEST detect object ################################ run mask_detect Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : mask_detect list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.16577720642089844 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:mask_detect Sat Feb 15 05:21:08 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10774 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-02-15 05:21:11.310241: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-15 05:21:11.335124: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-02-15 05:21:11.337217: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f3a8c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-15 05:21:11.337267: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-15 05:21:11.340779: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-15 05:21:11.576167: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2714e750 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-15 05:21:11.576228: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-15 05:21:11.577376: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-15 05:21:11.577694: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:21:11.584073: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:21:11.586652: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-15 05:21:11.587145: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-15 05:21:11.589897: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-15 05:21:11.591431: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-15 05:21:11.596318: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-15 05:21:11.598071: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-15 05:21:11.598141: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:21:11.599084: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-15 05:21:11.599105: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-15 05:21:11.599115: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-15 05:21:11.600739: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9985 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-02-15 05:21:11.731852: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-15 05:21:11.731958: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:21:11.731984: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:21:11.732010: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-15 05:21:11.732034: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-15 05:21:11.732059: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-15 05:21:11.732080: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-15 05:21:11.732102: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-15 05:21:11.733749: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-15 05:21:11.735242: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-15 05:21:11.735315: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:21:11.735342: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:21:11.735368: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-15 05:21:11.735396: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-15 05:21:11.735421: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-15 05:21:11.735446: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-15 05:21:11.735471: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-15 05:21:11.736871: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-15 05:21:11.736907: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-15 05:21:11.736916: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-15 05:21:11.736925: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-15 05:21:11.738379: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9985 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3473, 'mask_coco_origin', 16384, 25088, 'mask_coco_origin', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 3, 19, 10, 42, 21), datetime.datetime(2018, 3, 19, 10, 42, 21)) {'thcl': {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'], 'list_hashtags_csv': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'svm_hashtag_type_desc': 3473, 'photo_desc_type': 3473, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME mask_coco_origin NUM_CLASSES 81 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : mask_coco_origin model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-02-15 05:21:20.220328: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:21:20.405186: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/mask_coco_origin /data/models_weight/mask_coco_origin/mask_model.h5 size_local : 257557808 size in s3 : 257557808 create time local : 2021-08-09 05:27:17 create time in s3 : 2021-08-06 19:45:17 mask_model.h5 already exist and didn't need to update list_images length : 1 NEW PHOTO Processing 1 images image shape: (720, 1280, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 89) min: 0.00000 max: 1280.00000 nb d'objets trouves : 4 Detection mask done ! Trying to reset tf kernel 3823284 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5485 tf kernel not reseted sub process len(results) : 1 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 1 len(list_Values) 0 process is alive finish correctly or not : True after detect begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10774 list_Values should be empty [] ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] time for calcul the mask position with numpy : 0.0007152557373046875 nb_pixel_total : 16902 time to create 1 rle with old method : 0.04056048393249512 length of segment : 107 time for calcul the mask position with numpy : 0.01844954490661621 nb_pixel_total : 480745 time to create 1 rle with new method : 0.028135299682617188 length of segment : 632 time for calcul the mask position with numpy : 0.0004551410675048828 nb_pixel_total : 36582 time to create 1 rle with old method : 0.0802609920501709 length of segment : 132 time for calcul the mask position with numpy : 0.00017452239990234375 nb_pixel_total : 4793 time to create 1 rle with old method : 0.011228322982788086 length of segment : 51 time spent for convertir_results : 0.9089949131011963 time spend for datou_step_exec : 18.841970682144165 time spend to save output : 3.4809112548828125e-05 total time spend for step 1 : 18.842005491256714 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False eke 12-6-18 : saveMask need to be cleaned for new output ! Catched exception ! Connect or reconnect ! Number saved : None batch 1 Loaded 400 chid ids of type : 445 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.02321457862854004 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'917855882': [[(917855882, 492601069, 445, 1092, 1280, 0, 108, 0.99883825, [(1205, 1, 58), (1165, 2, 105), (1159, 3, 113), (1149, 4, 124), (1113, 5, 161), (1100, 6, 174), (1097, 7, 177), (1095, 8, 179), (1095, 9, 179), (1095, 10, 179), (1095, 11, 179), (1095, 12, 179), (1095, 13, 179), (1095, 14, 178), (1095, 15, 178), (1095, 16, 178), (1095, 17, 178), (1095, 18, 177), (1095, 19, 177), (1095, 20, 177), (1095, 21, 177), (1095, 22, 177), (1095, 23, 178), (1095, 24, 178), (1095, 25, 178), (1095, 26, 179), (1095, 27, 179), (1095, 28, 180), (1095, 29, 181), (1095, 30, 182), (1095, 31, 183), (1095, 32, 183), (1095, 33, 184), (1095, 34, 184), (1096, 35, 183), (1096, 36, 183), (1096, 37, 184), (1097, 38, 183), (1097, 39, 183), (1097, 40, 183), (1098, 41, 182), (1098, 42, 182), (1098, 43, 182), (1099, 44, 181), (1099, 45, 181), (1099, 46, 181), (1100, 47, 180), (1100, 48, 180), (1101, 49, 179), (1101, 50, 179), (1102, 51, 178), (1102, 52, 178), (1103, 53, 177), (1103, 54, 177), (1104, 55, 176), (1104, 56, 176), (1104, 57, 176), (1104, 58, 176), (1105, 59, 175), (1105, 60, 175), (1105, 61, 175), (1105, 62, 175), (1105, 63, 175), (1106, 64, 174), (1106, 65, 174), (1106, 66, 174), (1106, 67, 174), (1106, 68, 174), (1106, 69, 174), (1106, 70, 174), (1106, 71, 174), (1106, 72, 174), (1106, 73, 174), (1107, 74, 173), (1107, 75, 173), (1107, 76, 173), (1107, 77, 173), (1107, 78, 173), (1107, 79, 173), (1108, 80, 172), (1108, 81, 172), (1109, 82, 171), (1110, 83, 170), (1110, 84, 170), (1111, 85, 169), (1112, 86, 168), (1113, 87, 166), (1114, 88, 165), (1115, 89, 164), (1117, 90, 162), (1120, 91, 159), (1138, 92, 141), (1146, 93, 133), (1154, 94, 125), (1167, 95, 112), (1177, 96, 102), (1183, 97, 95), (1185, 98, 93), (1187, 99, 90), (1188, 100, 55), (1264, 100, 12), (1190, 101, 50), (1191, 102, 46), (1194, 103, 40), (1197, 104, 34), (1202, 105, 25), (1207, 106, 16)], ['1222,106,1207,106,1206,105,1197,104,1191,102,1182,96,1176,95,1167,95,1166,94,1154,94,1153,93,1146,93,1145,92,1137,91,1120,91,1115,89,1110,84,1107,79,1106,73,1106,64,1104,55,1099,46,1095,34,1095,8,1100,6,1112,6,1113,5,1148,5,1149,4,1158,4,1165,2,1204,2,1205,1,1262,1,1269,2,1273,5,1273,13,1271,18,1271,22,1273,27,1277,31,1279,37,1279,86,1278,87,1278,96,1275,100,1264,100,1263,99,1243,99,1230,104']), (917855882, 492601069, 445, 52, 1128, 16, 668, 0.99774194, [(711, 22, 21), (926, 22, 46), (608, 23, 146), (894, 23, 103), (598, 24, 234), (850, 24, 158), (590, 25, 427), (582, 26, 444), (575, 27, 458), (569, 28, 466), (565, 29, 472), (560, 30, 480), (556, 31, 486), (550, 32, 495), (545, 33, 502), (538, 34, 512), (532, 35, 520), (527, 36, 527), (523, 37, 534), (518, 38, 541), (514, 39, 548), (510, 40, 554), (506, 41, 561), (503, 42, 566), (499, 43, 572), (496, 44, 577), (493, 45, 582), (491, 46, 585), (489, 47, 589), (487, 48, 592), (485, 49, 595), (483, 50, 598), (482, 51, 600), (481, 52, 602), (480, 53, 603), (479, 54, 605), (478, 55, 606), (476, 56, 608), (475, 57, 610), (474, 58, 611), (473, 59, 613), (472, 60, 614), (470, 61, 616), (469, 62, 618), (468, 63, 619), (466, 64, 621), (465, 65, 623), (464, 66, 624), (462, 67, 626), (461, 68, 628), (459, 69, 630), (458, 70, 631), (456, 71, 633), (455, 72, 635), (453, 73, 637), (452, 74, 638), (451, 75, 639), (450, 76, 640), (448, 77, 642), (447, 78, 643), (446, 79, 644), (445, 80, 645), (444, 81, 646), (442, 82, 648), (441, 83, 649), (440, 84, 650), (439, 85, 651), (438, 86, 652), (437, 87, 653), (436, 88, 654), (435, 89, 655), (434, 90, 656), (433, 91, 657), (432, 92, 658), (431, 93, 659), (430, 94, 660), (429, 95, 661), (428, 96, 662), (427, 97, 663), (425, 98, 665), (423, 99, 667), (421, 100, 669), (419, 101, 671), (417, 102, 673), (413, 103, 677), (410, 104, 680), (405, 105, 685), (401, 106, 689), (397, 107, 693), (392, 108, 698), (387, 109, 703), (382, 110, 708), (377, 111, 713), (373, 112, 717), (368, 113, 722), (365, 114, 725), (362, 115, 728), (358, 116, 732), (356, 117, 734), (353, 118, 737), (351, 119, 739), (348, 120, 742), (346, 121, 744), (344, 122, 746), (341, 123, 749), (338, 124, 752), (335, 125, 755), (331, 126, 759), (327, 127, 763), (323, 128, 766), (319, 129, 770), (314, 130, 775), (308, 131, 781), (303, 132, 786), (294, 133, 795), (286, 134, 803), (279, 135, 810), (273, 136, 816), (266, 137, 823), (262, 138, 827), (258, 139, 831), (255, 140, 834), (252, 141, 837), (250, 142, 839), (247, 143, 842), (245, 144, 844), (242, 145, 847), (240, 146, 849), (237, 147, 852), (233, 148, 856), (230, 149, 859), (226, 150, 863), (220, 151, 869), (213, 152, 876), (206, 153, 883), (200, 154, 889), (193, 155, 896), (187, 156, 902), (183, 157, 906), (181, 158, 908), (178, 159, 911), (176, 160, 913), (174, 161, 915), (172, 162, 917), (170, 163, 919), (168, 164, 921), (167, 165, 922), (165, 166, 924), (164, 167, 925), (162, 168, 927), (161, 169, 928), (159, 170, 930), (157, 171, 932), (155, 172, 934), (153, 173, 935), (151, 174, 937), (148, 175, 940), (146, 176, 942), (144, 177, 944), (142, 178, 946), (140, 179, 948), (139, 180, 949), (137, 181, 951), (136, 182, 952), (134, 183, 954), (133, 184, 955), (132, 185, 956), (131, 186, 957), (130, 187, 958), (129, 188, 959), (128, 189, 960), (127, 190, 960), (126, 191, 961), (126, 192, 961), (125, 193, 962), (124, 194, 963), (123, 195, 964), (122, 196, 965), (122, 197, 965), (121, 198, 966), (120, 199, 967), (119, 200, 968), (118, 201, 969), (117, 202, 970), (116, 203, 971), (114, 204, 973), (113, 205, 973), (112, 206, 974), (111, 207, 975), (109, 208, 977), (108, 209, 978), (107, 210, 979), (106, 211, 980), (104, 212, 982), (104, 213, 982), (103, 214, 983), (102, 215, 984), (101, 216, 985), (101, 217, 984), (100, 218, 985), (99, 219, 986), (99, 220, 986), (98, 221, 987), (98, 222, 987), (97, 223, 988), (97, 224, 987), (96, 225, 988), (96, 226, 988), (95, 227, 989), (95, 228, 989), (94, 229, 990), (94, 230, 990), (94, 231, 990), (93, 232, 990), (93, 233, 990), (92, 234, 991), (92, 235, 991), (92, 236, 991), (91, 237, 992), (91, 238, 991), (91, 239, 991), (91, 240, 990), (91, 241, 990), (90, 242, 991), (90, 243, 990), (90, 244, 990), (90, 245, 989), (90, 246, 989), (89, 247, 990), (89, 248, 989), (89, 249, 989), (89, 250, 988), (89, 251, 988), (88, 252, 988), (88, 253, 988), (88, 254, 987), (88, 255, 986), (88, 256, 986), (87, 257, 986), (87, 258, 985), (87, 259, 985), (87, 260, 984), (87, 261, 983), (86, 262, 983), (86, 263, 982), (86, 264, 982), (86, 265, 981), (85, 266, 981), (85, 267, 980), (85, 268, 980), (84, 269, 980), (84, 270, 979), (84, 271, 979), (84, 272, 978), (83, 273, 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[(414, 0, 7), (441, 0, 60), (508, 0, 28), (402, 1, 142), (401, 2, 146), (402, 3, 145), (404, 4, 143), (406, 5, 140), (408, 6, 137), (410, 7, 134), (411, 8, 132), (412, 9, 130), (413, 10, 127), (414, 11, 125), (415, 12, 123), (415, 13, 122), (416, 14, 120), (417, 15, 117), (417, 16, 116), (418, 17, 114), (418, 18, 113), (418, 19, 111), (418, 20, 109), (419, 21, 107), (419, 22, 105), (419, 23, 103), (419, 24, 102), (420, 25, 99), (420, 26, 97), (420, 27, 95), (420, 28, 94), (421, 29, 91), (421, 30, 90), (422, 31, 88), (422, 32, 88), (422, 33, 87), (423, 34, 84), (423, 35, 82), (423, 36, 81), (424, 37, 79), (424, 38, 77), (424, 39, 75), (424, 40, 73), (424, 41, 71), (425, 42, 67), (425, 43, 66), (426, 44, 62), (426, 45, 6), (433, 45, 52), (443, 46, 30), (450, 47, 1)], ['449,46,443,46,442,45,426,45,424,41,424,37,423,36,422,31,420,28,420,25,419,24,419,21,418,20,418,17,417,15,409,6,402,3,402,1,413,1,414,0,420,0,421,1,440,1,441,0,500,0,501,1,507,1,508,0,535,0,536,1,543,1,546,2,546,4,542,8,530,18,527,19,525,21,522,22,520,24,512,28,508,33,505,34,502,37,494,41,492,41,490,43,488,43,484,45,473,45,472,46'])], 'temp/1739593268_3820514_917855882_da0fa7b7e6b5b551fe26c0ba8713276d.jpg']} ############################### TEST POLYGON ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : mask_detect list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.12208676338195801 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:mask_detect Sat Feb 15 05:21:37 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 10774 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-02-15 05:21:40.925856: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-15 05:21:40.955148: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-02-15 05:21:40.957273: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f3a8c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-15 05:21:40.957326: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-15 05:21:40.960932: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-15 05:21:41.197816: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2691b770 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-15 05:21:41.197867: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-15 05:21:41.199323: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-15 05:21:41.199716: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:21:41.202658: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:21:41.205760: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-15 05:21:41.206235: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-15 05:21:41.208854: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-15 05:21:41.209814: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-15 05:21:41.214181: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-15 05:21:41.215806: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-15 05:21:41.215871: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:21:41.216607: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-15 05:21:41.216621: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-15 05:21:41.216629: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-15 05:21:41.217913: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9985 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-02-15 05:21:41.333698: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-15 05:21:41.333809: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:21:41.333833: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:21:41.333853: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-15 05:21:41.333873: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-15 05:21:41.333892: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-15 05:21:41.333911: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-15 05:21:41.333930: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-15 05:21:41.335219: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-15 05:21:41.336518: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-15 05:21:41.336595: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:21:41.336613: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:21:41.336643: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-15 05:21:41.336660: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-15 05:21:41.336676: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-15 05:21:41.336692: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-15 05:21:41.336709: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-15 05:21:41.338025: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-15 05:21:41.338061: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-15 05:21:41.338070: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-15 05:21:41.338079: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-15 05:21:41.339403: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 9985 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) Using TensorFlow backend. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:396: calling crop_and_resize_v1 (from tensorflow.python.ops.image_ops_impl) with box_ind is deprecated and will be removed in a future version. Instructions for updating: box_ind is deprecated, use box_indices instead WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:703: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. WARNING:tensorflow:From /home/admin/workarea/install/Mask_RCNN/model.py:729: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version. Instructions for updating: Use `tf.cast` instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3473, 'mask_coco_origin', 16384, 25088, 'mask_coco_origin', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 3, 19, 10, 42, 21), datetime.datetime(2018, 3, 19, 10, 42, 21)) {'thcl': {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'], 'list_hashtags_csv': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'svm_hashtag_type_desc': 3473, 'photo_desc_type': 3473, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME mask_coco_origin NUM_CLASSES 81 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 model_param file didn't exist model_name : mask_coco_origin model_type : mask_rcnn list file need : ['mask_model.h5'] file exist in s3 : ['mask_model.h5'] file manque in s3 : [] 2025-02-15 05:21:52.060850: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:21:52.247871: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 local folder : /data/models_weight/mask_coco_origin /data/models_weight/mask_coco_origin/mask_model.h5 size_local : 257557808 size in s3 : 257557808 create time local : 2021-08-09 05:27:17 create time in s3 : 2021-08-06 19:45:17 mask_model.h5 already exist and didn't need to update list_images length : 1 NEW PHOTO Processing 1 images image shape: (2448, 2448, 3) min: 0.00000 max: 255.00000 molded_images shape: (1, 640, 640, 3) min: -123.70000 max: 151.10000 image_metas shape: (1, 89) min: 0.00000 max: 2448.00000 nb d'objets trouves : 1 Detection mask done ! Trying to reset tf kernel 3824599 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 5485 tf kernel not reseted sub process len(results) : 1 len(list_Values) 0 None max_time_sub_proc : 3600 parent process len(results) : 1 len(list_Values) 0 process is alive finish correctly or not : True after detect begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 10774 list_Values should be empty [] ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] time for calcul the mask position with numpy : 0.20403122901916504 nb_pixel_total : 3688930 time to create 1 rle with new method : 0.26877546310424805 length of segment : 2036 time spent for convertir_results : 1.6832919120788574 time spend for datou_step_exec : 22.048349142074585 time spend to save output : 2.47955322265625e-05 total time spend for step 1 : 22.04837393760681 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False eke 12-6-18 : saveMask need to be cleaned for new output ! Catched exception ! Connect or reconnect ! Number saved : None batch 1 Loaded 718 chid ids of type : 445 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.01654219627380371 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'917877156': [[(917877156, 492601069, 445, 7, 2264, 122, 2237, 0.98499286, [(522, 124, 446), (1148, 124, 277), (501, 125, 949), (480, 126, 993), (461, 127, 1035), (443, 128, 1096), (427, 129, 1153), (411, 130, 1178), (397, 131, 1200), (382, 132, 1223), (370, 133, 1243), (367, 134, 1254), (364, 135, 1264), (361, 136, 1274), (359, 137, 1283), (356, 138, 1292), (354, 139, 1300), (351, 140, 1309), (349, 141, 1316), (347, 142, 1322), (345, 143, 1328), (343, 144, 1334), (341, 145, 1340), (339, 146, 1346), (337, 147, 1351), (336, 148, 1356), (334, 149, 1361), (332, 150, 1367), (331, 151, 1371), (329, 152, 1376), (328, 153, 1380), (326, 154, 1385), (325, 155, 1389), (323, 156, 1393), (322, 157, 1397), (321, 158, 1401), (319, 159, 1405), (318, 160, 1409), (317, 161, 1412), (316, 162, 1416), (315, 163, 1420), (313, 164, 1424), (312, 165, 1428), (311, 166, 1431), (309, 167, 1435), (308, 168, 1438), (306, 169, 1443), (305, 170, 1446), (303, 171, 1450), (302, 172, 1453), (300, 173, 1458), (298, 174, 1462), (297, 175, 1466), (295, 176, 1471), (293, 177, 1475), (291, 178, 1480), (289, 179, 1485), (286, 180, 1491), (284, 181, 1496), (281, 182, 1502), (279, 183, 1508), (276, 184, 1514), (273, 185, 1521), (271, 186, 1526), (268, 187, 1533), (265, 188, 1540), (262, 189, 1547), (260, 190, 1554), (257, 191, 1561), (254, 192, 1569), (251, 193, 1579), (249, 194, 1587), (246, 195, 1596), (243, 196, 1605), (240, 197, 1615), (237, 198, 1624), (234, 199, 1633), (231, 200, 1642), (229, 201, 1650), (226, 202, 1659), (223, 203, 1667), (220, 204, 1676), (217, 205, 1685), (214, 206, 1690), (211, 207, 1694), (208, 208, 1699), (206, 209, 1703), (204, 210, 1707), (202, 211, 1710), (201, 212, 1713), (199, 213, 1717), (197, 214, 1720), (196, 215, 1723), (194, 216, 1726), (193, 217, 1728), (192, 218, 1731), (190, 219, 1734), (189, 220, 1736), (187, 221, 1739), (186, 222, 1741), (185, 223, 1743), (184, 224, 1746), (183, 225, 1748), (182, 226, 1750), (180, 227, 1753), (179, 228, 1755), (178, 229, 1756), (177, 230, 1758), (176, 231, 1760), (175, 232, 1762), (174, 233, 1764), (173, 234, 1766), (173, 235, 1767), (172, 236, 1768), (171, 237, 1770), (170, 238, 1772), (169, 239, 1773), (168, 240, 1775), (167, 241, 1777), (166, 242, 1779), (165, 243, 1781), (164, 244, 1782), (163, 245, 1784), (162, 246, 1786), (161, 247, 1788), (160, 248, 1790), (159, 249, 1792), (158, 250, 1794), (157, 251, 1796), (156, 252, 1798), (154, 253, 1801), (153, 254, 1803), (152, 255, 1805), (151, 256, 1807), (149, 257, 1810), (148, 258, 1812), (147, 259, 1815), (145, 260, 1818), (144, 261, 1820), (142, 262, 1824), (141, 263, 1826), (139, 264, 1829), (138, 265, 1832), (136, 266, 1835), (134, 267, 1839), (133, 268, 1841), (131, 269, 1845), (129, 270, 1849), (127, 271, 1852), (126, 272, 1855), (125, 273, 1858), (123, 274, 1862), (122, 275, 1864), (121, 276, 1867), (119, 277, 1870), (118, 278, 1873), (117, 279, 1875), (116, 280, 1878), (115, 281, 1880), (114, 282, 1882), (113, 283, 1885), (112, 284, 1887), (111, 285, 1889), (110, 286, 1891), (109, 287, 1893), (108, 288, 1895), (107, 289, 1897), (106, 290, 1899), (105, 291, 1901), (105, 292, 1902), (104, 293, 1904), (103, 294, 1906), (102, 295, 1908), (102, 296, 1909), (101, 297, 1911), (100, 298, 1913), (99, 299, 1915), (99, 300, 1915), (98, 301, 1917), (97, 302, 1919), (97, 303, 1920), (96, 304, 1921), (96, 305, 1922), (95, 306, 1924), (94, 307, 1926), (94, 308, 1926), (93, 309, 1928), (93, 310, 1929), (92, 311, 1930), (92, 312, 1931), (92, 313, 1931), (92, 314, 1932), (91, 315, 1933), (91, 316, 1934), (91, 317, 1934), (91, 318, 1935), (90, 319, 1936), (90, 320, 1937), (90, 321, 1937), (90, 322, 1938), (89, 323, 1940), (89, 324, 1940), (89, 325, 1941), (89, 326, 1941), (88, 327, 1943), (88, 328, 1944), (88, 329, 1944), (87, 330, 1946), (87, 331, 1946), (87, 332, 1947), (87, 333, 1948), (86, 334, 1950), (86, 335, 1950), (86, 336, 1951), (86, 337, 1952), (85, 338, 1953), (85, 339, 1954), (85, 340, 1955), (84, 341, 1957), (84, 342, 1957), (84, 343, 1958), (84, 344, 1959), (83, 345, 1961), (83, 346, 1962), (83, 347, 1963), (82, 348, 1964), (82, 349, 1965), (82, 350, 1966), (82, 351, 1967), (81, 352, 1969), (81, 353, 1970), (81, 354, 1971), (80, 355, 1973), (80, 356, 1974), (80, 357, 1975), (79, 358, 1977), (79, 359, 1978), (79, 360, 1979), (79, 361, 1981), (78, 362, 1983), (78, 363, 1984), (78, 364, 1985), (77, 365, 1987), (77, 366, 1988), (77, 367, 1989), (76, 368, 1991), (76, 369, 1992), (76, 370, 1993), (75, 371, 1995), (75, 372, 1996), (75, 373, 1997), (75, 374, 1998), (74, 375, 2000), (74, 376, 2001), (74, 377, 2002), (73, 378, 2003), (73, 379, 2004), (73, 380, 2005), (72, 381, 2007), (72, 382, 2007), (72, 383, 2008), (71, 384, 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pixel non reg : 3692295 nb pixel common : 3684517 proportion of common points : 0.9978934510920715 #&_# TEST SUCCEEDED #&_# : tests/mask_test #&_# #&_# END OF TEST #&_# : tests/mask_test #&_# #&_# BEGIN OF TEST : tests/datou_test #&_# /home/admin/workarea/git/Velours/python/tests/datou_test.py Datou All Test python version used : 3 ############################### TEST sam ################################ TEST SAM Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : sam list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.18850302696228027 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! WARNING : we have an input that is not a photo, we should get rid of it Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:sam Sat Feb 15 05:22:08 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step sam ! Inside sam : nb paths : 1 (640, 960, 3) time for calcul the mask position with numpy : 0.0016415119171142578 nb_pixel_total : 5626 time to create 1 rle with old method : 0.017259597778320312 time for calcul the mask position with numpy : 0.0015759468078613281 nb_pixel_total : 13945 time to create 1 rle with old method : 0.030695438385009766 time for calcul the mask position with numpy : 0.0014028549194335938 nb_pixel_total : 16291 time to create 1 rle with old method : 0.036072492599487305 time for calcul the mask position with numpy : 0.0014116764068603516 nb_pixel_total : 4273 time to create 1 rle with old method : 0.010874509811401367 time for calcul the mask position with numpy : 0.0013926029205322266 nb_pixel_total : 6623 time to create 1 rle with old method : 0.01490926742553711 time for calcul the mask position with numpy : 0.0014739036560058594 nb_pixel_total : 5863 time to create 1 rle with old method : 0.012919902801513672 time for calcul the mask position with numpy : 0.0014865398406982422 nb_pixel_total : 16481 time to create 1 rle with old method : 0.03713345527648926 time for calcul the mask position with numpy : 0.001413106918334961 nb_pixel_total : 10825 time to create 1 rle with old method : 0.025913238525390625 time for calcul the mask position with numpy : 0.001451730728149414 nb_pixel_total : 2939 time to create 1 rle with old method : 0.006642580032348633 time for calcul the mask position with numpy : 0.0014064311981201172 nb_pixel_total : 7624 time to create 1 rle with old method : 0.01682257652282715 time for calcul the mask position with numpy : 0.0014758110046386719 nb_pixel_total : 4161 time to create 1 rle with old method : 0.009692192077636719 time for calcul the mask position with numpy : 0.0013823509216308594 nb_pixel_total : 5275 time to create 1 rle with old method : 0.011989593505859375 time for calcul the mask position with numpy : 0.0014770030975341797 nb_pixel_total : 5518 time to create 1 rle with old method : 0.012052059173583984 time for calcul the mask position with numpy : 0.0014338493347167969 nb_pixel_total : 3780 time to create 1 rle with old method : 0.008409976959228516 time for calcul the mask position with numpy : 0.0014219284057617188 nb_pixel_total : 267 time to create 1 rle with old method : 0.0006642341613769531 time for calcul the mask position with numpy : 0.0014395713806152344 nb_pixel_total : 29474 time to create 1 rle with old method : 0.0622563362121582 time for calcul the mask position with numpy : 0.0017483234405517578 nb_pixel_total : 84177 time to create 1 rle with old method : 0.17739152908325195 time for calcul the mask position with numpy : 0.001425027847290039 nb_pixel_total : 2079 time to create 1 rle with old method : 0.004374504089355469 time for calcul the mask position with numpy : 0.0014510154724121094 nb_pixel_total : 1845 time to create 1 rle with old method : 0.003989696502685547 time for calcul the mask position with numpy : 0.00128936767578125 nb_pixel_total : 1025 time to create 1 rle with old method : 0.0022461414337158203 time for calcul the mask position with numpy : 0.0013871192932128906 nb_pixel_total : 1226 time to create 1 rle with old method : 0.0026531219482421875 time for calcul the mask position with numpy : 0.0013074874877929688 nb_pixel_total : 2453 time to create 1 rle with old method : 0.005528926849365234 time for calcul the mask position with numpy : 0.0013239383697509766 nb_pixel_total : 3958 time to create 1 rle with old method : 0.008559465408325195 time for calcul the mask position with numpy : 0.0012950897216796875 nb_pixel_total : 574 time to create 1 rle with old method : 0.001275777816772461 time for calcul the mask position with numpy : 0.0013055801391601562 nb_pixel_total : 3088 time to create 1 rle with old method : 0.00677943229675293 time for calcul the mask position with numpy : 0.0013966560363769531 nb_pixel_total : 8274 time to create 1 rle with old method : 0.018281221389770508 time for calcul the mask position with numpy : 0.0013883113861083984 nb_pixel_total : 12802 time to create 1 rle with old method : 0.027395248413085938 time for calcul the mask position with numpy : 0.0013155937194824219 nb_pixel_total : 2723 time to create 1 rle with old method : 0.005980253219604492 time for calcul the mask position with numpy : 0.0014374256134033203 nb_pixel_total : 27886 time to create 1 rle with old method : 0.05931258201599121 time for calcul the mask position with numpy : 0.001379251480102539 nb_pixel_total : 8631 time to create 1 rle with old method : 0.019193649291992188 time for calcul the mask position with numpy : 0.001344919204711914 nb_pixel_total : 1717 time to create 1 rle with old method : 0.003760099411010742 time for calcul the mask position with numpy : 0.0012907981872558594 nb_pixel_total : 1636 time to create 1 rle with old method : 0.0035386085510253906 time for calcul the mask position with numpy : 0.001476287841796875 nb_pixel_total : 38959 time to create 1 rle with old method : 0.08217501640319824 time for calcul the mask position with numpy : 0.0014791488647460938 nb_pixel_total : 7666 time to create 1 rle with old method : 0.016666173934936523 time for calcul the mask position with numpy : 0.001318216323852539 nb_pixel_total : 861 time to create 1 rle with old method : 0.0019888877868652344 time for calcul the mask position with numpy : 0.001298666000366211 nb_pixel_total : 3530 time to create 1 rle with old method : 0.007788658142089844 time for calcul the mask position with numpy : 0.0013036727905273438 nb_pixel_total : 943 time to create 1 rle with old method : 0.0022988319396972656 time for calcul the mask position with numpy : 0.0013408660888671875 nb_pixel_total : 11956 time to create 1 rle with old method : 0.024989604949951172 time for calcul the mask position with numpy : 0.00130462646484375 nb_pixel_total : 3936 time to create 1 rle with old method : 0.008376836776733398 time for calcul the mask position with numpy : 0.0013310909271240234 nb_pixel_total : 8601 time to create 1 rle with old method : 0.01782846450805664 time for calcul the mask position with numpy : 0.001276254653930664 nb_pixel_total : 1626 time to create 1 rle with old method : 0.003481149673461914 time for calcul the mask position with numpy : 0.0013539791107177734 nb_pixel_total : 14667 time to create 1 rle with old method : 0.03114604949951172 time for calcul the mask position with numpy : 0.0013322830200195312 nb_pixel_total : 2446 time to create 1 rle with old method : 0.005249500274658203 time for calcul the mask position with numpy : 0.0013234615325927734 nb_pixel_total : 9908 time to create 1 rle with old method : 0.021691322326660156 time for calcul the mask position with numpy : 0.0013089179992675781 nb_pixel_total : 2323 time to create 1 rle with old method : 0.005073070526123047 time for calcul the mask position with numpy : 0.001295328140258789 nb_pixel_total : 970 time to create 1 rle with old method : 0.002187490463256836 time for calcul the mask position with numpy : 0.0013055801391601562 nb_pixel_total : 2786 time to create 1 rle with old method : 0.006076812744140625 time for calcul the mask position with numpy : 0.0014233589172363281 nb_pixel_total : 339 time to create 1 rle with old method : 0.0008800029754638672 time for calcul the mask position with numpy : 0.001291036605834961 nb_pixel_total : 1260 time to create 1 rle with old method : 0.002794027328491211 time for calcul the mask position with numpy : 0.0012998580932617188 nb_pixel_total : 3328 time to create 1 rle with old method : 0.0071871280670166016 time for calcul the mask position with numpy : 0.001283884048461914 nb_pixel_total : 349 time to create 1 rle with old method : 0.0007855892181396484 time for calcul the mask position with numpy : 0.0013034343719482422 nb_pixel_total : 4141 time to create 1 rle with old method : 0.009220600128173828 time for calcul the mask position with numpy : 0.0013473033905029297 nb_pixel_total : 10620 time to create 1 rle with old method : 0.02341294288635254 time for calcul the mask position with numpy : 0.0016331672668457031 nb_pixel_total : 39264 time to create 1 rle with old method : 0.0841987133026123 time for calcul the mask position with numpy : 0.001417398452758789 nb_pixel_total : 2417 time to create 1 rle with old method : 0.005457401275634766 time for calcul the mask position with numpy : 0.0013947486877441406 nb_pixel_total : 4176 time to create 1 rle with old method : 0.008908987045288086 time for calcul the mask position with numpy : 0.0012946128845214844 nb_pixel_total : 595 time to create 1 rle with old method : 0.0013146400451660156 time for calcul the mask position with numpy : 0.00128173828125 nb_pixel_total : 875 time to create 1 rle with old method : 0.0019884109497070312 time for calcul the mask position with numpy : 0.0012791156768798828 nb_pixel_total : 888 time to create 1 rle with old method : 0.0019559860229492188 time for calcul the mask position with numpy : 0.0013933181762695312 nb_pixel_total : 692 time to create 1 rle with old method : 0.0015392303466796875 time for calcul the mask position with numpy : 0.001344919204711914 nb_pixel_total : 1674 time to create 1 rle with old method : 0.003864765167236328 time for calcul the mask position with numpy : 0.0013837814331054688 nb_pixel_total : 2411 time to create 1 rle with old method : 0.00551605224609375 time for calcul the mask position with numpy : 0.0012905597686767578 nb_pixel_total : 298 time to create 1 rle with old method : 0.0007386207580566406 time for calcul the mask position with numpy : 0.001287698745727539 nb_pixel_total : 1208 time to create 1 rle with old method : 0.0026092529296875 time for calcul the mask position with numpy : 0.0012884140014648438 nb_pixel_total : 2773 time to create 1 rle with old method : 0.005883932113647461 time for calcul the mask position with numpy : 0.0012805461883544922 nb_pixel_total : 1066 time to create 1 rle with old method : 0.0023734569549560547 time for calcul the mask position with numpy : 0.001268625259399414 nb_pixel_total : 585 time to create 1 rle with old method : 0.0012946128845214844 time for calcul the mask position with numpy : 0.0012812614440917969 nb_pixel_total : 1087 time to create 1 rle with old method : 0.0025565624237060547 time for calcul the mask position with numpy : 0.0013844966888427734 nb_pixel_total : 13076 time to create 1 rle with old method : 0.02765798568725586 time for calcul the mask position with numpy : 0.001386404037475586 nb_pixel_total : 16667 time to create 1 rle with old method : 0.03801870346069336 time for calcul the mask position with numpy : 0.001512289047241211 nb_pixel_total : 1632 time to create 1 rle with old method : 0.0036334991455078125 time for calcul the mask position with numpy : 0.0013363361358642578 nb_pixel_total : 1741 time to create 1 rle with old method : 0.0036973953247070312 time for calcul the mask position with numpy : 0.0012881755828857422 nb_pixel_total : 1339 time to create 1 rle with old method : 0.0031440258026123047 time for calcul the mask position with numpy : 0.0013031959533691406 nb_pixel_total : 4458 time to create 1 rle with old method : 0.009823799133300781 time for calcul the mask position with numpy : 0.001434326171875 nb_pixel_total : 1507 time to create 1 rle with old method : 0.0034990310668945312 time for calcul the mask position with numpy : 0.0014455318450927734 nb_pixel_total : 1009 time to create 1 rle with old method : 0.002341032028198242 time for calcul the mask position with numpy : 0.001329183578491211 nb_pixel_total : 713 time to create 1 rle with old method : 0.0017697811126708984 time for calcul the mask position with numpy : 0.0013432502746582031 nb_pixel_total : 9078 time to create 1 rle with old method : 0.019608259201049805 time for calcul the mask position with numpy : 0.0013394355773925781 nb_pixel_total : 9504 time to create 1 rle with old method : 0.020076274871826172 time for calcul the mask position with numpy : 0.0013129711151123047 nb_pixel_total : 7438 time to create 1 rle with old method : 0.015281438827514648 time for calcul the mask position with numpy : 0.0012819766998291016 nb_pixel_total : 3166 time to create 1 rle with old method : 0.006984233856201172 time for calcul the mask position with numpy : 0.0012981891632080078 nb_pixel_total : 837 time to create 1 rle with old method : 0.0019292831420898438 time for calcul the mask position with numpy : 0.0012857913970947266 nb_pixel_total : 614 time to create 1 rle with old method : 0.001367807388305664 time for calcul the mask position with numpy : 0.0013859272003173828 nb_pixel_total : 248 time to create 1 rle with old method : 0.0006070137023925781 time for calcul the mask position with numpy : 0.0012867450714111328 nb_pixel_total : 975 time to create 1 rle with old method : 0.002248525619506836 time for calcul the mask position with numpy : 0.0012819766998291016 nb_pixel_total : 221 time to create 1 rle with old method : 0.0005390644073486328 time for calcul the mask position with numpy : 0.0014030933380126953 nb_pixel_total : 1121 time to create 1 rle with old method : 0.0024356842041015625 time for calcul the mask position with numpy : 0.001451730728149414 nb_pixel_total : 1613 time to create 1 rle with old method : 0.0037648677825927734 time for calcul the mask position with numpy : 0.0013251304626464844 nb_pixel_total : 735 time to create 1 rle with old method : 0.0017483234405517578 time for calcul the mask position with numpy : 0.0014426708221435547 nb_pixel_total : 1498 time to create 1 rle with old method : 0.003333568572998047 time for calcul the mask position with numpy : 0.0012898445129394531 nb_pixel_total : 1386 time to create 1 rle with old method : 0.0031859874725341797 time for calcul the mask position with numpy : 0.0013651847839355469 nb_pixel_total : 1320 time to create 1 rle with old method : 0.003018617630004883 time for calcul the mask position with numpy : 0.0012912750244140625 nb_pixel_total : 1437 time to create 1 rle with old method : 0.0033516883850097656 time for calcul the mask position with numpy : 0.0012869834899902344 nb_pixel_total : 586 time to create 1 rle with old method : 0.0014317035675048828 time for calcul the mask position with numpy : 0.0013785362243652344 nb_pixel_total : 2200 time to create 1 rle with old method : 0.004930257797241211 time for calcul the mask position with numpy : 0.0014295578002929688 nb_pixel_total : 947 time to create 1 rle with old method : 0.002110004425048828 time for calcul the mask position with numpy : 0.0013022422790527344 nb_pixel_total : 823 time to create 1 rle with old method : 0.0018510818481445312 time for calcul the mask position with numpy : 0.001293182373046875 nb_pixel_total : 1603 time to create 1 rle with old method : 0.003685474395751953 time for calcul the mask position with numpy : 0.0013663768768310547 nb_pixel_total : 952 time to create 1 rle with old method : 0.002183675765991211 time for calcul the mask position with numpy : 0.0013000965118408203 nb_pixel_total : 881 time to create 1 rle with old method : 0.0020422935485839844 time for calcul the mask position with numpy : 0.0013391971588134766 nb_pixel_total : 193 time to create 1 rle with old method : 0.0005085468292236328 time for calcul the mask position with numpy : 0.0012803077697753906 nb_pixel_total : 1334 time to create 1 rle with old method : 0.002941608428955078 time for calcul the mask position with numpy : 0.001275777816772461 nb_pixel_total : 338 time to create 1 rle with old method : 0.0007596015930175781 time for calcul the mask position with numpy : 0.0012998580932617188 nb_pixel_total : 2334 time to create 1 rle with old method : 0.0049784183502197266 time for calcul the mask position with numpy : 0.0012784004211425781 nb_pixel_total : 887 time to create 1 rle with old method : 0.0019397735595703125 batch 1 Loaded 105 chid ids of type : 4677 Number RLEs to save : 9317 TO DO : save crop sub photo not yet done ! Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : sam we use saveGeneral [1189321094] Looping around the photos to save general results len do output : 1 /1189321094Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4573', None, None, None, None, None, None, None, None) ('4573', None, '1189321094', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 time used for this insertion : 0.4163239002227783 save_final save missing photos in datou_result : time spend for datou_step_exec : 12.982433557510376 time spend to save output : 0.4167487621307373 total time spend for step 1 : 13.399182319641113 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'1189321094': [[, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ], 'temp/1739593328_3820514_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png']} nb_objects detect : 105 ############################### TEST frcnn ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : frcnn list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.4922797679901123 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:frcnn Sat Feb 15 05:22:22 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step Faster rcnn ! To loadFromThcl() model_param file didn't exist model_name : detection_plaque_valcor_010622 model_type : caffe_faster_rcnn list file need : ['caffemodel', 'test.prototxt'] file exist in s3 : ['caffemodel', 'test.prototxt'] file manque in s3 : [] local folder : /data/models_weight/detection_plaque_valcor_010622 /data/models_weight/detection_plaque_valcor_010622/caffemodel size_local : 349723073 size in s3 : 349723073 create time local : 2022-07-12 14:12:27 create time in s3 : 2022-06-01 15:05:56 caffemodel already exist and didn't need to update /data/models_weight/detection_plaque_valcor_010622/test.prototxt size_local : 7163 size in s3 : 7163 create time local : 2022-07-12 14:12:27 create time in s3 : 2022-06-01 15:05:55 test.prototxt already exist and didn't need to update prototxt : /data/models_weight/detection_plaque_valcor_010622/test.prototxt caffemodel : /data/models_weight/detection_plaque_valcor_010622/caffemodel Loaded network /data/models_weight/detection_plaque_valcor_010622/caffemodel About to compute detect_faster_rcnn : len(args) : 1 Inside frcnn step exec : nb paths : 1 image_path : temp/1739593342_3820514_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg image_size (600, 800, 3) [[[ 4 6 6] [ 5 7 7] [ 6 8 8] ... [207 215 214] [206 214 213] [206 214 213]] [[ 4 6 6] [ 5 7 7] [ 6 8 8] ... [207 215 214] [206 214 213] [206 214 213]] [[ 4 6 6] [ 5 7 7] [ 6 8 8] ... [207 215 214] [206 214 213] [206 214 213]] ... [[ 14 16 16] [ 13 15 15] [ 11 13 13] ... [198 206 205] [198 206 205] [198 206 205]] [[ 16 18 18] [ 14 16 16] [ 11 13 13] ... [206 214 213] [206 214 213] [206 214 213]] [[ 13 15 15] [ 12 14 14] [ 9 11 11] ... [210 218 217] [210 218 217] [210 218 217]]] Detection took 0.086s for 300 object proposals len de result frcnn : 1 time spend for datou_step_exec : 2.9591805934906006 time spend to save output : 0.000148773193359375 total time spend for step 1 : 2.95932936668396 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False Inside saveFrcnn : final : True verbose : False threshold to save the result : 0.1 Warning : no hashtag_ids to insert in the database final : True begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.7794022560119629 [917754606] Looping around the photos to save general results len do output : 1 /0 before output type Managing all output in save final without adding information in the mtr_datou_result ('4184', None, None, None, None, None, None, None, None) ('4184', None, '917754606', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.01291966438293457 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {0: [[(0, 493029425, 4370, 374, 430, 293, 317, 0.06383547, None), (0, 493029425, 4370, 382, 552, 297, 344, 0.052226532, None), (0, 493029425, 4370, 345, 468, 272, 320, 0.012269322, None)], 'temp/1739593342_3820514_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg']} ############################### TEST thcl ################################ TEST THCL Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 1 thcl is not linked in the step_by_step architecture ! WARNING : step 2 argmax is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! List Step Type Loaded in datou : thcl, argmax list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.5139944553375244 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 2 step1:thcl Sat Feb 15 05:22:27 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step Thcl ! we are using the classfication for only one thcl 355 time to import caffe and check if the image exist : 0.009613752365112305 time to convert the images to numpy array : 0.0009434223175048828 total time to convert the images to numpy array : 0.01088714599609375 list photo_ids error: [] list photo_ids correct : [916235064] number of photos to traite : 1 try to delete the photos incorrect in DB tagging for thcl : 355 To do loadFromThcl(), then load ParamDescType : thcl355 thcls : [{'id': 355, 'mtr_user_id': 31, 'name': 'car_360_1027', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 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'506302,506374,506399,506192,506205,506350,506052,506295,506066,506117,506065,506125,506387,506381,506349,506328,506377,506286,506124,506172,506206,506178,506371,506076,506114,506329,506122,506220,506174,506224,506232,506234,506173,506181,506323,506326,506376,506048,506400,506179,506311,506325,506402,506051,506294,506318,506303,506175,506099,506061,506337,506250,506082,506166,506133,506308,506078,506340,506310,506100,506121,506070,506218,506227,506272,506147,506160,506265,506202,506222,506093,506257,506208,506344,506077,506395,506094,506219,506298,506339,506343,506365,506200,506348,506198,506385,506239,506236,506391,506087,506342,506149,506184,506393,506203,506280,506216,506403,506355,506332,506259,506401,506357,506324,506098,506315,506335,506088,506046,506185,506171,506080,506345,506347,506067,506233,506225,506312,506278,506300,506258,506182,506226,506262,506146,506113,506108,506297,506322,506143,506363,506073,506154,506313,506189,506197,506162,506249,506139,506237,506336,506084,506109,506106,506045,506392,506247,506316,506201,506353,506305,506050,506145,506362,506101,506128,506044,506317,506074,506134,506196,506194,506285,506177,506240,506282,506396,506281,506264,506276,506144,506069,506091,506081,506168,506291,506238,506072,506085,506235,506193,506268,506148,506356,506386,506229,506256,506187,506110,506304,506115,506214,506334,506289,506361,506366,506204,506190,506188,506307,506055,506389,506364,506279,506241,506057,506063,506320,506212,506263,506394,506306,506260,506309,506221,506155,506176,506398,506360,506210,506341,506209,506170,506097,506119,506163,506092,506267,506246,506047,506296,506058,506269,506378,506123,506271,506277,506207,506141,506390,506314,506299,506075,506183,506157,506228,506255,506358,506053,506060,506382,506217,506290,506230,506186,506213,506248,506354,506245,506104,506111,506054,506068,506156,506102,506191,506158,506159,506153,506107,506056,506131,506165,506370,506161,506242,506327,506253,506330,506243,506231,506096,506331,506062,506195,506369,506384,506071,506116,506164,506090,506397,506273,506338,506140,506136,506086,506083,506275,506283,506142,506383,506380,506129,506368,506130,506367,506292,506064,506138,506167,506223,506351,506079,506132,506293,506089,506095,506120,506388,506211,506274,506321,506150,506169,506049,506379,506252,506112,506199,506287,506266,506118,506103,506301,506105,506137,506352,506333,506180,506254,506375,506270,506319,506288,506244,506284,506059,506261,506372,506127,506359,506135,506215,506151,506251,506152,506126,506373,506346', 'photo_hashtag_type': 332, 'photo_desc_type': 3390, 'type_classification': 'caffe', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 3390 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3390, 'car_360_1027', 16384, 25088, 'car_360_1027', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2017, 10, 28, 12, 29, 27), datetime.datetime(2017, 10, 28, 12, 29, 27)) To loadFromThcl() : net_3390 begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 6677 max_wait_temp : 1 max_wait : 0 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3390, 'car_360_1027', 16384, 25088, 'car_360_1027', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2017, 10, 28, 12, 29, 27), datetime.datetime(2017, 10, 28, 12, 29, 27)) None mean_file_type : mean_file_path : prototxt_file_path : model : car_360_1027 Inside get_net Inside get_net before cache_data_model model_param file didn't exist Inside get_net before CDM.load_model_par_type model_name : car_360_1027 model_type : caffe list file need : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file exist in s3 : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file manque in s3 : [] local folder : /data/models_weight/car_360_1027 /data/models_weight/car_360_1027/caffemodel size_local : 542944640 size in s3 : 542944640 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:43 caffemodel already exist and didn't need to update /data/models_weight/car_360_1027/deploy_conv_normal.prototxt size_local : 4626 size in s3 : 4626 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:42 deploy_conv_normal.prototxt already exist and didn't need to update /data/models_weight/car_360_1027/deploy_fc.prototxt size_local : 1132 size in s3 : 1132 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:43 deploy_fc.prototxt already exist and didn't need to update /data/models_weight/car_360_1027/deploy.prototxt size_local : 5654 size in s3 : 5654 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:42 deploy.prototxt already exist and didn't need to update /data/models_weight/car_360_1027/mean.npy size_local : 1572944 size in s3 : 1572944 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:55 mean.npy already exist and didn't need to update /data/models_weight/car_360_1027/synset_words.txt size_local : 13687 size in s3 : 13687 create time local : 2021-08-09 05:28:34 create time in s3 : 2021-08-06 17:57:43 synset_words.txt already exist and didn't need to update Inside get_net after CDM.load_model_par_type After if not only_with_local_cache: /home/admin/workarea/install/darknet/:/home/admin/workarea/git/Velours/python:/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python:/home/admin/mtr/.credentials:/home/admin/workarea/install/caffe/python:/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools/:/home/admin/workarea/git/fotonowerpip/:/home/admin/workarea/install/segment-anything:/home/admin//workarea/git/pyfvs/ Here before set mode gpu Doing nothing but we could set mode gpu after set mode gpu prototxt_filename : /data/models_weight/car_360_1027/deploy.prototxt caffemodel_filename : /data/models_weight/car_360_1027/caffemodel now we set caffe to gpu mode before predict begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 6677 max_wait_temp : 1 max_wait : 0 dict_keys(['pool5', 'prob']) time used to do the prepocess of the images : 0.010799884796142578 time used to do the prediction : 0.06207156181335449 save descriptor for thcl : 355 time to traite the descriptors : 0.05977940559387207 Catched exception ! Connect or reconnect ! storage_type for insertDescriptorsMulti : 1 To insert : 916235064 time to insert the descriptors : 3.0024335384368896 Inside saveOutput : final : False verbose : False time used to find the portfolios of the photos SAVE THCL : begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 0 time used for this insertion : 8.106231689453125e-06 save missing photos in datou_result : time spend for datou_step_exec : 8.27844524383545 time spend to save output : 5.710318088531494 total time spend for step 1 : 13.988763332366943 step2:argmax Sat Feb 15 05:22:41 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step Argmax ! calculate argmax for thcl : 355 Inside saveOutput : final : True verbose : False photo_id : 916235064 output[photo_id] : [('916235064', 'c15_1027_gao__port_506055', 0.017717492, 332, '355'), 'temp/1739593346_3820514_916235064_6293d1bb790dc6902450e7c572b7d10b.jpg'] begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 1 time used for this insertion : 0.015595436096191406 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 1 time used for this insertion : 0.016805648803710938 len list_finale : 1, len picture : 1 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.015120744705200195 saving photo_ids in datou_result photo id not in port begin to insert list_values into mtr_datou_result : length of list_values in save_final : 0 time used for this insertion : 4.76837158203125e-06 save missing photos in datou_result : time spend for datou_step_exec : 0.0003237724304199219 time spend to save output : 0.04789090156555176 total time spend for step 2 : 0.04821467399597168 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 2 output : {'916235064': [('916235064', 'c15_1027_gao__port_506055', 0.017717492, 332, '355'), 'temp/1739593346_3820514_916235064_6293d1bb790dc6902450e7c572b7d10b.jpg']} ############################### TEST tfhub2 ################################ TEST TFHUB2 ######################## test with use_multi_inputs=0 ######################## Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 12835 tfhub_classification2 is not linked in the step_by_step architecture ! WARNING : step 12836 argmax is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! List Step Type Loaded in datou : tfhub_classification2, argmax list_input_json : [] origin BBBFFFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 3 ; length of list_pids : 3 ; length of list_args : 3 time to download the photos : 0.22220396995544434 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 2 step1:tfhub_classification2 Sat Feb 15 05:22:41 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step TFHub with tf2 ! we are using the classfication for only one thcl 3609 begin to check gpu status inside check gpu memory 2025-02-15 05:22:44.648578: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-02-15 05:22:44.649258: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-15 05:22:44.649369: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:22:44.649419: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:22:44.651286: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-15 05:22:44.651361: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-15 05:22:44.653332: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-15 05:22:44.654278: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-15 05:22:44.658166: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-15 05:22:44.659384: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-15 05:22:44.659813: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-02-15 05:22:44.695248: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-02-15 05:22:44.696991: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f37f4000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-02-15 05:22:44.697040: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-02-15 05:22:44.700644: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x34e93700 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-02-15 05:22:44.700675: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-02-15 05:22:44.701891: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-02-15 05:22:44.702004: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:22:44.702037: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-02-15 05:22:44.702126: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-02-15 05:22:44.702172: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-02-15 05:22:44.702226: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-02-15 05:22:44.702281: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-02-15 05:22:44.702336: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-02-15 05:22:44.704108: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-02-15 05:22:44.704187: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-02-15 05:22:44.704264: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-02-15 05:22:44.704282: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-02-15 05:22:44.704296: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-02-15 05:22:44.706163: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3096 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) l 3637 free memory gpu now : 6677 max_wait_temp : 1 max_wait : 5 1 Physical GPUs, 1 Logical GPUs tagging for thcl : 3609 To do loadFromThcl(), then load ParamDescType : thcl3609 thcls : [{'id': 3609, 'mtr_user_id': 31, 'name': 'tfhub_19_06_2023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'jrm,pcm,pcnc,pehd,tapis_vide', 'svm_portfolios_learning': '9336903,9336904,9336905,9336906,9336909', 'photo_hashtag_type': 4674, 'photo_desc_type': 5832, 'type_classification': 'tf_classification2', 'hashtag_id_list': '495916461,560181804,1284539308,628944319,2107748999'}] thcl {'id': 3609, 'mtr_user_id': 31, 'name': 'tfhub_19_06_2023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'jrm,pcm,pcnc,pehd,tapis_vide', 'svm_portfolios_learning': '9336903,9336904,9336905,9336906,9336909', 'photo_hashtag_type': 4674, 'photo_desc_type': 5832, 'type_classification': 'tf_classification2', 'hashtag_id_list': '495916461,560181804,1284539308,628944319,2107748999'} Update svm_hashtag_type_desc : 5832 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5832, 'tfhub_19_06_2023', 1280, 1280, 'tfhub_19_06_2023', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2023, 6, 19, 12, 55, 22), datetime.datetime(2023, 6, 19, 12, 55, 22)) model_name : tfhub_19_06_2023 model_param file didn't exist model_name : tfhub_19_06_2023 model_type : tf_classification2 list file need : ['Confusion_Matrix.png', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file exist in s3 : ['Confusion_Matrix.png', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file manque in s3 : [] /home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python/../../tools/../lib/rpn/proposal_layer.py:28: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. layer_params = yaml.load(self.param_str_) local folder : /data/models_weight/tfhub_19_06_2023 /data/models_weight/tfhub_19_06_2023/Confusion_Matrix.png size_local : 57753 size in s3 : 57753 create time local : 2023-06-22 17:09:38 create time in s3 : 2023-06-19 10:55:15 Confusion_Matrix.png already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Precision_Recall_jrm.jpg size_local : 79724 size in s3 : 79724 create time local : 2023-06-22 17:09:38 create time in s3 : 2023-06-19 10:55:20 Precision_Recall_jrm.jpg already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Precision_Recall_pcm.jpg size_local : 83556 size in s3 : 83556 create time local : 2023-06-22 17:09:38 create time in s3 : 2023-06-19 10:55:15 Precision_Recall_pcm.jpg already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Precision_Recall_pcnc.jpg size_local : 74107 size in s3 : 74107 create time local : 2023-06-22 17:09:38 create time in s3 : 2023-06-19 10:55:20 Precision_Recall_pcnc.jpg already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Precision_Recall_pehd.jpg size_local : 72705 size in s3 : 72705 create time local : 2023-06-22 17:09:39 create time in s3 : 2023-06-19 10:55:20 Precision_Recall_pehd.jpg already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Precision_Recall_tapis_vide.jpg size_local : 70874 size in s3 : 70874 create time local : 2023-06-22 17:09:39 create time in s3 : 2023-06-19 10:55:15 Precision_Recall_tapis_vide.jpg already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/Result_Summary.txt size_local : 642 size in s3 : 642 create time local : 2023-06-22 17:09:39 create time in s3 : 2023-06-19 10:55:22 Result_Summary.txt already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/checkpoint size_local : 99 size in s3 : 99 create time local : 2023-06-22 17:09:39 create time in s3 : 2023-06-19 10:55:22 checkpoint already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/model_checkpoint.ckpt.data-00000-of-00002 size_local : 216488 size in s3 : 216488 create time local : 2023-06-22 17:09:39 create time in s3 : 2023-06-19 10:55:22 model_checkpoint.ckpt.data-00000-of-00002 already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/model_checkpoint.ckpt.data-00001-of-00002 size_local : 32279708 size in s3 : 32279708 create time local : 2023-06-22 17:09:40 create time in s3 : 2023-06-19 10:55:21 model_checkpoint.ckpt.data-00001-of-00002 already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/model_checkpoint.ckpt.index size_local : 43546 size in s3 : 43546 create time local : 2023-06-22 17:09:40 create time in s3 : 2023-06-19 10:55:22 model_checkpoint.ckpt.index already exist and didn't need to update /data/models_weight/tfhub_19_06_2023/model_weights.h5 size_local : 16499144 size in s3 : 16499144 create time local : 2023-06-22 17:09:40 create time in s3 : 2023-06-19 10:55:15 model_weights.h5 already exist and didn't need to update desc size : 1280 Model: "sequential" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= module (KerasLayer) (None, 1280) 4049564 _________________________________________________________________ tfhub_19_06_2023dense (Dense (None, 5) 6405 ================================================================= Total params: 4,055,969 Trainable params: 6,405 Non-trainable params: 4,049,564 _________________________________________________________________ Loading Weights... time used to create the model : 12.009645223617554 time used to load_weights : 0.15839505195617676 0it [00:00, ?it/s] 3it [00:00, 671.55it/s]2025-02-15 05:22:59.821926: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 temp/1739593361_3820514_1171252764_29d5179a892cc50aadc9d67245534b59.jpg temp/1739593361_3820514_1171252487_5ebdd6b0a6bb39942a3808ed114806de.jpg temp/1739593361_3820514_1171252784_5a3c5d3bb155a7a116f67ded51bffb59.jpg Found 3 images belonging to 1 classes. begin to do the prediction : time used to do the prediction : 2.8609166145324707 (3,) (3, 5) (3, 1280) shape of features : (3, 1280) shape of new features : (1, 3, 1280) save descriptor for thcl : 3609 time to traite the descriptors : 0.030524492263793945 storage_type for insertDescriptorsMulti : 3 To insert : 1171252764 To insert : 1171252487 To insert : 1171252784 time to insert the descriptors : 0.7724783420562744 Inside saveOutput : final : False verbose : False saveOutput not yet implemented for datou_step.type : tfhub_classification2 we use saveGeneral [1171252764, 1171252487, 1171252784] Looping around the photos to save general results len do output : 3 /1171252764Didn't retrieve data . /1171252487Didn't retrieve data . /1171252784Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4567', None, None, None, None, None, None, None, None) ('4567', None, '1171252764', None, None, None, None, None, None) ('4567', None, None, None, None, None, None, None, None) ('4567', None, '1171252487', None, None, None, None, None, None) ('4567', None, None, None, None, None, None, None, None) ('4567', None, '1171252784', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 0.019256591796875 save_final save missing photos in datou_result : time spend for datou_step_exec : 21.95151162147522 time spend to save output : 0.019639015197753906 total time spend for step 1 : 21.971150636672974 step2:argmax Sat Feb 15 05:23:03 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step Argmax ! calculate argmax for thcl : 3609 Inside saveOutput : final : True verbose : False photo_id : 1171252764 output[photo_id] : [(1171252764, 'jrm', 0.9853535, 4674, '3609'), 'temp/1739593361_3820514_1171252764_29d5179a892cc50aadc9d67245534b59.jpg'] photo_id : 1171252487 output[photo_id] : [(1171252487, 'jrm', 0.92636186, 4674, '3609'), 'temp/1739593361_3820514_1171252487_5ebdd6b0a6bb39942a3808ed114806de.jpg'] photo_id : 1171252784 output[photo_id] : [(1171252784, 'jrm', 0.9677662, 4674, '3609'), 'temp/1739593361_3820514_1171252784_5a3c5d3bb155a7a116f67ded51bffb59.jpg'] begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 3 time used for this insertion : 0.014862060546875 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 3 time used for this insertion : 0.018943309783935547 len list_finale : 3, len picture : 3 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 time used for this insertion : 0.016672134399414062 saving photo_ids in datou_result photo id not in port photo id not in port photo id not in port begin to insert list_values into mtr_datou_result : length of list_values in save_final : 0 time used for this insertion : 4.291534423828125e-06 save missing photos in datou_result : time spend for datou_step_exec : 0.00021076202392578125 time spend to save output : 0.054807186126708984 total time spend for step 2 : 0.055017948150634766 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 2 output : {'1171252764': [(1171252764, 'jrm', 0.9853535, 4674, '3609'), 'temp/1739593361_3820514_1171252764_29d5179a892cc50aadc9d67245534b59.jpg'], '1171252487': [(1171252487, 'jrm', 0.92636186, 4674, '3609'), 'temp/1739593361_3820514_1171252487_5ebdd6b0a6bb39942a3808ed114806de.jpg'], '1171252784': [(1171252784, 'jrm', 0.9677662, 4674, '3609'), 'temp/1739593361_3820514_1171252784_5a3c5d3bb155a7a116f67ded51bffb59.jpg']} --------------------- test with use_multi_inputs=0 is succeded ------------------- ######################## test with use_multi_inputs=1 ######################## Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 12927 tfhub_classification2 is not linked in the step_by_step architecture ! WARNING : step 12928 argmax is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! List Step Type Loaded in datou : tfhub_classification2, argmax list_input_json : [] origin BBBFFFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 3 ; length of list_pids : 3 ; length of list_args : 3 time to download the photos : 0.2015702724456787 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 2 step1:tfhub_classification2 Sat Feb 15 05:23:03 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step TFHub with tf2 ! we are using the classfication for only one thcl 3655 begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 3125 max_wait_temp : 1 max_wait : 5 1 Physical GPUs, 1 Logical GPUs tagging for thcl : 3655 To do loadFromThcl(), then load ParamDescType : thcl3655 thcls : [{'id': 3655, 'mtr_user_id': 31, 'name': 'tfhub_18_7_2023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'pcm,pcnc,jrm,pehd,tapis_vide', 'svm_portfolios_learning': '9336904,9336905,9336903,9336906,9336909', 'photo_hashtag_type': 4723, 'photo_desc_type': 5862, 'type_classification': 'tf_classification2', 'hashtag_id_list': '560181804,1284539308,495916461,628944319,2107748999'}] thcl {'id': 3655, 'mtr_user_id': 31, 'name': 'tfhub_18_7_2023', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'pcm,pcnc,jrm,pehd,tapis_vide', 'svm_portfolios_learning': '9336904,9336905,9336903,9336906,9336909', 'photo_hashtag_type': 4723, 'photo_desc_type': 5862, 'type_classification': 'tf_classification2', 'hashtag_id_list': '560181804,1284539308,495916461,628944319,2107748999'} Update svm_hashtag_type_desc : 5862 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5862, 'tfhub_18_7_2023', 1280, 1280, 'tfhub_18_7_2023', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2023, 7, 18, 22, 46, 29), datetime.datetime(2023, 7, 18, 22, 46, 29)) model_name : tfhub_18_7_2023 model_param file didn't exist model_name : tfhub_18_7_2023 model_type : tf_classification2 list file need : ['Confusion_Matrix.png', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file exist in s3 : ['Confusion_Matrix.png', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file manque in s3 : [] local folder : /data/models_weight/tfhub_18_7_2023 /data/models_weight/tfhub_18_7_2023/Confusion_Matrix.png size_local : 54360 size in s3 : 54360 create time local : 2023-08-11 11:22:56 create time in s3 : 2023-07-18 20:46:28 Confusion_Matrix.png already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Precision_Recall_jrm.jpg size_local : 72583 size in s3 : 72583 create time local : 2023-08-11 11:22:56 create time in s3 : 2023-07-18 20:46:23 Precision_Recall_jrm.jpg already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Precision_Recall_pcm.jpg size_local : 81681 size in s3 : 81681 create time local : 2023-08-11 11:22:56 create time in s3 : 2023-07-18 20:46:17 Precision_Recall_pcm.jpg already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Precision_Recall_pcnc.jpg size_local : 79510 size in s3 : 79510 create time local : 2023-08-11 11:22:56 create time in s3 : 2023-07-18 20:46:23 Precision_Recall_pcnc.jpg already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Precision_Recall_pehd.jpg size_local : 59936 size in s3 : 59936 create time local : 2023-08-11 11:22:57 create time in s3 : 2023-07-18 20:46:23 Precision_Recall_pehd.jpg already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Precision_Recall_tapis_vide.jpg size_local : 78974 size in s3 : 78974 create time local : 2023-08-11 11:22:57 create time in s3 : 2023-07-18 20:46:17 Precision_Recall_tapis_vide.jpg already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/Result_Summary.txt size_local : 642 size in s3 : 642 create time local : 2023-08-11 11:22:57 create time in s3 : 2023-07-18 20:46:23 Result_Summary.txt already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/checkpoint size_local : 99 size in s3 : 99 create time local : 2023-08-11 11:22:57 create time in s3 : 2023-07-18 20:46:23 checkpoint already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/model_checkpoint.ckpt.data-00000-of-00002 size_local : 216529 size in s3 : 216529 create time local : 2023-08-11 11:22:57 create time in s3 : 2023-07-18 20:46:17 model_checkpoint.ckpt.data-00000-of-00002 already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/model_checkpoint.ckpt.data-00001-of-00002 size_local : 32279748 size in s3 : 32279748 create time local : 2023-08-11 11:22:58 create time in s3 : 2023-07-18 20:46:19 model_checkpoint.ckpt.data-00001-of-00002 already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/model_checkpoint.ckpt.index size_local : 43546 size in s3 : 43546 create time local : 2023-08-11 11:22:58 create time in s3 : 2023-07-18 20:46:19 model_checkpoint.ckpt.index already exist and didn't need to update /data/models_weight/tfhub_18_7_2023/model_weights.h5 size_local : 16500868 size in s3 : 16500868 create time local : 2023-08-11 11:22:58 create time in s3 : 2023-07-18 20:46:18 model_weights.h5 already exist and didn't need to update desc size : 1280 Model: "model" __________________________________________________________________________________________________ Layer (type) Output Shape Param # Connected to ================================================================================================== input_1 (InputLayer) [(None, 224, 224, 3) 0 __________________________________________________________________________________________________ input_2 (InputLayer) [(None, 1)] 0 __________________________________________________________________________________________________ module (KerasLayer) (None, 1280) 4049564 input_1[0][0] __________________________________________________________________________________________________ concatenate (Concatenate) (None, 1281) 0 input_2[0][0] module[0][0] __________________________________________________________________________________________________ tfhub_18_7_2023dense (Dense) (None, 5) 6410 concatenate[0][0] ================================================================================================== Total params: 4,055,974 Trainable params: 0 Non-trainable params: 4,055,974 __________________________________________________________________________________________________ Loading Weights... time used to create the model : 9.504873752593994 time used to load_weights : 0.15025973320007324 found 3 data found 0 labels begin to do the prediction : time used to do the prediction : 1.343916416168213 (3,) (3, 5) (3, 1280) shape of features : (3, 1280) shape of new features : (1, 3, 1280) save descriptor for thcl : 3655 time to traite the descriptors : 0.03941512107849121 storage_type for insertDescriptorsMulti : 3 To insert : 1171291875 To insert : 1171275372 To insert : 1171275314 time to insert the descriptors : 3.16733455657959 Inside saveOutput : final : False verbose : False saveOutput not yet implemented for datou_step.type : tfhub_classification2 we use saveGeneral [1171291875, 1171275372, 1171275314] Looping around the photos to save general results len do output : 3 /1171291875Didn't retrieve data . /1171275372Didn't retrieve data . /1171275314Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4621', None, None, None, None, None, None, None, None) ('4621', None, '1171291875', None, None, None, None, None, None) ('4621', None, None, None, None, None, None, None, None) ('4621', None, '1171275372', None, None, None, None, None, None) ('4621', None, None, None, None, None, None, None, None) ('4621', None, '1171275314', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 0.014005899429321289 save_final save missing photos in datou_result : time spend for datou_step_exec : 17.226466417312622 time spend to save output : 0.014401912689208984 total time spend for step 1 : 17.24086833000183 step2:argmax Sat Feb 15 05:23:20 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step Argmax ! calculate argmax for thcl : 3655 Inside saveOutput : final : True verbose : False photo_id : 1171291875 output[photo_id] : [(1171291875, 'tapis_vide', 0.9705664, 4723, '3655'), 'temp/1739593383_3820514_1171291875_b62cd9e0d976b143f86fe82d072798c0.jpg'] photo_id : 1171275372 output[photo_id] : [(1171275372, 'tapis_vide', 0.9673882, 4723, '3655'), 'temp/1739593383_3820514_1171275372_76d81364ff7df843bff095f45c07ba35.jpg'] photo_id : 1171275314 output[photo_id] : [(1171275314, 'tapis_vide', 0.9651632, 4723, '3655'), 'temp/1739593383_3820514_1171275314_6e0a72c8fa00d5e4b018bd689b547133.jpg'] begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 3 time used for this insertion : 1.0407814979553223 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 3 time used for this insertion : 0.336841344833374 len list_finale : 3, len picture : 3 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 time used for this insertion : 0.013785839080810547 saving photo_ids in datou_result photo id not in port photo id not in port photo id not in port begin to insert list_values into mtr_datou_result : length of list_values in save_final : 0 time used for this insertion : 5.7220458984375e-06 save missing photos in datou_result : time spend for datou_step_exec : 0.0002148151397705078 time spend to save output : 1.396141529083252 total time spend for step 2 : 1.3963563442230225 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 2 output : {'1171291875': [(1171291875, 'tapis_vide', 0.9705664, 4723, '3655'), 'temp/1739593383_3820514_1171291875_b62cd9e0d976b143f86fe82d072798c0.jpg'], '1171275372': [(1171275372, 'tapis_vide', 0.9673882, 4723, '3655'), 'temp/1739593383_3820514_1171275372_76d81364ff7df843bff095f45c07ba35.jpg'], '1171275314': [(1171275314, 'tapis_vide', 0.9651632, 4723, '3655'), 'temp/1739593383_3820514_1171275314_6e0a72c8fa00d5e4b018bd689b547133.jpg']} --------------------- test with use_multi_inputs=1 is succeded ------------------- ############################### TEST ordonner ################################ To do loadFromThcl(), then load ParamDescType : thcl358 thcls : [{'id': 358, 'mtr_user_id': 31, 'name': 'car_orientation_0111', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'FirstUploadExperveo_vignette__port_505674,CAR_EXTERIEUR_Roue__port_503398,FirstUploadExperveo_carrosseriegrosplan_VIndanslamoquette__port_506486,FirstUploadExperveo_carrosseriegrosplan_siegegrosplan__port_506485,CAR_EXTERIEUR_Cote_droit_axe_avant__port_504465,CAR_EXTERIEUR_Cote_gauche_axe_arriere__port_504198,CAR_EXTERIEUR_Face_avant_axe_droit__port_504451,CAR_EXTERIEUR_angle_avant_gauche_axe_avant__port_504235,FirstUploadExperveo_vin__port_505675,CAR_EXTERIEUR_cote_droite__port_504108,CAR_INTERIEUR_avant_volant_class_6_levierdevitesse__port_506565,FirstUploadExperveo_carrosseriegrosplan_carrosserie__port_506483,CAR_EXTERIEUR_Angle_arriere_gauche_axe_arriere__port_504201,cartegrise_orientation__port_505064,CAR_EXTERIEUR_Angle_arriere_droit_axe_arriere__port_504217,CAR_INTERIEUR_avant_vue-arriere_class_1__port_506531,CAR_EXTERIEUR_Face_arriere_axe_droit__port_504218,CAR_EXTERIEUR_Cote_droit_axe_arriere__port_504214,CAR_EXTERIEUR_Angle_avant_droit__port_504087,FirstUploadExperveo_carrosseriegrosplan_morceauderoue__port_506484,CAR_INTERIEUR_avant_volant_class_6_class_2__port_506563,CAR_EXTERIEUR_Angle_arriere_droit__port_504160,CAR_EXTERIEUR_arriere__port_504184,CAR_INTERIEUR_avant_volant_class_6_boutonrond__port_506562,INTERIEUR_Compteur_kilometrique__port_503644,CAR_INTERIEUR_avant_vue_gauche_habitacle_class_1__port_506494,CAR_EXTERIEUR_Angle_arriere_gauche__port_504170,CAR_EXTERIEUR_Angle_avant_droit_axe_arriere__port_504226,CAR_EXTERIEUR_Face_arriere_axe_gauche__port_504202,CAR_EXTERIEUR_moteur__port_503704,FirstUploadExperveo_carrosseriegrosplan_class_6__port_506487,CAR_INTERIEUR_siege_arriere_class_1__port_506551,CAR_EXTERIEUR_avant__port_504146,CAR_EXTERIEUR_Angle_arriere_droit_axe_droit__port_504215,CAR_EXTERIEUR_Angle_avant_droit_axe_droit__port_504225,CAR_INTERIEUR_avant_volant_class_6_ecrangrosplan__port_506564,FirstUploadExperveo_carrosseriegrosplan_moteurgrosplanetdegat__port_506482,CAR_INTERIEUR_coffre__port_503412,FirstUploadExperveo_rouetranche__port_505677,UploadPhotoImmatBest_class_1__port_505051,CAR_INTERIEUR_avant_vue-arriere_class_2__port_506532,CAR_EXTERIEUR_angle_avant_gauche__port_504098,CAR_EXTERIEUR_face_avant_axe_gauche__port_504236,CAR_INTERIEUR_avant_vue_droite_habitacle_class_1__port_506540,CAR_EXTERIEUR_cote_gauche_axe_avant__port_504233,CAR_EXTERIEUR_roue_de_secour__port_503763,CAR_EXTERIEUR_Angle_arriere_gauche_axe_gauche__port_504199,CAR_EXTERIEUR_cote_gauche__port_504017,CAR_INTERIEUR_avant_volant_class_1__port_506503,CAR_INTERIEUR_avant_volant_class_2__port_506504,CAR_EXTERIEUR_angle_avant_gauche_axe_gauche__port_504234', 'svm_portfolios_learning': '505674,503398,506486,506485,504465,504198,504451,504235,505675,504108,506565,506483,504201,505064,504217,506531,504218,504214,504087,506484,506563,504160,504184,506562,503644,506494,504170,504226,504202,503704,506487,506551,504146,504215,504225,506564,506482,503412,505677,505051,506532,504098,504236,506540,504233,503763,504199,504017,506503,506504,504234', 'photo_hashtag_type': 337, 'photo_desc_type': 3392, 'type_classification': 'caffe', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 358, 'mtr_user_id': 31, 'name': 'car_orientation_0111', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'FirstUploadExperveo_vignette__port_505674,CAR_EXTERIEUR_Roue__port_503398,FirstUploadExperveo_carrosseriegrosplan_VIndanslamoquette__port_506486,FirstUploadExperveo_carrosseriegrosplan_siegegrosplan__port_506485,CAR_EXTERIEUR_Cote_droit_axe_avant__port_504465,CAR_EXTERIEUR_Cote_gauche_axe_arriere__port_504198,CAR_EXTERIEUR_Face_avant_axe_droit__port_504451,CAR_EXTERIEUR_angle_avant_gauche_axe_avant__port_504235,FirstUploadExperveo_vin__port_505675,CAR_EXTERIEUR_cote_droite__port_504108,CAR_INTERIEUR_avant_volant_class_6_levierdevitesse__port_506565,FirstUploadExperveo_carrosseriegrosplan_carrosserie__port_506483,CAR_EXTERIEUR_Angle_arriere_gauche_axe_arriere__port_504201,cartegrise_orientation__port_505064,CAR_EXTERIEUR_Angle_arriere_droit_axe_arriere__port_504217,CAR_INTERIEUR_avant_vue-arriere_class_1__port_506531,CAR_EXTERIEUR_Face_arriere_axe_droit__port_504218,CAR_EXTERIEUR_Cote_droit_axe_arriere__port_504214,CAR_EXTERIEUR_Angle_avant_droit__port_504087,FirstUploadExperveo_carrosseriegrosplan_morceauderoue__port_506484,CAR_INTERIEUR_avant_volant_class_6_class_2__port_506563,CAR_EXTERIEUR_Angle_arriere_droit__port_504160,CAR_EXTERIEUR_arriere__port_504184,CAR_INTERIEUR_avant_volant_class_6_boutonrond__port_506562,INTERIEUR_Compteur_kilometrique__port_503644,CAR_INTERIEUR_avant_vue_gauche_habitacle_class_1__port_506494,CAR_EXTERIEUR_Angle_arriere_gauche__port_504170,CAR_EXTERIEUR_Angle_avant_droit_axe_arriere__port_504226,CAR_EXTERIEUR_Face_arriere_axe_gauche__port_504202,CAR_EXTERIEUR_moteur__port_503704,FirstUploadExperveo_carrosseriegrosplan_class_6__port_506487,CAR_INTERIEUR_siege_arriere_class_1__port_506551,CAR_EXTERIEUR_avant__port_504146,CAR_EXTERIEUR_Angle_arriere_droit_axe_droit__port_504215,CAR_EXTERIEUR_Angle_avant_droit_axe_droit__port_504225,CAR_INTERIEUR_avant_volant_class_6_ecrangrosplan__port_506564,FirstUploadExperveo_carrosseriegrosplan_moteurgrosplanetdegat__port_506482,CAR_INTERIEUR_coffre__port_503412,FirstUploadExperveo_rouetranche__port_505677,UploadPhotoImmatBest_class_1__port_505051,CAR_INTERIEUR_avant_vue-arriere_class_2__port_506532,CAR_EXTERIEUR_angle_avant_gauche__port_504098,CAR_EXTERIEUR_face_avant_axe_gauche__port_504236,CAR_INTERIEUR_avant_vue_droite_habitacle_class_1__port_506540,CAR_EXTERIEUR_cote_gauche_axe_avant__port_504233,CAR_EXTERIEUR_roue_de_secour__port_503763,CAR_EXTERIEUR_Angle_arriere_gauche_axe_gauche__port_504199,CAR_EXTERIEUR_cote_gauche__port_504017,CAR_INTERIEUR_avant_volant_class_1__port_506503,CAR_INTERIEUR_avant_volant_class_2__port_506504,CAR_EXTERIEUR_angle_avant_gauche_axe_gauche__port_504234', 'svm_portfolios_learning': '505674,503398,506486,506485,504465,504198,504451,504235,505675,504108,506565,506483,504201,505064,504217,506531,504218,504214,504087,506484,506563,504160,504184,506562,503644,506494,504170,504226,504202,503704,506487,506551,504146,504215,504225,506564,506482,503412,505677,505051,506532,504098,504236,506540,504233,503763,504199,504017,506503,506504,504234', 'photo_hashtag_type': 337, 'photo_desc_type': 3392, 'type_classification': 'caffe', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 3392 ['FirstUploadExperveo_vignette__port_505674', 'CAR_EXTERIEUR_Roue__port_503398', 'FirstUploadExperveo_carrosseriegrosplan_VIndanslamoquette__port_506486', 'FirstUploadExperveo_carrosseriegrosplan_siegegrosplan__port_506485', 'CAR_EXTERIEUR_Cote_droit_axe_avant__port_504465', 'CAR_EXTERIEUR_Cote_gauche_axe_arriere__port_504198', 'CAR_EXTERIEUR_Face_avant_axe_droit__port_504451', 'CAR_EXTERIEUR_angle_avant_gauche_axe_avant__port_504235', 'FirstUploadExperveo_vin__port_505675', 'CAR_EXTERIEUR_cote_droite__port_504108', 'CAR_INTERIEUR_avant_volant_class_6_levierdevitesse__port_506565', 'FirstUploadExperveo_carrosseriegrosplan_carrosserie__port_506483', 'CAR_EXTERIEUR_Angle_arriere_gauche_axe_arriere__port_504201', 'cartegrise_orientation__port_505064', 'CAR_EXTERIEUR_Angle_arriere_droit_axe_arriere__port_504217', 'CAR_INTERIEUR_avant_vue-arriere_class_1__port_506531', 'CAR_EXTERIEUR_Face_arriere_axe_droit__port_504218', 'CAR_EXTERIEUR_Cote_droit_axe_arriere__port_504214', 'CAR_EXTERIEUR_Angle_avant_droit__port_504087', 'FirstUploadExperveo_carrosseriegrosplan_morceauderoue__port_506484', 'CAR_INTERIEUR_avant_volant_class_6_class_2__port_506563', 'CAR_EXTERIEUR_Angle_arriere_droit__port_504160', 'CAR_EXTERIEUR_arriere__port_504184', 'CAR_INTERIEUR_avant_volant_class_6_boutonrond__port_506562', 'INTERIEUR_Compteur_kilometrique__port_503644', 'CAR_INTERIEUR_avant_vue_gauche_habitacle_class_1__port_506494', 'CAR_EXTERIEUR_Angle_arriere_gauche__port_504170', 'CAR_EXTERIEUR_Angle_avant_droit_axe_arriere__port_504226', 'CAR_EXTERIEUR_Face_arriere_axe_gauche__port_504202', 'CAR_EXTERIEUR_moteur__port_503704', 'FirstUploadExperveo_carrosseriegrosplan_class_6__port_506487', 'CAR_INTERIEUR_siege_arriere_class_1__port_506551', 'CAR_EXTERIEUR_avant__port_504146', 'CAR_EXTERIEUR_Angle_arriere_droit_axe_droit__port_504215', 'CAR_EXTERIEUR_Angle_avant_droit_axe_droit__port_504225', 'CAR_INTERIEUR_avant_volant_class_6_ecrangrosplan__port_506564', 'FirstUploadExperveo_carrosseriegrosplan_moteurgrosplanetdegat__port_506482', 'CAR_INTERIEUR_coffre__port_503412', 'FirstUploadExperveo_rouetranche__port_505677', 'UploadPhotoImmatBest_class_1__port_505051', 'CAR_INTERIEUR_avant_vue-arriere_class_2__port_506532', 'CAR_EXTERIEUR_angle_avant_gauche__port_504098', 'CAR_EXTERIEUR_face_avant_axe_gauche__port_504236', 'CAR_INTERIEUR_avant_vue_droite_habitacle_class_1__port_506540', 'CAR_EXTERIEUR_cote_gauche_axe_avant__port_504233', 'CAR_EXTERIEUR_roue_de_secour__port_503763', 'CAR_EXTERIEUR_Angle_arriere_gauche_axe_gauche__port_504199', 'CAR_EXTERIEUR_cote_gauche__port_504017', 'CAR_INTERIEUR_avant_volant_class_1__port_506503', 'CAR_INTERIEUR_avant_volant_class_2__port_506504', 'CAR_EXTERIEUR_angle_avant_gauche_axe_gauche__port_504234'] 51 51 thcl : 358 photo_hashtag_type : 337 ############################### TEST rotate ################################ test rotate only Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : rotate list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.18262982368469238 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:rotate Sat Feb 15 05:23:42 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step_rotate ! We are in a linear step without datou_depend ! rotate photos of 90,180,270 degres batch 1 Loaded 0 chid ids of type : 0 map_chi of length : 0 Needs to change image size ! Needs to change image size ! Needs to change image size ! About to upload 3 photos upload in portfolio : 551782 init cache_photo without model_param we have 3 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593423_3820514 we have uploaded 3 photos in the portfolio 551782 time of upload the photos Elapsed time : 1.2366812229156494 Len new_chis : 3 Len list_new_chi_with_photo_id : 0 of type : 0 time spend for datou_step_exec : 1.467867136001587 time spend to save output : 2.9325485229492188e-05 total time spend for step 1 : 1.4678964614868164 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : rotate we use saveGeneral [917849322] Looping around the photos to save general results len do output : 3 /1337814475Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814476Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814477Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('230', None, None, None, None, None, None, None, None) ('230', None, '917849322', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 10 time used for this insertion : 0.01681995391845703 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1337814475: ['917849322', 'temp/1739593422_3820514_917849322_2bd260e91e91df8378dde8bb8b8c454890.jpg', []], 1337814476: ['917849322', 'temp/1739593422_3820514_917849322_2bd260e91e91df8378dde8bb8b8c4548180.jpg', []], 1337814477: ['917849322', 'temp/1739593422_3820514_917849322_2bd260e91e91df8378dde8bb8b8c4548270.jpg', []]} test rotate only is a success ! test rotate conditionnel Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! List Step Type Loaded in datou : thcl, argmax, rotate list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.12097001075744629 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 3 step1:thcl Sat Feb 15 05:23:44 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step Thcl ! we are using the classfication for only one thcl 500 time to import caffe and check if the image exist : 0.00023937225341796875 time to convert the images to numpy array : 0.6585285663604736 total time to convert the images to numpy array : 0.6590559482574463 list photo_ids error: [] list photo_ids correct : [917849322] number of photos to traite : 1 try to delete the photos incorrect in DB tagging for thcl : 500 To do loadFromThcl(), then load ParamDescType : thcl500 thcls : [{'id': 500, 'mtr_user_id': 31, 'name': 'orientation_carte_grise_all_2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'carteGrisesVerticales__port_549774,cartegrise_90deg__port_550987,cartesGrisesEnvers__port_549765,portfolio_270deg__port_550988', 'svm_portfolios_learning': '549774,550987,549765,550988', 'photo_hashtag_type': 507, 'photo_desc_type': 3517, 'type_classification': 'caffe', 'hashtag_id_list': '0,0,0,0'}] thcl {'id': 500, 'mtr_user_id': 31, 'name': 'orientation_carte_grise_all_2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'carteGrisesVerticales__port_549774,cartegrise_90deg__port_550987,cartesGrisesEnvers__port_549765,portfolio_270deg__port_550988', 'svm_portfolios_learning': '549774,550987,549765,550988', 'photo_hashtag_type': 507, 'photo_desc_type': 3517, 'type_classification': 'caffe', 'hashtag_id_list': '0,0,0,0'} Update svm_hashtag_type_desc : 3517 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3517, 'orientation_carte_grise_all_2', 16384, 25088, 'orientation_carte_grise_all_2', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 4, 18, 20, 4, 34), datetime.datetime(2018, 4, 18, 20, 4, 34)) To loadFromThcl() : net_3517 begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 3125 max_wait_temp : 1 max_wait : 0 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3517, 'orientation_carte_grise_all_2', 16384, 25088, 'orientation_carte_grise_all_2', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 4, 18, 20, 4, 34), datetime.datetime(2018, 4, 18, 20, 4, 34)) None mean_file_type : mean_file_path : prototxt_file_path : model : orientation_carte_grise_all_2 Inside get_net Inside get_net before cache_data_model model_param file didn't exist Inside get_net before CDM.load_model_par_type model_name : orientation_carte_grise_all_2 model_type : caffe list file need : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file exist in s3 : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file manque in s3 : [] local folder : /data/models_weight/orientation_carte_grise_all_2 /data/models_weight/orientation_carte_grise_all_2/caffemodel size_local : 537110520 size in s3 : 537110520 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:17 caffemodel already exist and didn't need to update /data/models_weight/orientation_carte_grise_all_2/deploy_conv_normal.prototxt size_local : 4626 size in s3 : 4626 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:16 deploy_conv_normal.prototxt already exist and didn't need to update /data/models_weight/orientation_carte_grise_all_2/deploy_fc.prototxt size_local : 1130 size in s3 : 1130 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:16 deploy_fc.prototxt already exist and didn't need to update /data/models_weight/orientation_carte_grise_all_2/deploy.prototxt size_local : 5653 size in s3 : 5653 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:16 deploy.prototxt already exist and didn't need to update /data/models_weight/orientation_carte_grise_all_2/mean.npy size_local : 1572992 size in s3 : 1572992 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:31 mean.npy already exist and didn't need to update /data/models_weight/orientation_carte_grise_all_2/synset_words.txt size_local : 159 size in s3 : 159 create time local : 2021-08-09 05:29:00 create time in s3 : 2021-08-06 20:07:16 synset_words.txt already exist and didn't need to update Inside get_net after CDM.load_model_par_type After if not only_with_local_cache: /home/admin/workarea/install/darknet/:/home/admin/workarea/git/Velours/python:/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python:/home/admin/mtr/.credentials:/home/admin/workarea/install/caffe/python:/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools/:/home/admin/workarea/git/fotonowerpip/:/home/admin/workarea/install/segment-anything:/home/admin//workarea/git/pyfvs/ Here before set mode gpu Doing nothing but we could set mode gpu after set mode gpu prototxt_filename : /data/models_weight/orientation_carte_grise_all_2/deploy.prototxt caffemodel_filename : /data/models_weight/orientation_carte_grise_all_2/caffemodel now we set caffe to gpu mode before predict begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 3125 max_wait_temp : 1 max_wait : 0 dict_keys(['pool5', 'prob']) time used to do the prepocess of the images : 1.4303069114685059 time used to do the prediction : 0.20668506622314453 save descriptor for thcl : 500 time to traite the descriptors : 0.07059383392333984 storage_type for insertDescriptorsMulti : 1 To insert : 917849322 time to insert the descriptors : 0.6674070358276367 time spend for datou_step_exec : 7.990612983703613 time spend to save output : 4.9591064453125e-05 total time spend for step 1 : 7.990662574768066 step2:argmax Sat Feb 15 05:23:52 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou_step Argmax ! calculate argmax for thcl : 500 time spend for datou_step_exec : 0.0001742839813232422 time spend to save output : 4.863739013671875e-05 total time spend for step 2 : 0.00022292137145996094 step3:rotate Sat Feb 15 05:23:52 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 complete output_args for input 1 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou_step_rotate ! We are in a datou with depends ! angle_condi : {'carteGrisesVerticales__port_549774': 0, 'cartegrise_90deg__port_550987': 270, 'portfolio_270deg__port_550988': 90, 'cartesGrisesEnvers__port_549765': 180} rotate photos for hashtag carteGrisesVerticales__port_549774 of 0 degres 1 photos founded : [917849322] batch 1 Loaded 0 chid ids of type : 0 map_chi of length : 0 Needs to change image size ! About to upload 1 photos upload in portfolio : 551782 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593432_3820514 we have uploaded 1 photos in the portfolio 551782 time of upload the photos Elapsed time : 0.6107828617095947 Len new_chis : 1 Len list_new_chi_with_photo_id : 0 of type : 0 rotate photos for hashtag cartegrise_90deg__port_550987 of 270 degres 0 photos founded : [] rotate photos for hashtag portfolio_270deg__port_550988 of 90 degres 0 photos founded : [] rotate photos for hashtag cartesGrisesEnvers__port_549765 of 180 degres 0 photos founded : [] time spend for datou_step_exec : 0.7049660682678223 time spend to save output : 2.8371810913085938e-05 total time spend for step 3 : 0.7049944400787354 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : rotate we use saveGeneral [917849322] Looping around the photos to save general results len do output : 1 /1337814484Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('233', None, None, None, None, None, None, None, None) ('233', None, '917849322', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 4 time used for this insertion : 0.013314962387084961 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 3 output : {1337814484: ['917849322', 'temp/1739593424_3820514_917849322_2bd260e91e91df8378dde8bb8b8c45480.jpg', []]} ############################### TEST data_augmentation_ellipse_varroa_tile_rotate ################################ # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 316 crop is not linked in the step_by_step architecture ! Step 318 rotate have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 318 rotate have less outputs used (0) than in the step definition (3) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! Unexpected type seems boolean for variable list_input_json ERROR or WARNING : can't parse json string Expecting value: line 1 column 1 (char 0) Tried to parse : DATA AUGMENTATION ELLIPSE VARROA TILE ROTATE Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 316 crop is not linked in the step_by_step architecture ! Step 318 rotate have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 318 rotate have less outputs used (0) than in the step definition (3) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! List Step Type Loaded in datou : crop, tile, rotate list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.12616491317749023 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 3 step1:crop Sat Feb 15 05:23:53 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step Crop ! param_json : {'hashtag_id_ellipse': 2087736828, 'photo_hashtag_type_from_ellipse': 520, 'token': '78d09a0790ec6ecbf119343125a81fdc', 'portfolio_name': 'crop_detect_varroa', 'photo_hashtag_type': 407, 'feed_id_new_photos_not_used': 549103, 'host': 'www.fotonower.com', 'margin': 8, 'upload_type': 'python'} margin_type : margin margin_value : [8, 8, 8, 8] Loading chi in step crop with photo_hashtag_type : 407 Loading chi in step crop for list_pids : 1 ! batch 1 Loaded 4 chid ids of type : 407 +WARNING : Unexpected points, we should remove this data for chi_id : 8165075, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 8165076, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 8165077, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 8165078, for now we just ignore these empty polygon points WARNING : margin is only used for type bib ! map_result returned by crop_photo_return_map_crop : length : 4 Here we crop with rles About to insert : list_path_to_insert length 4 new photo from crops ! About to upload 4 photos https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=crop_detect_varroa&access_token=78d09a0790ec6ecbf119343125a81fdc upload in portfolio : 20582914 init cache_photo without model_param we have 4 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593436_3820514 we have uploaded 4 photos in the portfolio 20582914 time of upload the photos Elapsed time : 4.5111963748931885 Now we prepare data that will be used for ellipse search ! About to compute ellipse and record with type : 520 score : 5120 strategy_opt : 5| | arg_min : 1.9500000000000002 min_score : 2311 | arg_min : -30.0 min_score : 1968 | arg_min : 17.8125 min_score : 1614 | arg_min : 31.875 min_score : 1105 | arg_min : 28.5 min_score : 1105 arg_min : 1.9500000000000002 min_score : 1105 arg_min : 25.0 min_score : 1088 arg_min : 24.9375 min_score : 979 arg_min : 31.875 min_score : 979 arg_min : 28.5 min_score : 979 yc : 31.875 xc : 24.9375 angle : 25.0 radius : 28.5 excentricity : 1.9500000000000002 yc : 31.875 xc : 24.9375 angle : 25.0 radius : 28.5 excentricity : 1.9500000000000002 Now saving polygons points : 1| batch 1 Loaded 1 chid ids of type : 520 CHI and polygons saved ! score : 5362 strategy_opt : 5| | arg_min : 1.9500000000000002 min_score : 2281 | arg_min : -10.0 min_score : 2127 | arg_min : 25.0 min_score : 2127 | arg_min : 30.9375 min_score : 714 | arg_min : 25.0 min_score : 714 arg_min : 1.9500000000000002 min_score : 714 arg_min : -5.0 min_score : 668 arg_min : 23.4375 min_score : 655 arg_min : 29.53125 min_score : 631 arg_min : 25.0 min_score : 631 yc : 29.53125 xc : 23.4375 angle : -5.0 radius : 25.0 excentricity : 1.9500000000000002 yc : 29.53125 xc : 23.4375 angle : -5.0 radius : 25.0 excentricity : 1.9500000000000002 Now saving polygons points : 1| batch 1 Loaded 2 chid ids of type : 520 + CHI and polygons saved ! score : 4603 strategy_opt : 5| | arg_min : 1.85 min_score : 2981 | arg_min : -50.0 min_score : 1356 | arg_min : 30.28125 min_score : 1079 | arg_min : 23.625 min_score : 995 | arg_min : 27.0 min_score : 995 arg_min : 1.6500000000000001 min_score : 961 arg_min : -70.0 min_score : 852 arg_min : 28.6875 min_score : 847 arg_min : 23.625 min_score : 847 arg_min : 27.0 min_score : 847 yc : 23.625 xc : 28.6875 angle : -70.0 radius : 27.0 excentricity : 1.6500000000000001 yc : 23.625 xc : 28.6875 angle : -70.0 radius : 27.0 excentricity : 1.6500000000000001 Now saving polygons points : 1| batch 1 Loaded 3 chid ids of type : 520 ++ CHI and polygons saved ! score : 7970 strategy_opt : 5| | arg_min : 1.9500000000000002 min_score : 1576 | arg_min : 40.0 min_score : 632 | arg_min : 20.15625 min_score : 561 | arg_min : 26.0 min_score : 561 | arg_min : 26.0 min_score : 561 arg_min : 1.8 min_score : 520 arg_min : 40.0 min_score : 520 arg_min : 18.8125 min_score : 494 arg_min : 26.0 min_score : 494 arg_min : 26.0 min_score : 494 yc : 26.0 xc : 18.8125 angle : 40.0 radius : 26.0 excentricity : 1.8 yc : 26.0 xc : 18.8125 angle : 40.0 radius : 26.0 excentricity : 1.8 Now saving polygons points : 1| batch 1 Loaded 4 chid ids of type : 520 +++ CHI and polygons saved ! ['temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0_ellipsebest.jpg', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165075_0_varroa_with_ellipsebest.jpg', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0_ellipsebest.jpg', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165076_0_varroa_with_ellipsebest.jpg', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0_ellipsebest.jpg', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165077_0_varroa_with_ellipsebest.jpg', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0_ellipsebest.jpg', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_bib_crop_8165078_0_varroa_with_ellipsebest.jpg'] About to upload 8 photos https://marlene.fotonower.com/api/v1/secured/portfolio/new?access_token=78d09a0790ec6ecbf119343125a81fdc upload in portfolio : 20582915 Result OK ! uploaded one batch 0 Elapsed time : 19.24599838256836 time spend for datou_step_exec : 27.57834768295288 time spend to save output : 2.384185791015625e-05 total time spend for step 1 : 27.57837152481079 step2:tile Sat Feb 15 05:24:20 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure verbose : False param_json : {'photo_tile_type': 17, 'whiten': True, 'remove_crop_border': True, 'minimal_size_crop_border': 900, 'stride': 240, 'crop_hashtag_type_tiled': 521, 'ETA': 86400, 'new_width': 480, 'new_height': 480, 'token': '78d09a0790ec6ecbf119343125a81fdc', 'portfolio_name': 'tile_taggage_varroa', 'crop_hashtag_type': 520, 'host': 'www.fotonower.com', 'arg_aux_upload': {'type_upload': 'python'}} type(crop_hashtag_type) : type(crop_hashtag_type_tiled) : We consider crop_hashtag_type is an integer ! map_chi_type_to_chi_type_cropped : {520: 521} TO DEPRECATE VR 14-6-18 map_filenames : {937852786: 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg'} list_pids : 1 list_pids : 2 list_subpids to replace list_pids : 0 batch 1 Loaded 4 chid ids of type : 520 ++++https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=tile_taggage_varroa&access_token=78d09a0790ec6ecbf119343125a81fdc created feed_id_new_photos : 20582916 with name tile_taggage_varroa feed_id_new_photos : 20582916 filename : temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg photo_id : 937852786 height_image_input : 480 width_image_input : 480 new_width : 480 new_height : 480 stride : 240 stride_relative : 0.1 chi to copy from the main photo to the tiled photo input_chi_for_this_image_as_chi : 4 list_bib_to_crops : 1 [(0, 480, 0, 480, 0)] new_crops_tiles : 1 crop_transformed : 4 batch 1 Loaded 1 chid ids of type : 17 treat the image : temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67.jpg , 0 before upload mediasElapsed time : 0.0078105926513671875 on upload les photos avec python init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593468_3820514 we have uploaded 1 photos in the portfolio 20582916 Importing ! upload mediasElapsed time : 0.8023087978363037 , 0Saving 4 CHIs. batch 1 Loaded 4 chid ids of type : 521 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! end of tileElapsed time : 2.029158592224121 time spend for datou_step_exec : 9.04291558265686 time spend to save output : 3.0517578125e-05 total time spend for step 2 : 9.042946100234985 step3:rotate Sat Feb 15 05:24:29 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou_step_rotate ! Warning, new_feed_id is empty ! We are in a datou with depends ! rotate photos of 0,15,30,45,60,75,90,105,120,135,150,165,180,195,210,225,240,255,270,285,300,315,330,345 degres batch 1 Loaded 4 chid ids of type : 521 ++++++++ map_chi of length : 1 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=rotate_data_augmentation_varroa_480_ellipse_320&access_token=78d09a0790ec6ecbf119343125a81fdc feed_id_new_photos : 20582917 Needs to change image size ! time for calcul the mask position with numpy : 0.0008156299591064453 nb_pixel_total : 1389 time to create 1 rle with old method : 0.0040128231048583984 .time for calcul the mask position with numpy : 0.00042438507080078125 nb_pixel_total : 1157 time to create 1 rle with old method : 0.0033724308013916016 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.00048351287841796875 nb_pixel_total : 694 time to create 1 rle with old method : 0.002713918685913086 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00047659873962402344 nb_pixel_total : 1162 time to create 1 rle with old method : 0.002907991409301758 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.0024766921997070312 nb_pixel_total : 221 time to create 1 rle with old method : 0.002999544143676758 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0005514621734619141 nb_pixel_total : 1155 time to create 1 rle with old method : 0.007124185562133789 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.0006558895111083984 nb_pixel_total : 143 time to create 1 rle with old method : 0.0005400180816650391 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0004932880401611328 nb_pixel_total : 1161 time to create 1 rle with old method : 0.00434112548828125 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.0030481815338134766 nb_pixel_total : 414 time to create 1 rle with old method : 0.003552675247192383 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0005049705505371094 nb_pixel_total : 1159 time to create 1 rle with old method : 0.005861520767211914 . crop are not in the shrunk photo ! On the border Smaller than minimal size ! Needs to change image size ! time for calcul the mask position with numpy : 0.0004904270172119141 nb_pixel_total : 1204 time to create 1 rle with old method : 0.004395008087158203 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.000392913818359375 nb_pixel_total : 1157 time to create 1 rle with old method : 0.004070758819580078 . crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.0003504753112792969 nb_pixel_total : 264 time to create 1 rle with old method : 0.0007710456848144531 On the border Smaller than minimal size ! Needs to change image size ! time for calcul the mask position with numpy : 0.00037479400634765625 nb_pixel_total : 1389 time to create 1 rle with old method : 0.003323078155517578 .time for calcul the mask position with numpy : 0.0003540515899658203 nb_pixel_total : 1157 time to create 1 rle with old method : 0.002781391143798828 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.0003876686096191406 nb_pixel_total : 694 time to create 1 rle with old method : 0.0017364025115966797 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003600120544433594 nb_pixel_total : 1162 time to create 1 rle with old method : 0.002849102020263672 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.00035858154296875 nb_pixel_total : 221 time to create 1 rle with old method : 0.0006432533264160156 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003628730773925781 nb_pixel_total : 1155 time to create 1 rle with old method : 0.002785205841064453 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.0003848075866699219 nb_pixel_total : 143 time to create 1 rle with old method : 0.0004525184631347656 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00036525726318359375 nb_pixel_total : 1160 time to create 1 rle with old method : 0.002780437469482422 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.0003814697265625 nb_pixel_total : 414 time to create 1 rle with old method : 0.0010981559753417969 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003676414489746094 nb_pixel_total : 1159 time to create 1 rle with old method : 0.0027849674224853516 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.0003368854522705078 nb_pixel_total : 1 time to create 1 rle with old method : 2.3603439331054688e-05 Needs to change image size ! time for calcul the mask position with numpy : 0.00039696693420410156 nb_pixel_total : 1204 time to create 1 rle with old method : 0.003570079803466797 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003714561462402344 nb_pixel_total : 1158 time to create 1 rle with old method : 0.0033559799194335938 . crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.0004489421844482422 nb_pixel_total : 264 time to create 1 rle with old method : 0.0008819103240966797 On the border Smaller than minimal size ! Needs to change image size ! time for calcul the mask position with numpy : 0.0003972053527832031 nb_pixel_total : 1389 time to create 1 rle with old method : 0.0039942264556884766 .time for calcul the mask position with numpy : 0.0003600120544433594 nb_pixel_total : 1157 time to create 1 rle with old method : 0.002800464630126953 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.0003788471221923828 nb_pixel_total : 727 time to create 1 rle with old method : 0.0018274784088134766 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003571510314941406 nb_pixel_total : 1162 time to create 1 rle with old method : 0.0028002262115478516 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.00038123130798339844 nb_pixel_total : 250 time to create 1 rle with old method : 0.0007331371307373047 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00035572052001953125 nb_pixel_total : 1155 time to create 1 rle with old method : 0.00274658203125 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.00038361549377441406 nb_pixel_total : 169 time to create 1 rle with old method : 0.0005838871002197266 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003654956817626953 nb_pixel_total : 1161 time to create 1 rle with old method : 0.002852201461791992 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.0003769397735595703 nb_pixel_total : 450 time to create 1 rle with old method : 0.0012133121490478516 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00036072731018066406 nb_pixel_total : 1159 time to create 1 rle with old method : 0.0027861595153808594 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.0003402233123779297 nb_pixel_total : 1 time to create 1 rle with old method : 2.4080276489257812e-05 Needs to change image size ! time for calcul the mask position with numpy : 0.0004754066467285156 nb_pixel_total : 1237 time to create 1 rle with old method : 0.0029349327087402344 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00037217140197753906 nb_pixel_total : 1158 time to create 1 rle with old method : 0.0027892589569091797 . crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.0003466606140136719 nb_pixel_total : 234 time to create 1 rle with old method : 0.0006771087646484375 On the border Smaller than minimal size ! Needs to change image size ! time for calcul the mask position with numpy : 0.00043702125549316406 nb_pixel_total : 1389 time to create 1 rle with old method : 0.00322723388671875 .time for calcul the mask position with numpy : 0.00035881996154785156 nb_pixel_total : 1157 time to create 1 rle with old method : 0.0027933120727539062 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.0003886222839355469 nb_pixel_total : 727 time to create 1 rle with old method : 0.0017905235290527344 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003643035888671875 nb_pixel_total : 1162 time to create 1 rle with old method : 0.0027740001678466797 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.00037550926208496094 nb_pixel_total : 250 time to create 1 rle with old method : 0.0007507801055908203 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003628730773925781 nb_pixel_total : 1155 time to create 1 rle with old method : 0.002786874771118164 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.0003769397735595703 nb_pixel_total : 169 time to create 1 rle with old method : 0.0005145072937011719 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003609657287597656 nb_pixel_total : 1161 time to create 1 rle with old method : 0.002720355987548828 . crop are not in the shrunk photo ! crop are not in the shrunk photo ! Needs to change image size ! time for calcul the mask position with numpy : 0.00039768218994140625 nb_pixel_total : 450 time to create 1 rle with old method : 0.0011813640594482422 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.0003528594970703125 nb_pixel_total : 1159 time to create 1 rle with old method : 0.002825498580932617 . crop are not in the shrunk photo ! On the border Smaller than minimal size ! Needs to change image size ! time for calcul the mask position with numpy : 0.0003676414489746094 nb_pixel_total : 1237 time to create 1 rle with old method : 0.0027556419372558594 On the border Smaller than minimal size ! time for calcul the mask position with numpy : 0.00037741661071777344 nb_pixel_total : 1157 time to create 1 rle with old method : 0.017578601837158203 . crop are not in the shrunk photo ! time for calcul the mask position with numpy : 0.00036072731018066406 nb_pixel_total : 234 time to create 1 rle with old method : 0.0006842613220214844 On the border Smaller than minimal size ! About to upload 24 photos upload in portfolio : 20582917 init cache_photo without model_param we have 24 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593472_3820514 we have uploaded 24 photos in the portfolio 20582917 time of upload the photos Elapsed time : 11.227560043334961 Len new_chis : 24 Len list_new_chi_with_photo_id : 28 of type : 529 batch 1 Loaded 28 chid ids of type : 529 Number RLEs to save : 1197 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 28 chid ids of type : 529 ++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! time spend for datou_step_exec : 16.339106559753418 time spend to save output : 9.012222290039062e-05 total time spend for step 3 : 16.33919668197632 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : rotate we use saveGeneral [937852786, 937852786, '1337814506'] Looping around the photos to save general results len do output : 24 /1337814511Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814512Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814513Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814514Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814515Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814517Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814518Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814519Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814520Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814521Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814522Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814523Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814524Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814525Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814526Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814527Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814528Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814529Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814530Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814531Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814532Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814533Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814534Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814535Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('243', None, None, None, None, None, None, None, None) ('243', None, '937852786', None, None, None, None, None, None) ('243', None, None, None, None, None, None, None, None) ('243', None, '937852786', None, None, None, None, None, None) ('243', None, None, None, None, None, None, None, None) ('243', None, '1337814506', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 75 time used for this insertion : 0.026285409927368164 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 3 output : {1337814511: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_00.jpg', [, ]], 1337814512: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_015.jpg', []], 1337814513: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_030.jpg', []], 1337814514: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_045.jpg', []], 1337814515: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_060.jpg', []], 1337814517: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_075.jpg', []], 1337814518: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_090.jpg', [, ]], 1337814519: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0105.jpg', []], 1337814520: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0120.jpg', []], 1337814521: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0135.jpg', []], 1337814522: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0150.jpg', []], 1337814523: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0165.jpg', []], 1337814524: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0180.jpg', [, ]], 1337814525: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0195.jpg', []], 1337814526: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0210.jpg', []], 1337814527: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0225.jpg', []], 1337814528: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0240.jpg', []], 1337814529: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0255.jpg', []], 1337814530: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0270.jpg', [, ]], 1337814531: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0285.jpg', []], 1337814532: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0300.jpg', []], 1337814533: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0315.jpg', []], 1337814534: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0330.jpg', []], 1337814535: ['937852786', 'temp/1739593432_3820514_937852786_7d9a231a08a1c63d0868e56a5361bf67_0345.jpg', []]} list chi : [[, ], [], [], [], [], [], [, ], [], [], [], [], [], [, ], [], [], [], [], [], [, ], [], [], [], [], []] ############################### TEST flip ################################ t Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : flip list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.09998512268066406 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:flip Sat Feb 15 05:24:49 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step_flip ! We are in a linear step without datou_depend ! batch 1 Loaded 6 chid ids of type : 741 +++++WARNING : Unexpected points, we should remove this data for chi_id : 18344210, for now we just ignore these empty polygon points + map_chi_objs of length : 1 photo_id in download_rotate_and_save : 911785586 list_chi_loc : 6 Vertical flip of photo 911785586 Horizontal flip of photo 911785586 About to upload 2 photos upload in portfolio : 1090565 init cache_photo without model_param we have 2 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593489_3820514 we have uploaded 2 photos in the portfolio 1090565 time of upload the photos Elapsed time : 1.0786874294281006 Len new_chis : 12 Len list_new_chi_with_photo_id : 12 of type : 741 batch 1 Loaded 12 chid ids of type : 741 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! time spend for datou_step_exec : 1.2778024673461914 time spend to save output : 5.91278076171875e-05 total time spend for step 1 : 1.2778615951538086 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : flip we use saveGeneral [911785586] Looping around the photos to save general results len do output : 2 /1337814541 /1337814543 before output type Managing all output in save final without adding information in the mtr_datou_result ('571', None, None, None, None, None, None, None, None) ('571', None, '911785586', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 time used for this insertion : 0.018941164016723633 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'1337814541': ['911785586', 'temp/1739593489_3820514_911785586_d8582feabcd359151ff718b5832248c7-big_flip_vert.jpg', [, , , , , ]], '1337814543': ['911785586', 'temp/1739593489_3820514_911785586_d8582feabcd359151ff718b5832248c7-big_flip_hori.jpg', [, , , , , ]]} ############################### TEST crop_rles ################################ # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! Unexpected type seems boolean for variable list_input_json ERROR or WARNING : can't parse json string Expecting value: line 1 column 1 (char 0) Tried to parse : TEST CROP RLES Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : crop list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.18074655532836914 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:crop Sat Feb 15 05:24:51 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step Crop ! param_json : {'photo_hashtag_type': 755, 'token': '78d09a0790ec6ecbf119343125a81fdc', 'feed_id_new_photos': 0, 'host': 'www.fotonower.com', 'crop_type': 'rle', 'margin_relative': 0.1, 'min_score': 0.3, 'upload,type': 'python'} margin_type : margin_relative margin_value : [0.1, 0.1, 0.1, 0.1] Loading chi in step crop with photo_hashtag_type : 755 Loading chi in step crop for list_pids : 1 ! batch 1 Loaded 8 chid ids of type : 755 ++++++++WARNING : margin is only used for type bib ! we have both polygon and rles we have both polygon and rles we have both polygon and rles we have both polygon and rles we have both polygon and rles we have both polygon and rles we have both polygon and rles we have both polygon and rles map_result returned by crop_photo_return_map_crop : length : 8 Here we crop with rles About to insert : list_path_to_insert length 8 new photo from crops ! About to upload 8 photos https://marlene.fotonower.com/api/v1/secured/portfolio/new?access_token=78d09a0790ec6ecbf119343125a81fdc upload in portfolio : 20582919 Result OK ! uploaded one batch 0 Elapsed time : 19.669426202774048 Now we prepare data that will be used for ellipse search ! time spend for datou_step_exec : 19.933446645736694 time spend to save output : 2.8133392333984375e-05 total time spend for step 1 : 19.93347477912903 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : crop we use saveGeneral [950103132] Looping around the photos to save general results len do output : 8 /1337814546Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814549Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814551Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814553Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814555Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814557Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814558Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814560Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('686', None, None, None, None, None, None, None, None) ('686', None, '950103132', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 25 time used for this insertion : 0.020990371704101562 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'1337814546': ['950103132', 'temp/1739593491_3820514_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670931_0.jpg', (183, 199, 15, 41)], '1337814549': ['950103132', 'temp/1739593491_3820514_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670932_0.jpg', (38, 85, 113, 140)], '1337814551': ['950103132', 'temp/1739593491_3820514_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670933_0.jpg', (168, 194, 141, 151)], '1337814553': ['950103132', 'temp/1739593491_3820514_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670934_0.jpg', (47, 101, 16, 110)], '1337814555': ['950103132', 'temp/1739593491_3820514_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670935_0.jpg', (175, 199, 104, 111)], '1337814557': ['950103132', 'temp/1739593491_3820514_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670936_0.jpg', (86, 130, 184, 196)], '1337814558': ['950103132', 'temp/1739593491_3820514_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670937_0.jpg', (79, 195, 0, 61)], '1337814560': ['950103132', 'temp/1739593491_3820514_950103132_4f47bd527301396b0a701a1b4183ba00_rle_crop_1947670938_0.jpg', (131, 155, 181, 195)]} 8 ############################### TEST angular_coeff ################################ t Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : angular_coeff list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.21913385391235352 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:angular_coeff Sat Feb 15 05:25:11 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec beginning of step detection filter param_json : {'input_type': 846, 'output_type': -1, 'orientation_type': 872, 'ref_crop_type': 846, 'condition_crop': 'car', 'criteria_crop': 'center_rect', 'crops_coeffs': {'CAR_EXTERIEUR_angle_avant_droit.*': {'aile-avant': [[15, 0.0], [240, 0.0], [285, 1.0], [345, 1.0]], 'capot': [[45, 1.0], [60, 0.5], [270, 0.0], [315, 1.0], [360, 1.0]]}}} angular_coefficients_to_crops batch 1 Loaded 19 chid ids of type : 846 treating photo 932296368 time spend for datou_step_exec : 0.18758130073547363 time spend to save output : 5.53131103515625e-05 total time spend for step 1 : 0.1876366138458252 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {932296368: ([(932296368, 2106233860, 846, 1066, 1277, 93, 340, 0.31964028378983567, 0, []), (932296368, 2106233860, 846, 434, 690, 218, 498, 0.7170410105787726, 0, []), (932296368, 503548896, 846, 902, 1111, 466, 576, 0.31724966, 769189715, []), (932296368, 599722655, 846, 523, 1100, 152, 337, 0.98039776, 0, []), (932296368, 492601069, 846, 143, 1190, 90, 695, 0.9696157, 769189717, []), (932296368, 492601069, 846, 0, 408, 246, 719, 0.9431181, 769189718, []), (932296368, 2096875722, 846, 567, 964, 162, 215, 0.55490255, 769189721, []), (932296368, 2096875709, 846, 437, 939, 24, 198, 0.9983077, 769189723, []), (932296368, 2096875709, 846, 1004, 1263, 28, 144, 0.9485744, 769189724, []), (932296368, 624624117, 846, 595, 1122, 331, 640, 0.99100167, 769189725, []), (932296368, 492624020, 846, 585, 874, 308, 393, 0.78697366, 769189727, []), (932296368, 2096875719, 846, 943, 1100, 428, 547, 0.96733797, 769189729, []), (932296368, 492654799, 846, 253, 467, 35, 441, 0.99621326, 769189730, []), (932296368, 492689227, 846, 1118, 1264, 270, 438, 0.9901647, 769189732, []), (932296368, 492689227, 846, 486, 671, 378, 690, 0.98789483, 769189733, []), (932296368, 492689227, 846, 161, 255, 229, 409, 0.70801014, 769189734, []), (932296368, 492925064, 846, 261, 421, 27, 193, 0.92215157, 769189737, []), (932296368, 492925064, 846, 873, 1045, 46, 156, 0.7535122, 769189738, []), (932296368, 492925064, 846, 1090, 1279, 20, 107, 0.45259848, 769189739, [])],)} test angular coeff is a success ! ############################### TEST detection_filter_by_crop ################################ t Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : detection_filter_by_crop list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.12251138687133789 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:detection_filter_by_crop Sat Feb 15 05:25:11 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec beginning of step detection filter param_json : {'input_type': 631, 'output_type': -1, 'condition_type': 445, 'condition_crop': 'car', 'criteria_crop': 'center_rect', 'min_surface_ratio': 0.7} conditional_crop_copy batch 1 Loaded 3 chid ids of type : 445 +++batch 1 Loaded 35 chid ids of type : 631 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++batch 1 Loaded 3 chid ids of type : 445 +++ treating photo 946711423 time spend for datou_step_exec : 0.1363825798034668 time spend to save output : 3.528594970703125e-05 total time spend for step 1 : 0.13641786575317383 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {946711423: ([(946711423, 624624117, 631, 226, 569, 252, 425, 0.99812776, 1947740368, 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'312,179,311,178,308,179,309,180', '268,269,264,269,259,266,259,262,261,258,261,250,265,245,269,250,270,257,274,260,278,265,275,267,269,268', '414,281,401,281,414,281']), (946711423, 2096875722, 631, 433, 558, 248, 286, 0.44133398, 1947740397, ['492,272,474,272,473,271,468,271,465,269,460,269,460,268,465,266,467,266,468,265,470,265,471,264,475,264,476,263,479,263,480,262,486,262,487,261,491,261,492,260,495,260,496,259,502,259,506,257,510,257,514,255,517,255,518,254,530,253,531,252,535,252,536,251,538,251,539,252,543,252,544,253,547,253,549,251,553,251,555,253,555,267,552,270,550,270,550,269,548,267,547,267,547,267,548,266,547,265,545,266,540,266,539,264,530,264,529,263,524,263,519,266,513,266,510,268,507,268,506,269,499,270,498,271,493,271', '438,279,435,279,435,273,436,272,448,271,449,272,448,274,443,274,440,277,440,278']), (946711423, 492654799, 631, 399, 569, 68, 251, 0.41876298, 1947740399, []), (946711423, 492624020, 631, 420, 552, 244, 293, 0.35962066, 1947740400, ['474,289,453,289,452,288,439,288,437,286,431,286,427,284,423,284,422,283,422,275,427,275,428,273,430,272,435,272,436,271,438,271,442,269,447,269,450,267,454,267,460,264,464,264,467,262,483,261,484,260,488,260,489,259,494,259,495,258,502,258,503,257,505,257,509,255,512,255,516,252,520,252,521,251,526,250,530,248,534,248,535,247,546,247,547,248,549,248,549,250,550,251,550,266,551,267,551,275,550,276,550,278,549,279,549,281,537,282,535,284,528,284,527,285,504,285,503,286,495,286,492,288,488,287,487,288,475,288']), (946711423, 503548896, 631, 301, 540, 339, 403, 0.740756, 3140491551, ['442,401,371,401,371,397,366,390,365,386,356,386,353,384,348,383,319,383,319,378,314,370,310,370,305,368,304,357,305,353,330,353,339,356,378,356,379,357,474,357,475,356,488,356,493,353,501,354,507,352,517,352,522,351,527,346,530,347,533,351,530,355,527,356,515,356,505,362,503,365,497,368,494,372,489,374,492,376,488,378,490,380,495,380,487,382,485,385,476,387,469,392,461,393,456,395,451,399,447,399', '519,353,518,352,517,353,518,354'])],)} test detection filter by crop is a success ! ############################### TEST detection_filter_by_classif ################################ t Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : detection_filter_by_classif list_input_json : [] origin we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 0.004945039749145508 About to test input to load Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:detection_filter_by_classif Sat Feb 15 05:25:12 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec beginning of step detection filter with classification results param_json : {'input_type': 631, 'output_type': 816, 'condition_type': 872, 'crops_ok': {'CAR_DOCUMENT.*': {}, 'CAR_INTERIEUR.*': {}, 'CAR_EXTERIEUR_angle_avant_droit.*': {'Retroviseur': 2, 'Roue': 2, 'Capot': 1, 'Pare-brise': 1, 'vitre': 10, 'phare': 2, 'Feu-antibrouillard': 2, 'poignee': 2, 'porte': 2, 'calandre': 1, 'logo-marque': 1, 'Plaque-immatriculation': 1, 'Essuie-glace': 1, 'pare-choc': 1, 'toit': 1, 'logo-roue': 1, 'aile-avant': 1}}, 'separation': {'CAR_EXTERIEUR_avant.*': {'pare-choc': ['pare-chocs-avant'], 'phare': ['phare-gauche', 'a-droite-de', 'phare-droit']}, 'CAR_EXTERIEUR_angle_avant_droit.*': {'pare-choc': ['pare-chocs-avant'], 'phare': ['phare-droite', 'a-gauche-de', 'phare-gauche'], 'porte': ['porte-avant', 'a-droite-de', 'porte-arriere']}}} conditional_crop_by_classif_copy batch 1 Loaded 35 chid ids of type : 631 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ treating photo 946711423 batch 1 Loaded 0 chid ids of type : 0 batch 1 Loaded 23 chid ids of type : 816 Number RLEs to save : 1600 TO DO : save crop sub photo not yet done ! time spend for datou_step_exec : 1.4007153511047363 time spend to save output : 8.96453857421875e-05 total time spend for step 1 : 1.4008049964904785 caffe_path_current : About to save ! 0 After save, about to update current ! test detection filter by classif is a success ! ############################### TEST blur_detection ################################ t Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : blur_detection list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.1533946990966797 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:blur_detection Sat Feb 15 05:25:13 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec inside step blur_detection methode: ratio et variance treat image : temp/1739593513_3820514_930729675_b2d2beaaee733d521cbb0c9800a29073.jpg resize: (600, 800) 930729675 12.961859636534896 time spend for datou_step_exec : 0.26114892959594727 time spend to save output : 5.507469177246094e-05 total time spend for step 1 : 0.2612040042877197 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {930729675: [(930729675, 12.961859636534896, 492688767)]} {930729675: [(930729675, 12.961859636534896, 492688767)]} ############################### TEST detect_point_224x224 ################################ test_detect_point_224x224 Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 4589 thcl is not linked in the step_by_step architecture ! WARNING : step 4590 argmax is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! List Step Type Loaded in datou : thcl, argmax list_input_json : [] origin BBBBBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFFFBBFFBBBFBFBFBFBFBFBFBFFBFBFBFBFBFFBFFFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 64 ; length of list_pids : 64 ; length of list_args : 64 time to download the photos : 2.1309993267059326 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 2 step1:thcl Sat Feb 15 05:25:16 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step Thcl ! we are using the classfication for only one thcl 1528 time to import caffe and check if the image exist : 0.0006268024444580078 time to convert the images to numpy array : 0.005542278289794922 time to import caffe and check if the image exist : 0.009865999221801758 time to convert the images to numpy array : 0.05056643486022949 time to import caffe and check if the image exist : 0.005454063415527344 time to convert the images to numpy array : 0.05673837661743164 time to import caffe and check if the image exist : 0.008443355560302734 time to convert the images to numpy array : 0.052983760833740234 time to import caffe and check if the image exist : 0.012729406356811523 time to convert the images to numpy array : 0.050821781158447266 time to import caffe and check if the image exist : 0.020710468292236328 time to convert the images to numpy array : 0.04577231407165527 time to import caffe and check if the image exist : 0.007529497146606445 time to convert the images to numpy array : 0.05764341354370117 time to import caffe and check if the image exist : 0.011302947998046875 time to convert the images to numpy array : 0.05336880683898926 time to import caffe and check if the image exist : 0.011328697204589844 time to convert the images to numpy array : 0.058177947998046875 time to import caffe and check if the image exist : 0.015014171600341797 time to convert the images to numpy array : 0.055629730224609375 total time to convert the images to numpy array : 0.07129979133605957 list photo_ids error: [] list photo_ids correct : [987515238, 987515241, 987515242, 987515243, 987515244, 987515245, 987515246, 987515247, 987515189, 987515190, 987515192, 987515193, 987515195, 987515196, 987515198, 987515222, 987515223, 987515224, 987515226, 987515227, 987515228, 987515230, 987515248, 987515249, 987515250, 987515207, 987515208, 987515209, 987515211, 987515200, 987515201, 987515202, 987515204, 987515205, 987515239, 987515240, 987515212, 987515213, 987515215, 987515216, 987515217, 987515219, 987515220, 987515231, 987515232, 987515233, 987515234, 987515235, 987515236, 987515237, 987515182, 987515183, 987515184, 987515185, 987515186, 987515187, 987515188, 987515175, 987515176, 987515177, 987515178, 987515179, 987515180, 987515181] number of photos to traite : 64 try to delete the photos incorrect in DB tagging for thcl : 1528 To do loadFromThcl(), then load ParamDescType : thcl1528 thcls : [{'id': 1528, 'mtr_user_id': 31, 'name': 'learn_refus_upm_blanches_1924', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Autre_Environement,Carton,Kraft,Lointain_Papier_Magazine,Metal,Papier_Magazine,Plastique,Sol_Environement,Teint_Dans_La_Masse,autre_refus', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 1927, 'photo_desc_type': 4421, 'type_classification': 'caffe', 'hashtag_id_list': '2107752388,492774966,493202403,2107752389,492628673,2107752386,492725882,2107752387,2107752385,2107752406'}] thcl {'id': 1528, 'mtr_user_id': 31, 'name': 'learn_refus_upm_blanches_1924', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Autre_Environement,Carton,Kraft,Lointain_Papier_Magazine,Metal,Papier_Magazine,Plastique,Sol_Environement,Teint_Dans_La_Masse,autre_refus', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 1927, 'photo_desc_type': 4421, 'type_classification': 'caffe', 'hashtag_id_list': '2107752388,492774966,493202403,2107752389,492628673,2107752386,492725882,2107752387,2107752385,2107752406'} Update svm_hashtag_type_desc : 4421 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (4421, 'learn_refus_upm_blanches_1924', 16384, 25088, 'learn_refus_upm_blanches_1924', 'res5b', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2019, 10, 22, 17, 39, 25), datetime.datetime(2019, 10, 22, 17, 39, 25)) To loadFromThcl() : net_4421 begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 3346 max_wait_temp : 1 max_wait : 0 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (4421, 'learn_refus_upm_blanches_1924', 16384, 25088, 'learn_refus_upm_blanches_1924', 'res5b', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2019, 10, 22, 17, 39, 25), datetime.datetime(2019, 10, 22, 17, 39, 25)) None mean_file_type : mean_file_path : prototxt_file_path : model : learn_refus_upm_blanches_1924 Inside get_net Inside get_net before cache_data_model model_param file didn't exist Inside get_net before CDM.load_model_par_type model_name : learn_refus_upm_blanches_1924 model_type : caffe list file need : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file exist in s3 : ['caffemodel', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file manque in s3 : ['deploy_conv_normal.prototxt', 'deploy_fc.prototxt'] local folder : /data/models_weight/learn_refus_upm_blanches_1924 /data/models_weight/learn_refus_upm_blanches_1924/caffemodel size_local : 45774543 size in s3 : 45774543 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:04 caffemodel already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/deploy.prototxt size_local : 17312 size in s3 : 17312 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:03 deploy.prototxt already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/mean.npy size_local : 1572992 size in s3 : 1572992 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:05 mean.npy already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/synset_words.txt size_local : 218 size in s3 : 218 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:04 synset_words.txt already exist and didn't need to update Inside get_net after CDM.load_model_par_type After if not only_with_local_cache: /home/admin/workarea/install/darknet/:/home/admin/workarea/git/Velours/python:/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python:/home/admin/mtr/.credentials:/home/admin/workarea/install/caffe/python:/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools/:/home/admin/workarea/git/fotonowerpip/:/home/admin/workarea/install/segment-anything:/home/admin//workarea/git/pyfvs/ Here before set mode gpu Doing nothing but we could set mode gpu after set mode gpu prototxt_filename : /data/models_weight/learn_refus_upm_blanches_1924/deploy.prototxt caffemodel_filename : /data/models_weight/learn_refus_upm_blanches_1924/caffemodel now we set caffe to gpu mode before predict begin to check gpu status inside check gpu memory l 3637 free memory gpu now : 3346 max_wait_temp : 1 max_wait : 0 dict_keys(['res5b', 'prob']) time used to do the prepocess of the images : 0.0606236457824707 time used to do the prediction : 0.25145411491394043 save descriptor for thcl : 1528 time to traite the descriptors : 4.120816469192505 storage_type for insertDescriptorsMulti : 1 To insert : 987515238 To insert : 987515241 To insert : 987515242 To insert : 987515243 To insert : 987515244 To insert : 987515245 To insert : 987515246 To insert : 987515247 To insert : 987515189 To insert : 987515190 To insert : 987515192 To insert : 987515193 To insert : 987515195 To insert : 987515196 To insert : 987515198 To insert : 987515222 To insert : 987515223 To insert : 987515224 To insert : 987515226 To insert : 987515227 To insert : 987515228 To insert : 987515230 To insert : 987515248 To insert : 987515249 To insert : 987515250 To insert : 987515207 To insert : 987515208 To insert : 987515209 To insert : 987515211 To insert : 987515200 To insert : 987515201 To insert : 987515202 To insert : 987515204 To insert : 987515205 To insert : 987515239 To insert : 987515240 To insert : 987515212 To insert : 987515213 To insert : 987515215 To insert : 987515216 To insert : 987515217 To insert : 987515219 To insert : 987515220 To insert : 987515231 To insert : 987515232 To insert : 987515233 To insert : 987515234 To insert : 987515235 To insert : 987515236 To insert : 987515237 To insert : 987515182 To insert : 987515183 To insert : 987515184 To insert : 987515185 To insert : 987515186 To insert : 987515187 To insert : 987515188 To insert : 987515175 To insert : 987515176 To insert : 987515177 To insert : 987515178 To insert : 987515179 To insert : 987515180 To insert : 987515181 time to insert the descriptors : 14.121907234191895 time spend for datou_step_exec : 22.170409440994263 time spend to save output : 9.584426879882812e-05 total time spend for step 1 : 22.17050528526306 step2:argmax Sat Feb 15 05:25:38 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step Argmax ! calculate argmax for thcl : 1528 time spend for datou_step_exec : 0.0012886524200439453 time spend to save output : 1.9073486328125e-05 total time spend for step 2 : 0.0013077259063720703 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 2 output : {'987515238': [('987515238', 'Carton', 0.9995733, 1927, '1528'), 'temp/1739593513_3820514_987515238_e6292cb81e05894cfeb4b99f21a1d3f8.jpg'], '987515241': [('987515241', 'Carton', 0.98210734, 1927, '1528'), 'temp/1739593513_3820514_987515241_073420d938f5f010ffd5b4353c064e09.jpg'], '987515242': [('987515242', 'Carton', 0.93583024, 1927, '1528'), 'temp/1739593513_3820514_987515242_327abb5215d6fd1f0aad51f53ed8c324.jpg'], '987515243': [('987515243', 'Papier_Magazine', 0.87441957, 1927, '1528'), 'temp/1739593513_3820514_987515243_4375283f3bc5cdaa431c2fc6f17f53a4.jpg'], '987515244': [('987515244', 'Papier_Magazine', 0.81726253, 1927, '1528'), 'temp/1739593513_3820514_987515244_419530eaef5ef868f75c758b94eea4b4.jpg'], '987515245': [('987515245', 'Carton', 0.8661034, 1927, '1528'), 'temp/1739593513_3820514_987515245_757d9d208d5bd4375c5f21f68b699148.jpg'], '987515246': [('987515246', 'Carton', 0.99923193, 1927, '1528'), 'temp/1739593513_3820514_987515246_671a708f67f2efa19004b8257fc7b9c8.jpg'], '987515247': [('987515247', 'Carton', 0.9996679, 1927, '1528'), 'temp/1739593513_3820514_987515247_e47b65403df916ba909bc9c439b0af73.jpg'], '987515189': [('987515189', 'Carton', 0.9977956, 1927, '1528'), 'temp/1739593513_3820514_987515189_8e8590a26f72249d4c2116dffd0cf668.jpg'], '987515190': [('987515190', 'Carton', 0.9764656, 1927, '1528'), 'temp/1739593513_3820514_987515190_d56932bfc6ba2a8c974c691108755017.jpg'], '987515192': [('987515192', 'Papier_Magazine', 0.9999114, 1927, '1528'), 'temp/1739593513_3820514_987515192_b661073b218f5f056833d6af1c617153.jpg'], '987515193': [('987515193', 'Papier_Magazine', 0.9993963, 1927, '1528'), 'temp/1739593513_3820514_987515193_1a97fceb4dcbf5821d783b2e00b52fe6.jpg'], '987515195': [('987515195', 'Carton', 0.9844632, 1927, '1528'), 'temp/1739593513_3820514_987515195_30ccb89dfe410c445878a7f2819ddc36.jpg'], '987515196': [('987515196', 'Carton', 0.984643, 1927, '1528'), 'temp/1739593513_3820514_987515196_30ccb89dfe410c445878a7f2819ddc36.jpg'], '987515198': [('987515198', 'Carton', 0.9661347, 1927, '1528'), 'temp/1739593513_3820514_987515198_599e80f444c876f407e94b533c89360b.jpg'], '987515222': [('987515222', 'Carton', 0.99746644, 1927, '1528'), 'temp/1739593513_3820514_987515222_067a027bc7402f969b6277d0dcb47eaa.jpg'], '987515223': [('987515223', 'Carton', 0.9920523, 1927, '1528'), 'temp/1739593513_3820514_987515223_ebb57f09941cd11d7ee45a9368a883c1.jpg'], '987515224': [('987515224', 'Carton', 0.9085473, 1927, '1528'), 'temp/1739593513_3820514_987515224_e8747b400e713ecbd08d5b75db4d7568.jpg'], '987515226': [('987515226', 'Papier_Magazine', 0.9870401, 1927, '1528'), 'temp/1739593513_3820514_987515226_a18048dca1a77ae086b62cf07759f704.jpg'], '987515227': [('987515227', 'Papier_Magazine', 0.9000772, 1927, '1528'), 'temp/1739593513_3820514_987515227_e9c45a0e576ec9e44c1379c3fc5fec7c.jpg'], '987515228': [('987515228', 'Papier_Magazine', 0.52339065, 1927, '1528'), 'temp/1739593513_3820514_987515228_9f1759f20c9e603bccb9f9879d2f0d54.jpg'], '987515230': [('987515230', 'Carton', 0.9994048, 1927, '1528'), 'temp/1739593513_3820514_987515230_846ad925884264181565c81d152a2e94.jpg'], '987515248': [('987515248', 'Carton', 0.9812541, 1927, '1528'), 'temp/1739593513_3820514_987515248_a70ad88462a22fb62a120721a42b2d42.jpg'], '987515249': [('987515249', 'Carton', 0.9813627, 1927, '1528'), 'temp/1739593513_3820514_987515249_a70ad88462a22fb62a120721a42b2d42.jpg'], '987515250': [('987515250', 'Carton', 0.98085034, 1927, '1528'), 'temp/1739593513_3820514_987515250_b2827c9639df69656f23abcc7f2f82d9.jpg'], '987515207': [('987515207', 'Papier_Magazine', 0.8742503, 1927, '1528'), 'temp/1739593513_3820514_987515207_de216ddb041e249524b0fb2b949064a5.jpg'], '987515208': [('987515208', 'Carton', 0.99173915, 1927, '1528'), 'temp/1739593513_3820514_987515208_a2b90cb74908aa64bbc4aae58f0c5ae8.jpg'], '987515209': [('987515209', 'Carton', 0.9678553, 1927, '1528'), 'temp/1739593513_3820514_987515209_02dfe1ae39f51994652f4a8538844aea.jpg'], '987515211': [('987515211', 'Carton', 0.9734283, 1927, '1528'), 'temp/1739593513_3820514_987515211_72cc7664d45bd40477351b9b764f1500.jpg'], '987515200': [('987515200', 'Carton', 0.9859359, 1927, '1528'), 'temp/1739593513_3820514_987515200_978964436b5d5fb0eeda17e3bfafe889.jpg'], '987515201': [('987515201', 'Carton', 0.9954613, 1927, '1528'), 'temp/1739593513_3820514_987515201_b224d2acdc7fa2bbb134c09db6bca7ce.jpg'], '987515202': [('987515202', 'Carton', 0.9910607, 1927, '1528'), 'temp/1739593513_3820514_987515202_3314bd90d1404f31b827d8925abf2d62.jpg'], '987515204': [('987515204', 'Papier_Magazine', 0.99508166, 1927, '1528'), 'temp/1739593513_3820514_987515204_9779c4f9d44360a9c80499e3b01e8a09.jpg'], '987515205': [('987515205', 'Papier_Magazine', 0.9908942, 1927, '1528'), 'temp/1739593513_3820514_987515205_fd4b136d0b3a9a1a347942d7191f6fea.jpg'], '987515239': [('987515239', 'Carton', 0.99978334, 1927, '1528'), 'temp/1739593513_3820514_987515239_b3fa6f29636080b5138c8d8c33fea309.jpg'], '987515240': [('987515240', 'Carton', 0.99951994, 1927, '1528'), 'temp/1739593513_3820514_987515240_7829b9b15f1bf128ea4e2c1a39b9f0dd.jpg'], '987515212': [('987515212', 'Carton', 0.9869538, 1927, '1528'), 'temp/1739593513_3820514_987515212_b0a038fcb9678ebfd60d9b1f6ec1fc17.jpg'], '987515213': [('987515213', 'Carton', 0.9870027, 1927, '1528'), 'temp/1739593513_3820514_987515213_b0a038fcb9678ebfd60d9b1f6ec1fc17.jpg'], '987515215': [('987515215', 'Papier_Magazine', 0.9939182, 1927, '1528'), 'temp/1739593513_3820514_987515215_902ef348a7eebb9a8b87f42927347936.jpg'], '987515216': [('987515216', 'Papier_Magazine', 0.97747076, 1927, '1528'), 'temp/1739593513_3820514_987515216_4f7dc21f1d2cd3fcabadc4a6755921e1.jpg'], '987515217': [('987515217', 'Carton', 0.53092, 1927, '1528'), 'temp/1739593513_3820514_987515217_78877bb2c5760be28518d17f77d1c609.jpg'], '987515219': [('987515219', 'Carton', 0.9993654, 1927, '1528'), 'temp/1739593513_3820514_987515219_c2d417a5ba6ccf7c84527636f8d5eef9.jpg'], '987515220': [('987515220', 'Carton', 0.99638075, 1927, '1528'), 'temp/1739593513_3820514_987515220_e729f316c4c3b32049adfbaaa336d95c.jpg'], '987515231': [('987515231', 'Carton', 0.9994204, 1927, '1528'), 'temp/1739593513_3820514_987515231_dbf4cafa71b6db4771c5c8f0c25e9cda.jpg'], '987515232': [('987515232', 'Carton', 0.99924505, 1927, '1528'), 'temp/1739593513_3820514_987515232_38db7950cdb3c674ee0ad65915b021f3.jpg'], '987515233': [('987515233', 'Carton', 0.98352975, 1927, '1528'), 'temp/1739593513_3820514_987515233_a92514bed0e8c5724f2d032d3ab1e2ad.jpg'], '987515234': [('987515234', 'Carton', 0.94476575, 1927, '1528'), 'temp/1739593513_3820514_987515234_2eca3480aed0f8b876242675ad99b666.jpg'], '987515235': [('987515235', 'Papier_Magazine', 0.89217824, 1927, '1528'), 'temp/1739593513_3820514_987515235_87075955a2f76b3948b47ffe1825ecd9.jpg'], '987515236': [('987515236', 'Papier_Magazine', 0.5390033, 1927, '1528'), 'temp/1739593513_3820514_987515236_8b44a98b1aceadad73ed000d65836a9a.jpg'], '987515237': [('987515237', 'Carton', 0.7696803, 1927, '1528'), 'temp/1739593513_3820514_987515237_1183dfa371a457f11ce2b622c7cf9467.jpg'], '987515182': [('987515182', 'Carton', 0.99240994, 1927, '1528'), 'temp/1739593513_3820514_987515182_fe7f29bf6d13e08c3e985f91b5232178.jpg'], '987515183': [('987515183', 'Papier_Magazine', 0.99999213, 1927, '1528'), 'temp/1739593513_3820514_987515183_6aab9ca0421398b4899892c10c2594c6.jpg'], '987515184': [('987515184', 'Papier_Magazine', 0.9997311, 1927, '1528'), 'temp/1739593513_3820514_987515184_19c8c2177209a285df6014d95fe53f2c.jpg'], '987515185': [('987515185', 'Papier_Magazine', 0.7972158, 1927, '1528'), 'temp/1739593513_3820514_987515185_e172d54457cabee9d7f02ee1300f3ae9.jpg'], '987515186': [('987515186', 'Carton', 0.984766, 1927, '1528'), 'temp/1739593513_3820514_987515186_797def426440b544aa80dbd63a19234a.jpg'], '987515187': [('987515187', 'Carton', 0.98118454, 1927, '1528'), 'temp/1739593513_3820514_987515187_9f62f98efd3caca0b9c17d27f5c70440.jpg'], '987515188': [('987515188', 'Carton', 0.99567187, 1927, '1528'), 'temp/1739593513_3820514_987515188_4116f9906657a69bb76c2fda982037b9.jpg'], '987515175': [('987515175', 'Papier_Magazine', 0.9998136, 1927, '1528'), 'temp/1739593513_3820514_987515175_8b398cba2f448622cd9657f5eb3f9796.jpg'], '987515176': [('987515176', 'Papier_Magazine', 0.999813, 1927, '1528'), 'temp/1739593513_3820514_987515176_8b398cba2f448622cd9657f5eb3f9796.jpg'], '987515177': [('987515177', 'Papier_Magazine', 0.9772156, 1927, '1528'), 'temp/1739593513_3820514_987515177_4a54e9967227806219ddf45d256539d8.jpg'], '987515178': [('987515178', 'Carton', 0.8580938, 1927, '1528'), 'temp/1739593513_3820514_987515178_298b3d2bfe0fda6787b59a78e2e68867.jpg'], '987515179': [('987515179', 'Carton', 0.92724913, 1927, '1528'), 'temp/1739593513_3820514_987515179_f7d4d1757a470f4c96dc3541eac88b9e.jpg'], '987515180': [('987515180', 'Carton', 0.98998356, 1927, '1528'), 'temp/1739593513_3820514_987515180_776a5d7d8486ee2961bbe3a0d90f95b5.jpg'], '987515181': [('987515181', 'Carton', 0.99777263, 1927, '1528'), 'temp/1739593513_3820514_987515181_1738c2798fb31152809ecb443ac286d6.jpg']} Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : detect_points list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.09597587585449219 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:detect_points Sat Feb 15 05:25:38 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step predict points ! Inside try reload ! gpu_mode in detect_points : 1 To load net FromThcl() model_param file didn't exist model_name : learn_refus_upm_blanches_1924 model_type : caffe list file need : ['caffemodel', 'deploy_conv_normal.prototxt', 'deploy_fc.prototxt', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file exist in s3 : ['caffemodel', 'deploy.prototxt', 'mean.npy', 'synset_words.txt'] file manque in s3 : ['deploy_conv_normal.prototxt', 'deploy_fc.prototxt'] local folder : /data/models_weight/learn_refus_upm_blanches_1924 /data/models_weight/learn_refus_upm_blanches_1924/caffemodel size_local : 45774543 size in s3 : 45774543 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:04 caffemodel already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/deploy.prototxt size_local : 17312 size in s3 : 17312 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:03 deploy.prototxt already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/mean.npy size_local : 1572992 size in s3 : 1572992 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:05 mean.npy already exist and didn't need to update /data/models_weight/learn_refus_upm_blanches_1924/synset_words.txt size_local : 218 size in s3 : 218 create time local : 2021-08-09 05:29:53 create time in s3 : 2021-08-06 19:36:04 synset_words.txt already exist and didn't need to update reshape net's input to : (224, 224) origin shape : (10, 3, 224, 224) after reshape : (1, 3, 224, 224) [('data', (1, 3, 224, 224)), ('conv1', (1, 64, 112, 112)), ('pool1', (1, 64, 56, 56)), ('pool1_pool1_0_split_0', (1, 64, 56, 56)), ('pool1_pool1_0_split_1', (1, 64, 56, 56)), ('res2a_branch1', (1, 64, 56, 56)), ('res2a_branch2a', (1, 64, 56, 56)), ('res2a_branch2b', (1, 64, 56, 56)), ('res2a', (1, 64, 56, 56)), ('res2a_res2a_relu_0_split_0', (1, 64, 56, 56)), ('res2a_res2a_relu_0_split_1', (1, 64, 56, 56)), ('res2b_branch2a', (1, 64, 56, 56)), ('res2b_branch2b', (1, 64, 56, 56)), ('res2b', (1, 64, 56, 56)), ('res2b_res2b_relu_0_split_0', (1, 64, 56, 56)), ('res2b_res2b_relu_0_split_1', (1, 64, 56, 56)), ('res3a_branch1', (1, 128, 28, 28)), ('res3a_branch2a', (1, 128, 28, 28)), ('res3a_branch2b', (1, 128, 28, 28)), ('res3a', (1, 128, 28, 28)), ('res3a_res3a_relu_0_split_0', (1, 128, 28, 28)), ('res3a_res3a_relu_0_split_1', (1, 128, 28, 28)), ('res3b_branch2a', (1, 128, 28, 28)), ('res3b_branch2b', (1, 128, 28, 28)), ('res3b', (1, 128, 28, 28)), ('res3b_res3b_relu_0_split_0', (1, 128, 28, 28)), ('res3b_res3b_relu_0_split_1', (1, 128, 28, 28)), ('res4a_branch1', (1, 256, 14, 14)), ('res4a_branch2a', (1, 256, 14, 14)), ('res4a_branch2b', (1, 256, 14, 14)), ('res4a', (1, 256, 14, 14)), ('res4a_res4a_relu_0_split_0', (1, 256, 14, 14)), ('res4a_res4a_relu_0_split_1', (1, 256, 14, 14)), ('res4b_branch2a', (1, 256, 14, 14)), ('res4b_branch2b', (1, 256, 14, 14)), ('res4b', (1, 256, 14, 14)), ('res4b_res4b_relu_0_split_0', (1, 256, 14, 14)), ('res4b_res4b_relu_0_split_1', (1, 256, 14, 14)), ('res5a_branch1', (1, 512, 7, 7)), ('res5a_branch2a', (1, 512, 7, 7)), ('res5a_branch2b', (1, 512, 7, 7)), ('res5a', (1, 512, 7, 7)), ('res5a_res5a_relu_0_split_0', (1, 512, 7, 7)), ('res5a_res5a_relu_0_split_1', (1, 512, 7, 7)), ('res5b_branch2a', (1, 512, 7, 7)), ('res5b_branch2b', (1, 512, 7, 7)), ('res5b', (1, 512, 7, 7)), ('fc2019-10-22_15-02-46', (1, 10, 1, 1)), ('prob', (1, 10, 1, 1))] set image transformer : About to compute detect the points : len(args) : 1 Inside predict_points step exec : nb paths : 1 treate image : temp/1739593538_3820514_987515173_91fa471b1a04f95b356afdbaf021f623.jpg size of numpy array img : 2408584 scale method : caffe/skimage size of numpy array img_scale : 2408584 (448, 448, 3) nb_h 8 nb_w 8 size of sub images : (224, 224, 3) size of caffe_input : 38535320 (64, 3, 224, 224) time to do the preprocess : 0.04130959510803223 time to do a prediction : 0.3368184566497803 dict_keys(['prob']) shape of output (64, 10, 1, 1) shape of the out_put heatmap (10, 8, 8) number of sub_photos vertical and horizon 8 8 size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) size of heatmap : (8,8) time spend for datou_step_exec : 1.6796002388000488 time spend to save output : 4.100799560546875e-05 total time spend for step 1 : 1.6796412467956543 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {987515173: [(987515173, 1982, 'Autre_Environement', 112, -1, 112, -1, 6.201242644388039e-12), (987515173, 1982, 'Autre_Environement', 144, -1, 112, -1, 2.4555718569629903e-11), (987515173, 1982, 'Autre_Environement', 176, -1, 112, -1, 1.065420907053749e-08), (987515173, 1982, 'Autre_Environement', 208, -1, 112, -1, 4.439928034116747e-07), (987515173, 1982, 'Autre_Environement', 240, -1, 112, -1, 1.928224264702294e-06), (987515173, 1982, 'Autre_Environement', 272, -1, 112, -1, 3.773228672798723e-05), (987515173, 1982, 'Autre_Environement', 304, -1, 112, -1, 0.00012182101636426523), (987515173, 1982, 'Autre_Environement', 336, -1, 112, -1, 2.9519149393308908e-05), (987515173, 1982, 'Autre_Environement', 112, -1, 144, -1, 2.3626132161780333e-08), (987515173, 1982, 'Autre_Environement', 144, -1, 144, -1, 2.2122582876704655e-08), (987515173, 1982, 'Autre_Environement', 176, -1, 144, -1, 1.380891490043723e-07), (987515173, 1982, 'Autre_Environement', 208, -1, 144, -1, 1.4728024098076276e-06), (987515173, 1982, 'Autre_Environement', 240, -1, 144, -1, 1.1252856893406715e-05), (987515173, 1982, 'Autre_Environement', 272, -1, 144, -1, 0.00015787853044457734), (987515173, 1982, 'Autre_Environement', 304, -1, 144, -1, 0.00044369074748829007), (987515173, 1982, 'Autre_Environement', 336, -1, 144, -1, 6.51986847515218e-05), (987515173, 1982, 'Autre_Environement', 112, -1, 176, -1, 1.3346793821256142e-06), (987515173, 1982, 'Autre_Environement', 144, -1, 176, -1, 1.6154597233253298e-06), (987515173, 1982, 'Autre_Environement', 176, -1, 176, -1, 2.52126437771949e-06), (987515173, 1982, 'Autre_Environement', 208, -1, 176, -1, 1.607582362339599e-06), (987515173, 1982, 'Autre_Environement', 240, -1, 176, -1, 6.256079814193072e-06), (987515173, 1982, 'Autre_Environement', 272, -1, 176, -1, 8.669427188578993e-05), (987515173, 1982, 'Autre_Environement', 304, -1, 176, -1, 0.0003259819932281971), (987515173, 1982, 'Autre_Environement', 336, -1, 176, -1, 0.00030532159144058824), (987515173, 1982, 'Autre_Environement', 112, -1, 208, -1, 1.859766234701965e-05), (987515173, 1982, 'Autre_Environement', 144, -1, 208, -1, 7.909812666184735e-06), (987515173, 1982, 'Autre_Environement', 176, -1, 208, -1, 2.703337486309465e-05), (987515173, 1982, 'Autre_Environement', 208, -1, 208, -1, 1.797188633645419e-05), (987515173, 1982, 'Autre_Environement', 240, -1, 208, -1, 2.340205173823051e-05), (987515173, 1982, 'Autre_Environement', 272, -1, 208, -1, 1.7080210454878397e-05), (987515173, 1982, 'Autre_Environement', 304, -1, 208, -1, 4.5393617256195284e-06), (987515173, 1982, 'Autre_Environement', 336, -1, 208, -1, 8.823730240692385e-06), (987515173, 1982, 'Autre_Environement', 112, -1, 240, -1, 6.0873890106449835e-06), (987515173, 1982, 'Autre_Environement', 144, -1, 240, -1, 1.6481017155456357e-06), (987515173, 1982, 'Autre_Environement', 176, -1, 240, -1, 1.9596311631175922e-06), (987515173, 1982, 'Autre_Environement', 208, -1, 240, -1, 1.4358250837176456e-06), (987515173, 1982, 'Autre_Environement', 240, -1, 240, -1, 7.847863344068173e-06), (987515173, 1982, 'Autre_Environement', 272, -1, 240, -1, 1.2854354281444103e-05), (987515173, 1982, 'Autre_Environement', 304, -1, 240, -1, 9.319219316239469e-06), (987515173, 1982, 'Autre_Environement', 336, -1, 240, -1, 2.173789107473567e-05), (987515173, 1982, 'Autre_Environement', 112, -1, 272, -1, 3.827996351901675e-06), (987515173, 1982, 'Autre_Environement', 144, -1, 272, -1, 2.5459034986852203e-06), (987515173, 1982, 'Autre_Environement', 176, -1, 272, -1, 2.964002078442718e-06), (987515173, 1982, 'Autre_Environement', 208, -1, 272, -1, 2.7624055292108096e-06), (987515173, 1982, 'Autre_Environement', 240, -1, 272, -1, 4.314684247219702e-06), (987515173, 1982, 'Autre_Environement', 272, -1, 272, -1, 8.188100764527917e-06), (987515173, 1982, 'Autre_Environement', 304, -1, 272, -1, 1.1513365279824939e-05), (987515173, 1982, 'Autre_Environement', 336, -1, 272, -1, 3.919992013834417e-05), (987515173, 1982, 'Autre_Environement', 112, -1, 304, -1, 1.2076626262569334e-05), (987515173, 1982, 'Autre_Environement', 144, -1, 304, -1, 1.580541538714897e-05), (987515173, 1982, 'Autre_Environement', 176, -1, 304, -1, 3.262147220084444e-05), (987515173, 1982, 'Autre_Environement', 208, -1, 304, -1, 0.00015461392467841506), (987515173, 1982, 'Autre_Environement', 240, -1, 304, -1, 0.00025944129447452724), (987515173, 1982, 'Autre_Environement', 272, -1, 304, -1, 0.00018891808576881886), (987515173, 1982, 'Autre_Environement', 304, -1, 304, -1, 0.00021348177688196301), (987515173, 1982, 'Autre_Environement', 336, -1, 304, -1, 0.00016421468171756715), (987515173, 1982, 'Autre_Environement', 112, -1, 336, -1, 4.562102276395308e-06), (987515173, 1982, 'Autre_Environement', 144, -1, 336, -1, 1.737157981551718e-05), (987515173, 1982, 'Autre_Environement', 176, -1, 336, -1, 4.9307040171697736e-05), (987515173, 1982, 'Autre_Environement', 208, -1, 336, -1, 0.00012131205585319549), (987515173, 1982, 'Autre_Environement', 240, -1, 336, -1, 0.0001964920957107097), (987515173, 1982, 'Autre_Environement', 272, -1, 336, -1, 0.0001875894085969776), (987515173, 1982, 'Autre_Environement', 304, -1, 336, -1, 0.0001224503357661888), (987515173, 1982, 'Autre_Environement', 336, -1, 336, -1, 0.000272762612439692), (987515173, 1982, 'Carton', 112, -1, 112, -1, 1.5594237368077302e-07), (987515173, 1982, 'Carton', 144, -1, 112, -1, 4.03490321332356e-06), (987515173, 1982, 'Carton', 176, -1, 112, -1, 7.050507065287093e-06), (987515173, 1982, 'Carton', 208, -1, 112, -1, 0.0008734787115827203), (987515173, 1982, 'Carton', 240, -1, 112, -1, 0.002665324369445443), (987515173, 1982, 'Carton', 272, -1, 112, -1, 0.0033774927724152803), (987515173, 1982, 'Carton', 304, -1, 112, -1, 0.03133474662899971), (987515173, 1982, 'Carton', 336, -1, 112, -1, 0.05591922625899315), (987515173, 1982, 'Carton', 112, -1, 144, -1, 0.00012453185627236962), (987515173, 1982, 'Carton', 144, -1, 144, -1, 0.00020878153736703098), (987515173, 1982, 'Carton', 176, -1, 144, -1, 0.00036824215203523636), (987515173, 1982, 'Carton', 208, -1, 144, -1, 0.006823350675404072), (987515173, 1982, 'Carton', 240, -1, 144, -1, 0.015806760638952255), (987515173, 1982, 'Carton', 272, -1, 144, -1, 0.009413366205990314), (987515173, 1982, 'Carton', 304, -1, 144, -1, 0.009732306934893131), (987515173, 1982, 'Carton', 336, -1, 144, -1, 0.022090550512075424), (987515173, 1982, 'Carton', 112, -1, 176, -1, 0.021923506632447243), (987515173, 1982, 'Carton', 144, -1, 176, -1, 0.1928650587797165), (987515173, 1982, 'Carton', 176, -1, 176, -1, 0.09631869941949844), (987515173, 1982, 'Carton', 208, -1, 176, -1, 0.12293310463428497), (987515173, 1982, 'Carton', 240, -1, 176, -1, 0.5334221720695496), (987515173, 1982, 'Carton', 272, -1, 176, -1, 0.461514413356781), (987515173, 1982, 'Carton', 304, -1, 176, -1, 0.7709495425224304), (987515173, 1982, 'Carton', 336, -1, 176, -1, 0.8661242127418518), (987515173, 1982, 'Carton', 112, -1, 208, -1, 0.8501125574111938), (987515173, 1982, 'Carton', 144, -1, 208, -1, 0.9845532178878784), (987515173, 1982, 'Carton', 176, -1, 208, -1, 0.9846786260604858), (987515173, 1982, 'Carton', 208, -1, 208, -1, 0.9919639825820923), (987515173, 1982, 'Carton', 240, -1, 208, -1, 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336, -1, 0.9911574125289917), (987515173, 1982, 'Carton', 208, -1, 336, -1, 0.9869130849838257), (987515173, 1982, 'Carton', 240, -1, 336, -1, 0.9086530804634094), (987515173, 1982, 'Carton', 272, -1, 336, -1, 0.945254385471344), (987515173, 1982, 'Carton', 304, -1, 336, -1, 0.9371597766876221), (987515173, 1982, 'Carton', 336, -1, 336, -1, 0.9808017611503601), (987515173, 1982, 'Kraft', 112, -1, 112, -1, 1.9213257651529148e-09), (987515173, 1982, 'Kraft', 144, -1, 112, -1, 1.7193304557849842e-08), (987515173, 1982, 'Kraft', 176, -1, 112, -1, 9.729694738780381e-07), (987515173, 1982, 'Kraft', 208, -1, 112, -1, 3.134548387606628e-05), (987515173, 1982, 'Kraft', 240, -1, 112, -1, 4.47794227511622e-05), (987515173, 1982, 'Kraft', 272, -1, 112, -1, 0.00020611593208741397), (987515173, 1982, 'Kraft', 304, -1, 112, -1, 0.0010777984280139208), (987515173, 1982, 'Kraft', 336, -1, 112, -1, 0.0008303183712996542), (987515173, 1982, 'Kraft', 112, -1, 144, -1, 2.614180812088307e-05), (987515173, 1982, 'Kraft', 144, -1, 144, -1, 6.987522283452563e-06), (987515173, 1982, 'Kraft', 176, -1, 144, -1, 3.6234364415577147e-06), (987515173, 1982, 'Kraft', 208, -1, 144, -1, 3.556925730663352e-05), (987515173, 1982, 'Kraft', 240, -1, 144, -1, 6.678198406007141e-05), (987515173, 1982, 'Kraft', 272, -1, 144, -1, 8.694791904417798e-05), (987515173, 1982, 'Kraft', 304, -1, 144, -1, 0.00012156800949014723), (987515173, 1982, 'Kraft', 336, -1, 144, -1, 0.00011242182517889887), (987515173, 1982, 'Kraft', 112, -1, 176, -1, 0.00049964664503932), (987515173, 1982, 'Kraft', 144, -1, 176, -1, 0.00012297308421693742), (987515173, 1982, 'Kraft', 176, -1, 176, -1, 9.067415521712974e-05), (987515173, 1982, 'Kraft', 208, -1, 176, -1, 5.1617065764730796e-05), (987515173, 1982, 'Kraft', 240, -1, 176, -1, 0.00011560472921701148), (987515173, 1982, 'Kraft', 272, -1, 176, -1, 0.0004329159273765981), (987515173, 1982, 'Kraft', 304, -1, 176, -1, 0.0009266496635973454), (987515173, 1982, 'Kraft', 336, -1, 176, -1, 0.001430021715350449), (987515173, 1982, 'Kraft', 112, -1, 208, -1, 6.89797816448845e-05), (987515173, 1982, 'Kraft', 144, -1, 208, -1, 1.8391705452813767e-05), (987515173, 1982, 'Kraft', 176, -1, 208, -1, 2.580556429165881e-05), (987515173, 1982, 'Kraft', 208, -1, 208, -1, 3.535637370077893e-05), (987515173, 1982, 'Kraft', 240, -1, 208, -1, 3.7422345485538244e-05), (987515173, 1982, 'Kraft', 272, -1, 208, -1, 8.627384522696957e-05), (987515173, 1982, 'Kraft', 304, -1, 208, -1, 0.00012375532242003828), (987515173, 1982, 'Kraft', 336, -1, 208, -1, 0.000390777422580868), (987515173, 1982, 'Kraft', 112, -1, 240, -1, 0.00030748845892958343), (987515173, 1982, 'Kraft', 144, -1, 240, -1, 4.161120887147263e-05), (987515173, 1982, 'Kraft', 176, -1, 240, -1, 1.2390174561005551e-05), (987515173, 1982, 'Kraft', 208, -1, 240, -1, 7.342318895098288e-06), (987515173, 1982, 'Kraft', 240, -1, 240, -1, 2.291596138093155e-05), (987515173, 1982, 'Kraft', 272, -1, 240, -1, 5.8708388678496704e-05), (987515173, 1982, 'Kraft', 304, -1, 240, -1, 6.573410064447671e-05), (987515173, 1982, 'Kraft', 336, -1, 240, -1, 0.00018887908663600683), (987515173, 1982, 'Kraft', 112, -1, 272, -1, 0.0014597137924283743), (987515173, 1982, 'Kraft', 144, -1, 272, -1, 0.0006877697305753827), (987515173, 1982, 'Kraft', 176, -1, 272, -1, 0.00027396934456191957), (987515173, 1982, 'Kraft', 208, -1, 272, -1, 4.369023008621298e-05), (987515173, 1982, 'Kraft', 240, -1, 272, -1, 3.3482920116512105e-05), (987515173, 1982, 'Kraft', 272, -1, 272, -1, 8.342007640749216e-05), (987515173, 1982, 'Kraft', 304, -1, 272, -1, 0.00011186183837708086), (987515173, 1982, 'Kraft', 336, -1, 272, -1, 0.00042295598541386425), (987515173, 1982, 'Kraft', 112, -1, 304, -1, 0.000993305817246437), (987515173, 1982, 'Kraft', 144, -1, 304, -1, 0.0009043306927196681), (987515173, 1982, 'Kraft', 176, -1, 304, -1, 0.0006093673873692751), (987515173, 1982, 'Kraft', 208, -1, 304, -1, 0.0010788424406200647), (987515173, 1982, 'Kraft', 240, -1, 304, -1, 0.0017843232490122318), (987515173, 1982, 'Kraft', 272, -1, 304, -1, 0.004718117415904999), (987515173, 1982, 'Kraft', 304, -1, 304, -1, 0.004706154111772776), (987515173, 1982, 'Kraft', 336, -1, 304, -1, 0.01250611525028944), (987515173, 1982, 'Kraft', 112, -1, 336, -1, 0.002184878336265683), (987515173, 1982, 'Kraft', 144, -1, 336, -1, 0.0057198540307581425), (987515173, 1982, 'Kraft', 176, -1, 336, -1, 0.0008303921204060316), (987515173, 1982, 'Kraft', 208, -1, 336, -1, 0.0012612574500963092), (987515173, 1982, 'Kraft', 240, -1, 336, -1, 0.007780404295772314), (987515173, 1982, 'Kraft', 272, -1, 336, -1, 0.012527309358119965), (987515173, 1982, 'Kraft', 304, -1, 336, -1, 0.01773754321038723), (987515173, 1982, 'Kraft', 336, -1, 336, -1, 0.007773573510348797), (987515173, 1982, 'Lointain_Papier_Magazine', 112, -1, 112, -1, 1.4818357652046643e-10), (987515173, 1982, 'Lointain_Papier_Magazine', 144, -1, 112, -1, 8.244277260871513e-09), (987515173, 1982, 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(987515173, 1982, 'autre_refus', 144, -1, 208, -1, 0.00018550622917246073), (987515173, 1982, 'autre_refus', 176, -1, 208, -1, 0.00031970313284546137), (987515173, 1982, 'autre_refus', 208, -1, 208, -1, 0.00035712640965357423), (987515173, 1982, 'autre_refus', 240, -1, 208, -1, 0.00019921947387047112), (987515173, 1982, 'autre_refus', 272, -1, 208, -1, 0.0002863132976926863), (987515173, 1982, 'autre_refus', 304, -1, 208, -1, 0.00020258076256141067), (987515173, 1982, 'autre_refus', 336, -1, 208, -1, 0.00024372876214329153), (987515173, 1982, 'autre_refus', 112, -1, 240, -1, 0.00023368319671135396), (987515173, 1982, 'autre_refus', 144, -1, 240, -1, 0.00010847260273294523), (987515173, 1982, 'autre_refus', 176, -1, 240, -1, 6.486287747975439e-05), (987515173, 1982, 'autre_refus', 208, -1, 240, -1, 2.5299121261923574e-05), (987515173, 1982, 'autre_refus', 240, -1, 240, -1, 7.271025970112532e-05), (987515173, 1982, 'autre_refus', 272, -1, 240, -1, 0.00014064658898860216), (987515173, 1982, 'autre_refus', 304, -1, 240, -1, 8.932968194130808e-05), (987515173, 1982, 'autre_refus', 336, -1, 240, -1, 8.273823914350942e-05), (987515173, 1982, 'autre_refus', 112, -1, 272, -1, 0.0002682320191524923), (987515173, 1982, 'autre_refus', 144, -1, 272, -1, 0.00011168434139108285), (987515173, 1982, 'autre_refus', 176, -1, 272, -1, 0.00012496428098529577), (987515173, 1982, 'autre_refus', 208, -1, 272, -1, 5.129153942107223e-05), (987515173, 1982, 'autre_refus', 240, -1, 272, -1, 2.9232160159153864e-05), (987515173, 1982, 'autre_refus', 272, -1, 272, -1, 4.266519317752682e-05), (987515173, 1982, 'autre_refus', 304, -1, 272, -1, 6.826691969763488e-05), (987515173, 1982, 'autre_refus', 336, -1, 272, -1, 0.00014267054211813956), (987515173, 1982, 'autre_refus', 112, -1, 304, -1, 0.00011523217835929245), (987515173, 1982, 'autre_refus', 144, -1, 304, -1, 0.00021758877846878022), (987515173, 1982, 'autre_refus', 176, -1, 304, -1, 0.0004254315863363445), (987515173, 1982, 'autre_refus', 208, -1, 304, -1, 0.00042774653411470354), (987515173, 1982, 'autre_refus', 240, -1, 304, -1, 6.586148811038584e-05), (987515173, 1982, 'autre_refus', 272, -1, 304, -1, 3.1909010431263596e-05), (987515173, 1982, 'autre_refus', 304, -1, 304, -1, 1.1675016139633954e-05), (987515173, 1982, 'autre_refus', 336, -1, 304, -1, 1.8850148990168236e-05), (987515173, 1982, 'autre_refus', 112, -1, 336, -1, 0.00024800034589134157), (987515173, 1982, 'autre_refus', 144, -1, 336, -1, 0.00047191878547891974), (987515173, 1982, 'autre_refus', 176, -1, 336, -1, 0.0003352028434164822), (987515173, 1982, 'autre_refus', 208, -1, 336, -1, 0.00023682057508267462), (987515173, 1982, 'autre_refus', 240, -1, 336, -1, 0.00010761930025182664), (987515173, 1982, 'autre_refus', 272, -1, 336, -1, 9.567140659783036e-05), (987515173, 1982, 'autre_refus', 304, -1, 336, -1, 0.00013081794895697385), (987515173, 1982, 'autre_refus', 336, -1, 336, -1, 0.0007339338771998882)]} ############################### TEST certificat_qualite_papier ################################ TEST certificat qualite papier Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Step 4442 tile have less inputs used (1) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 4441 detect_points is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 4443 count_percent_refus is not consistent : 4 used against 3 in the step definition ! Step 4444 send_mail_dechet have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : output 1 of step 4440 have datatype=1 whereas input 0 of step 4443 have datatype=2 WARNING : type of output 1 of step 4441 doesn't seem to be define in the database( WARNING : type of input 4 of step 4443 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : init_dechet, tile, detect_points, count_percent_refus, brightness, blur_detection, send_mail_dechet list_input_json : [] origin Catched exception ! Connect or reconnect ! We have 1 , BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 1.881223440170288 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 7 step1:init_dechet Sat Feb 15 05:25:42 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec debut step init detect dechets input : temp/1739593541_3820514_987321136_6a08497399a24a3041045c21475a90ea.jpg ON MODIFIE NB AVEC LE INPUT map photo id path extension : temp/1739593541_3820514_987321136_6a08497399a24a3041045c21475a90ea.jpg scale : 0.9481481481481482 FIN step init dechet Inside saveOutput : final : False verbose : False saveOutput not yet implemented for datou_step.type : init_dechet we use saveGeneral [987321136] Looping around the photos to save general results len do output : 1 /987321136Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('1848', None, None, None, None, None, None, None, None) ('1848', '1902940', '987321136', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 4 time used for this insertion : 0.4192330837249756 save_final save missing photos in datou_result : time spend for datou_step_exec : 0.00018715858459472656 time spend to save output : 0.4195749759674072 total time spend for step 1 : 0.41976213455200195 step2:tile Sat Feb 15 05:25:42 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure verbose : False param_json : {'token': '78d09a0790ec6ecbf119343125a81fdc', 'portfolio_name': 'tile_correct_upm', 'ETA': 86400, 'new_width': 1500, 'new_height': 20000, 'host': 'www.fotonower.com', 'protocol': 'https', 'photo_tile_type': 1522, 'option_bande': 'True'} type(crop_hashtag_type) : type(crop_hashtag_type_tiled) : We consider crop_hashtag_type is an integer ! map_chi_type_to_chi_type_cropped : {406: 410} map_filenames : {987321136: 'temp/1739593541_3820514_987321136_6a08497399a24a3041045c21475a90ea.jpg'} list_pids : 1 list_pids : 2 list_subpids to replace list_pids : 1 batch 1 Loaded 0 chid ids of type : 0 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=tile_correct_upm&access_token=78d09a0790ec6ecbf119343125a81fdc created feed_id_new_photos : 20582920 with name tile_correct_upm feed_id_new_photos : 20582920 filename : temp/1739593541_3820514_987321136_6a08497399a24a3041045c21475a90ea.jpg photo_id : 987321136 height_image_input : 439 width_image_input : 562 new_width : 1500 new_height : 20000 stride : 0 stride_relative : 0.1 chi to copy from the main photo to the tiled photo input_chi_for_this_image_as_chi : 0 list_bib_to_crops : 1 [(0, 562, 0, 439, 0)] new_crops_tiles : 1 crop_transformed : 0 batch 1 Loaded 1 chid ids of type : 1522 treat the image : temp/1739593541_3820514_987321136_6a08497399a24a3041045c21475a90ea.jpg , 0 before upload mediasElapsed time : 0.010165691375732422 About to upload 1 photos upload in portfolio : 20582920 400 uploaded one batch 0 Elapsed time : 0.028942108154296875 upload mediasElapsed time : 0.03917574882507324 ERROR in datou_step_exec, will save and exit ! 'temp/1739593541_3820514_987321136_6a08497399a24a3041045c21475a90ea_0.jpg' File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2329, in datou_exec output = datou_step_exec(sNext, args, cache, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2438, in datou_step_exec return pre_process.datou_step_exec_tile(param, json_param, args, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py", line 468, in datou_step_exec_tile map_new_photo_id_files = crop_and_record(photo_id, filename, new_crops_tiles, File "/home/admin/workarea/git/Velours/python/mtr/simple_image_editor/rotate_crop_and_images.py", line 1267, in crop_and_record new_photo_id = map_path_new_photo_id[path_photo_id_temp] [987321136, 987321136] begin to insert list_values into mtr_datou_result : length of list_values in save_final : 2 time used for this insertion : 0.012780904769897461 save_final ERROR in last step tile, 'temp/1739593541_3820514_987321136_6a08497399a24a3041045c21475a90ea_0.jpg' time spend for datou_step_exec : 8.48288631439209 time spend to save output : 0.019239425659179688 total time spend for step 1 : 8.50212574005127 Useless call to update_current_state caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 7 output : None probably due to empty image bug ERROR expected : {987321136: (-110, -0.39870825574700136, -5.392404060312662, 30.0, 61.64383561643836, {'carton': 3, 'Papier_Magazine': 7}, {'refus_total': 30.0, 'carton': 30.0, 'Papier_Magazine': 70.0}, {'refus_total': 61.64383561643836, 'carton': 61.64383561643836, 'Papier_Magazine': 38.35616438356164})} got : None ERROR certificat_qualite_papier FAILED ############################### TEST image_temperature_detection ################################ t Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : image_temperature_detection list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.1358788013458252 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:image_temperature_detection Sat Feb 15 05:25:51 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec inside step blanche_jaune_detection treat image : temp/1739593550_3820514_984484223_2e25dc219a9a57a9f85bcae482a80c35.jpg 984484223 1.004309911525615 time spend for datou_step_exec : 0.16662359237670898 time spend to save output : 8.416175842285156e-05 total time spend for step 1 : 0.16670775413513184 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {984484223: [(984484223, 1.004309911525615, 492630606)]} {984484223: [(984484223, 1.004309911525615, 492630606)]} ############################### TEST broca ################################ t Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : split_time_score list_input_json : [] origin We have 1 , we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 0.20366740226745605 About to test input to load Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:split_time_score Sat Feb 15 05:25:51 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec split portfolio by speed calcul order for each photo with time calcul time for a portfolio 2021-12-01 10:11:30 2021-12-01 10:11:32 2021-12-01 10:11:30 2021-12-01 10:11:34 2021-12-01 10:11:32 2021-12-01 10:11:40 2021-12-01 10:11:34 2021-12-01 10:12:17 2021-12-01 10:11:40 2021-12-01 10:12:24 2021-12-01 10:12:17 2021-12-01 10:12:27 2021-12-01 10:12:24 2021-12-01 10:12:29 2021-12-01 10:12:27 2021-12-01 10:12:56 2021-12-01 10:12:29 2021-12-01 10:13:04 2021-12-01 10:12:56 2021-12-01 10:13:13 2021-12-01 10:13:04 2021-12-01 10:13:04 distance 1.4513659170185111 2021-12-01 10:13:13 2021-12-01 10:13:22 2021-12-01 10:13:13 2021-12-01 10:13:30 2021-12-01 10:13:22 2021-12-01 10:16:14 2021-12-01 10:13:30 2021-12-01 10:13:30 distance 8.382409567451603 2021-12-01 10:16:14 2021-12-01 10:16:18 2021-12-01 10:16:14 2021-12-01 10:16:47 2021-12-01 10:16:18 2021-12-01 10:16:53 2021-12-01 10:16:47 2021-12-01 10:16:47 distance 8.03396608896571 2021-12-01 10:16:53 2021-12-01 10:16:57 2021-12-01 10:16:53 dict_time_useful: {0: [1098136690, 1098136784, 48.864288393888884, 2.19199505125, [datetime.datetime(2021, 12, 1, 10, 11, 30), datetime.datetime(2021, 12, 1, 10, 13, 4), 94]], 1: [1098136974, 1098137007, 48.86291258986111, 2.19361357125, [datetime.datetime(2021, 12, 1, 10, 16, 14), datetime.datetime(2021, 12, 1, 10, 16, 47), 33]]} get gps info of PAV SELECT id,Y_WGS84,X_WGS84 FROM MTRLabel.info_PAV; get gps info of PAV SELECT id,Y_WGS84,X_WGS84 FROM MTRLabel.info_PAV WHERE type_pav = "CS"; get gps info of PAV SELECT id,Y_WGS84,X_WGS84 FROM MTRLabel.info_PAV WHERE type_pav = "OM"; distance: RUEIL14CS [48.864288393888884, 2.19199505125] 16.57008455321128 time spend for datou_step_exec : 0.23489904403686523 time spend to save output : 0.00012493133544921875 total time spend for step 1 : 0.23502397537231445 caffe_path_current : About to save ! 0 After save, about to update current ! {15: [(20582921, 48.864288393888884, 2.19199505125, 10, 1064919752, [datetime.datetime(2021, 12, 1, 10, 11, 30), datetime.datetime(2021, 12, 1, 10, 13, 4), 94.0], 5205529)]} résultat du premier test BROCA : True True ############################### TEST crop_conditional ################################ t Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 1335 frcnn is not linked in the step_by_step architecture ! WARNING : step 1336 crop_condition is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! List Step Type Loaded in datou : frcnn, crop_condition list_input_json : [] origin We have 1 , BBBFBFBFBFFFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 6 ; length of list_pids : 6 ; length of list_args : 6 time to download the photos : 0.2940053939819336 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 2 step1:frcnn Sat Feb 15 05:25:52 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step Faster rcnn ! Inside try reload ! To loadFromThcl() model_param file didn't exist model_name : learn_piece_voiture_0808_v2 model_type : caffe_faster_rcnn list file need : ['caffemodel', 'test.prototxt'] file exist in s3 : ['caffemodel', 'test.prototxt'] file manque in s3 : [] local folder : /data/models_weight/learn_piece_voiture_0808_v2 /data/models_weight/learn_piece_voiture_0808_v2/caffemodel size_local : 350215080 size in s3 : 350215080 create time local : 2021-08-09 05:30:22 create time in s3 : 2021-08-06 19:24:16 caffemodel already exist and didn't need to update /data/models_weight/learn_piece_voiture_0808_v2/test.prototxt size_local : 7166 size in s3 : 7166 create time local : 2021-08-09 05:30:22 create time in s3 : 2021-08-06 19:24:16 test.prototxt already exist and didn't need to update prototxt : /data/models_weight/learn_piece_voiture_0808_v2/test.prototxt caffemodel : /data/models_weight/learn_piece_voiture_0808_v2/caffemodel Loaded network /data/models_weight/learn_piece_voiture_0808_v2/caffemodel About to compute detect_faster_rcnn : len(args) : 6 Inside frcnn step exec : nb paths : 6 image_path : temp/1739593551_3820514_950003812_3dbffe9f441f7d28d087f3e571769e74.jpg image_size (480, 614, 3) [[[ 44 44 44] [ 49 51 51] [ 42 44 44] ... [ 8 10 10] [ 8 10 10] [ 8 10 10]] [[ 43 43 43] [ 36 38 38] [ 39 41 41] ... [ 5 7 7] [ 5 7 7] [ 5 7 7]] [[ 70 70 70] [ 40 42 42] [ 41 43 43] ... [ 4 6 6] [ 4 6 6] [ 4 6 6]] ... [[103 101 101] [110 108 108] [ 61 59 59] ... [ 8 10 10] [ 8 10 10] [ 8 10 10]] [[ 98 96 96] [115 113 113] [ 73 71 71] ... [ 0 2 2] [ 11 13 13] [ 21 23 23]] [[ 92 90 90] [114 112 112] [ 87 82 83] ... [ 10 12 12] [ 18 20 20] [ 25 27 27]]] Detection took 0.136s for 300 object proposals image_path : temp/1739593551_3820514_950003696_11e3a77b72af4b332d366d98984039c7.jpg image_size (2160, 3264, 3) [[[168 165 161] [168 165 161] [168 165 161] ... [ 47 59 63] [ 48 60 64] [ 48 60 64]] [[168 165 161] [168 165 161] [168 165 161] ... [ 47 59 63] [ 47 59 63] [ 48 60 64]] [[168 165 161] [168 165 161] [168 165 161] ... [ 47 59 63] [ 47 59 63] [ 47 59 63]] ... [[167 164 160] [167 164 160] [167 164 160] ... [ 44 59 61] [ 44 59 61] [ 44 59 61]] [[165 162 158] [165 162 158] [165 162 158] ... [ 45 60 62] [ 45 60 62] [ 45 60 62]] [[164 161 157] [164 161 157] [164 161 157] ... [ 45 60 62] [ 45 60 62] [ 45 60 62]]] Detection took 0.619s for 300 object proposals image_path : temp/1739593551_3820514_950003695_22b4110c9a86b12e1542ec2bb977f6a8.jpg image_size (2160, 3840, 3) [[[111 118 91] [113 120 93] [115 120 93] ... [ 23 40 37] [ 23 40 37] [ 24 41 38]] [[111 118 91] [112 119 92] [115 120 93] ... [ 23 40 37] [ 23 40 37] [ 23 40 37]] [[113 118 91] [114 119 92] [115 120 93] ... [ 22 39 36] [ 23 40 37] [ 23 40 37]] ... [[120 125 94] [119 124 93] [118 123 92] ... [ 22 36 34] [ 22 36 34] [ 23 37 35]] [[119 124 93] [119 124 93] [118 123 92] ... [ 22 36 34] [ 22 36 34] [ 22 36 34]] [[118 123 91] [117 122 90] [117 122 91] ... [ 22 36 34] [ 22 36 34] [ 22 36 34]]] Detection took 0.532s for 300 object proposals image_path : temp/1739593551_3820514_926687666_a8bc8c1fad77748c62ca641ceb29ad9c.jpg image_size (480, 640, 3) [[[36 41 44] [36 41 44] [35 40 43] ... [ 8 10 10] [ 8 10 10] [ 8 10 10]] [[37 42 45] [36 41 44] [35 40 43] ... [ 5 7 7] [ 5 7 7] [ 5 7 7]] [[37 42 45] [36 41 44] [35 40 43] ... [ 3 5 5] [ 4 6 6] [ 4 6 6]] ... [[42 47 50] [41 46 49] [40 45 48] ... [ 8 10 10] [ 8 10 10] [ 8 10 10]] [[41 46 49] [41 46 49] [40 45 48] ... [ 0 2 2] [10 12 12] [22 24 24]] [[40 45 48] [40 45 48] [40 45 48] ... [10 12 12] [17 19 19] [26 28 28]]] Detection took 0.060s for 300 object proposals image_path : temp/1739593551_3820514_950003838_e480bc28e6ceabc2f5995246a6af6b46.jpg image_size (294, 285, 3) [[[ 29 29 29] [ 29 29 29] [ 30 30 30] ... [182 172 165] [141 131 124] [103 94 90]] [[ 29 29 29] [ 29 29 29] [ 31 31 31] ... [231 220 212] [202 193 184] [164 154 147]] [[ 30 30 30] [ 27 27 27] [ 26 26 26] ... [223 211 199] [229 219 209] [228 217 209]] ... [[ 22 27 25] [ 16 21 19] [ 11 16 14] ... [166 145 123] [168 147 125] [170 149 127]] [[ 20 25 23] [ 17 22 20] [ 15 20 18] ... [163 142 120] [165 144 122] [166 145 123]] [[ 13 18 16] [ 17 22 20] [ 20 25 23] ... [162 141 119] [163 142 120] [163 142 121]]] Detection took 0.031s for 300 object proposals image_path : temp/1739593551_3820514_950003813_e28be02dfcce79cce594a390a9911a0a.jpg image_size (254, 229, 3) [[[202 190 186] [205 193 189] [205 194 190] ... [ 81 70 56] [ 80 69 55] [ 78 67 53]] [[198 187 183] [200 189 185] [198 189 185] ... [ 50 41 28] [ 44 36 23] [ 45 36 23]] [[192 187 184] [191 186 183] [191 186 183] ... [ 36 30 23] [ 32 29 21] [ 33 27 20]] ... [[187 186 190] [186 185 189] [188 184 189] ... [ 43 38 35] [ 37 33 28] [ 33 28 25]] [[184 185 189] [183 184 188] [184 183 187] ... [ 28 23 22] [ 29 24 21] [ 33 28 27]] [[181 185 186] [180 184 185] [182 184 185] ... [ 23 15 16] [ 22 14 14] [ 24 16 17]]] Detection took 0.028s for 300 object proposals len de result frcnn : 6 time spend for datou_step_exec : 3.820505142211914 time spend to save output : 0.0009238719940185547 total time spend for step 1 : 3.8214290142059326 step2:crop_condition Sat Feb 15 05:25:55 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Loading chi in step crop with photo_hashtag_type : 757 Loading chi in step crop for subpids : 6 ! batch 1 Loaded 32 chid ids of type : 757 begin to crop the class : phare param for this class : {'margin_type': 'margin', 'margin_value': 300, 'feed_id_new_photos': 1097966} filtre for class : phare hashtag_id of this class : 492624020 WARNING : margin is only used for type bib ! map_result returned by crop_photo_return_map_crop : length : 3 About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! we have finished the crop for the class : phare begin to crop the class : aile-avant param for this class : {} filtre for class : aile-avant hashtag_id of this class : 2106233860 WARNING : margin is only used for type bib ! now we use margin_relative for the photo_id : 950003812 now we use margin_relative for the photo_id : 926687666 map_result returned by crop_photo_return_map_crop : length : 2 About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! we have finished the crop for the class : aile-avant time spend for datou_step_exec : 1.0694305896759033 time spend to save output : 5.078315734863281e-05 total time spend for step 2 : 1.069481372833252 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 2 output : {1071808957: [950003812, 'temp/1739593551_3820514_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713647_0.jpg', (318, 489, 264, 310)], 1071808960: [950003812, 'temp/1739593551_3820514_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713648_0.jpg', (261, 408, 234, 331)], 1071808962: [926687666, 'temp/1739593551_3820514_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713621_0.jpg', (326, 477, 251, 312)], 1071808966: [950003812, 'temp/1739593551_3820514_950003812_3dbffe9f441f7d28d087f3e571769e74_bib_crop_1655713634_0.jpg', (133, 305, 146, 344)], 1071808969: [926687666, 'temp/1739593551_3820514_926687666_a8bc8c1fad77748c62ca641ceb29ad9c_bib_crop_1655713607_0.jpg', (161, 330, 149, 343)]} ############################### TEST image_blanchir ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : image_blanchir list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.22034955024719238 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! WARNING : we have an input that is not a photo, we should get rid of it Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:image_blanchir Sat Feb 15 05:25:57 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec inside step blanchir_image https://marlene.fotonower.com/api/v1/secured/portfolio/new?access_token=78d09a0790ec6ecbf119343125a81fdc feed_id_new_photos:20582923 treat image : temp/1739593556_3820514_990111206_7ca22c7e68dd0a10509c7987af0cf549.png blanchir func Result OK ! time spend for datou_step_exec : 6.775500535964966 time spend to save output : 6.67572021484375e-06 total time spend for step 1 : 6.775507211685181 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False sauvegarde pour la step blanchir_image begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [[1818, 0, 990111206, 1, 1, 1, None, 1, None]] time used for this insertion : 0.013408422470092773 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : [(990111206, '1337814578', 0, 300, 0, 381, 1, 1, 'blanc')] [(990111206, '1337814578', 0, 300, 0, 381, 1, 1, 'blanc')] ############################### TEST darker_image ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : darker_image list_input_json : [] origin We have 1 , BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.1431138515472412 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:darker_image Sat Feb 15 05:26:04 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec dans la step darker batch 1 Loaded 7 chid ids of type : 2228 +WARNING : Unexpected points, we should remove this data for chi_id : 1753484977, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484978, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484979, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484980, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484981, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484982, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484983, for now we just ignore these empty polygon points treat image : temp/1739593564_3820514_989962950_4d2e56be59e275c3d57b085a836be0ba.jpg Result OK ! batch 1 Loaded 7 chid ids of type : 2228 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! crops sauvegardes time spend for datou_step_exec : 7.5008745193481445 time spend to save output : 3.600120544433594e-05 total time spend for step 1 : 7.500910520553589 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False sauvegarde pour la step blanchir_image begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [[2085, 0, 989962950, 1, 1, 1, None, 1, None]] time used for this insertion : 0.023470401763916016 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : [(989962950, '1337814579', 0, 897, 0, 1431, 1, 1, 'darker')] [(989962950, '1337814579', 0, 897, 0, 1431, 1, 1, 'darker')] batch 1 Loaded 7 chid ids of type : 2228 ############################### TEST img_aug ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : data_aug list_input_json : [] origin We have 1 , BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.09843873977661133 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:data_aug Sat Feb 15 05:26:12 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec numpy.version est ancienne, on utilise l'ancien bit generator numpy.version est ancienne, on utilise l'ancien bit generator batch 1 Loaded 7 chid ids of type : 2228 +WARNING : Unexpected points, we should remove this data for chi_id : 1753484977, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484978, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484979, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484980, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484981, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484982, for now we just ignore these empty polygon points +WARNING : Unexpected points, we should remove this data for chi_id : 1753484983, for now we just ignore these empty polygon points on traite des points Result OK ! batch 1 Loaded 7 chid ids of type : 2260 ERROR missing MTRPhoto.crop_hashtag_ids : 492774966 on photo_id : 1337814580 ERROR missing MTRPhoto.crop_hashtag_ids : 492774966 on photo_id : 1337814580 ERROR missing MTRPhoto.crop_hashtag_ids : 492725882 on photo_id : 1337814580 ERROR missing MTRPhoto.crop_hashtag_ids : 492725882 on photo_id : 1337814580 ERROR missing MTRPhoto.crop_hashtag_ids : 492668766 on photo_id : 1337814580 ERROR missing MTRPhoto.crop_hashtag_ids : 492668766 on photo_id : 1337814580 ERROR missing MTRPhoto.crop_hashtag_ids : 492668766 on photo_id : 1337814580 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! photo_uploade augmentation faite pour la photo : 989962950 time spend for datou_step_exec : 7.582470655441284 time spend to save output : 4.172325134277344e-05 total time spend for step 1 : 7.582512378692627 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False sauvegarde pour la step blanchir_image begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [[2041, 0, 989962950, 1, 1, 1, None, 1, None]] time used for this insertion : 0.11778092384338379 save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : [(989962950, 1337814580, 0, 1431, 0, 897, 1, 1, 'img_aug')] [(989962950, 1337814580, 0, 1431, 0, 897, 1, 1, 'img_aug')] batch 1 Loaded 7 chid ids of type : 2260 ############################### TEST rubbia ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : split_time_score list_input_json : [] origin We have 1 , we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 7.7997355461120605 About to test input to load Calling datou_exec Inside datou_exec : verbose : False we use local cache db, so we are in local job, but when commit will be implemented for local cache db, we could again use save number of steps : 1 step1:split_time_score Sat Feb 15 05:26:28 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec begin split time score 2022-04-13 10:29:59 0 TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('05', 2), ('07', 25), ('06', 1), ('08', 96), ('09', 44), ('10', 64)) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {1: 188, 2: 36, 3: 8} 07092021 4599398 Nombre de photos uploadées : 232 / 23040 (1%) 07092021 4599398 Nombre de photos taguées (types de déchets): 232 / 232 (100%) 07092021 4599398 Nombre de photos taguées (volume) : 232 / 232 (100%) elapsed_time : load_data_split_time_score 6.198883056640625e-06 elapsed_time : order_list_meta_photo_and_scores 0.00024247169494628906 elapsed_time : fill_and_build_computed_from_old_data 0.02816605567932129 elapsed_time : insert_dashboard_record_day_entry 0.029386520385742188 Creating list_photo_total elapsed_time : select_descriptors 17.27008628845215 07092021 4599398 Nombre de photos avec descriptors (type 3963) : 232 / 232 (100%) ERROR : Hum hum, what can we do for different size of descriptors (ignore the difference ) : 0 vs 2048 photo_id : 1049293230 photo_id_prec : 0 0:00:00|ON:0:27:28.999934|OFF:1:46:59.999878|ON:0:00:20.000007|OFF:0:01:51.000162|ON:0:12:18.999909|OFF:0:01:01.000055|ON:0:08:50.000116|OFF:0:00:09.999867|ON:0:00:19.999899|OFF:0:00:09.000058|ON:0:00:29.999860|OFF:0:01:40.000249|ON:0:00:30.999931|OFF:0:07:40.000107|ON:0:00:28.999981|OFF:0:00:09.999968|ON:0:00:10.999986|OFF:0:08:09.999919|ON:0:00:40.000176|OFF:0:01:08.999784|ON:0:00:11.000245|OFF:0:00:39.999921|ON:0:00:19.000004|OFF:0:06:31.000039|ON:0:02:09.999929|OFF:0:01:40.000021|ON:0:00:39.000031|OFF:0:07:10.999966|ON:0:12:30.000101|OFF:0:00:18.999765|ON:0:00:39.999946|OFF:0:00:11.000212|ON:0:00:29.999851|OFF:0:00:20.000150|ON:0:00:30.000042|OFF:0:00:18.999771|ON:0:07:31.000243|OFF:0:00:09.999942|ON:0:00:08.999822|OFF:0:00:11.000172|ON:0:00:39.999914|OFF:0:00:20|ON:0:31:10.000147|OFF:0:12:18.999857|ON:0:01:39.999950|OFF:0:00:19.999947|ON:0:00:21.000213|OFF:0:00:28.999911|ON:0:00:21.000117|OFF:0:00:40.000020|ON:0:10:58.999762|OFF:0:00:41.000023|ON:0:00:09.000008|OFF:0:00:21.000234|ON:0:00:29.999765|OFF:0:00:28.999920|ON:0:00:21.000174|OFF:0:00:30.000078|ON:0:00:29.999938|OFF:0:00:29.999871|ON:0:00:08.999965|OFF:0:09:31.000234|ON:0:00:09.999916|OFF:0:00:20.000049|ON:0:04:09.999926|OFF:0:01:09.000014|ON:0:02:00.999957|OFF:0:00:08.999951|ON:0:00:21.000053|OFF:0:00:18.999927|ON:0:00:39.999997|OFF:0:00:30.000158|ON: 07092021 Removing 115 photos because of the 'same image' condition Total on : 7859.999814999999 list_time_on Total off : 10509.0002 list_time_off dist_desc begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 232 time used for this insertion : 0.09192633628845215 photos_removed : len 115 elapsed_time : remove_photo_duplicate 0.17540335655212402 Creating list_photo_total XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX elapsed_time : count_sum_diff_and_build_graph 0.07010817527770996 Total photos : 232 ..can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info ....can't find max_score_info .....can't find max_score_info .can't find max_score_info ...Change port : 10 hashtag : 2107750911 photo_id =1049308384 : rungis_plastique_fonce ..can't find max_score_info ...can't find max_score_info ....can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info ....can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info ....can't find max_score_info ..can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .....can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info ..can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info ...can't find max_score_info .can't find max_score_info .can't find max_score_info .....Change port : 25 hashtag : 2107750908 photo_id =1049311795 : rungis_papier ..can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info ...Change port : 4 hashtag : 2107750911 photo_id =1049311961 : rungis_plastique_fonce .can't find max_score_info .can't find max_score_info .can't find max_score_info .Change port : 1 hashtag : 2107750908 photo_id =1049312208 : rungis_papier .....Change port : 5 hashtag : 2107750911 photo_id =1049312420 : rungis_plastique_fonce .Change port : 1 hashtag : 2107750908 photo_id =1049312422 : rungis_papier ..can't find max_score_info .can't find max_score_info .Change port : 2 hashtag : 2107750911 photo_id =1049312438 : rungis_plastique_fonce ....can't find max_score_info ...can't find max_score_info .can't find max_score_info ....can't find max_score_info .can't find max_score_info ....Change port : 12 hashtag : 2107750908 photo_id =1049312556 : rungis_papier .can't find max_score_info ..can't find max_score_info .....can't find max_score_info .can't find max_score_info ...Change port : 8 hashtag : 2107750911 photo_id =1049312984 : rungis_plastique_fonce ...can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .........can't find max_score_info .can't find max_score_info ...can't find max_score_info .can't find max_score_info ...can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info ...can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .Change port : 17 hashtag : 2107751280 photo_id =1049317359 : rungis_aluminium .can't find max_score_info .can't find max_score_info ....can't find max_score_info .can't find max_score_info .can't find max_score_info ...can't find max_score_info .can't find max_score_info .can't find max_score_info ...Change port : 8 hashtag : 2107750913 photo_id =1049317524 : rungis_tetrapak .can't find max_score_info .can't find max_score_info .can't find max_score_info ..can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info .Change port : 2 hashtag : 2107750911 photo_id =1049318212 : rungis_plastique_fonce .can't find max_score_info .can't find max_score_info ...can't find max_score_info .can't find max_score_info .can't find max_score_info .can't find max_score_info ..........Change port : 12 hashtag : 2107750908 photo_id =1049318287 : rungis_papier ...can't find max_score_info ..Change port : 4 hashtag : 2107750911 photo_id =1049318294 : rungis_plastique_fonce .can't find max_score_info .can't find max_score_info .....can't find max_score_info .can't find max_score_info .can't find max_score_info . Total photos : 232 Number of lists : 15 counter photos in port : 117 hashtag : rungis_aluminium(2107751280) : 8 photos in 1 portfolios ! hashtag : rungis_carton(2107750907) : 0 photos in 0 portfolios ! hashtag : rungis_papier(2107750908) : 33 photos in 6 portfolios ! hashtag : rungis_plastique_clair(2107750909) : 0 photos in 0 portfolios ! hashtag : rungis_plastique_dur(2107750910) : 0 photos in 0 portfolios ! hashtag : rungis_plastique_fonce(2107750911) : 74 photos in 7 portfolios ! hashtag : rungis_tapis_vide(2107750912) : 0 photos in 0 portfolios ! hashtag : rungis_tetrapak(2107750913) : 2 photos in 1 portfolios ! elapsed_time : group_photo_by_moyenne_exp 0.013957738876342773 elapsed_time : compute_and_correct_tag_with_moyenne_mobile 4.5299530029296875e-06 today str has not a value , we define it as the date of the first image todaystr_first : 07092021 attention , prev_timestamp is 0 , we do nothing *******o** BIG TIME 550.0000100135803 (11.000229120254517, 2, 0, 0, 0.979349, 0, 0, 0, 0, 0, 0.8199999980926513, 0.0012, 0.0008999778032302856, 2.9, 0.11100016188621521, -0.0) on 3 1049307693 2021-09-07 07:45:54.010041 id_data : 12 * BIG TIME 168.99982810020447 (11.000229120254517, 2, 0, 0, 0.979349, 0, 0, 0, 0, 0, 0.8199999980926513, 0.0012, 0.0008999778032302856, 2.9, 0.11100016188621521, -0.0) on 3 1049308235 2021-09-07 07:48:43.009869 id_data : 13 ** BIG TIME 499.9998118877411 (191.00026988983154, 2, 0, 0, 0.93498826, 0, 0, 0, 0, 0, 0.9018999995946884, 0.002, 0.002999984407424927, 2.9, 0.019000051021575926, -0.01666705330212911) on 7 1049309345 2021-09-07 07:58:43.009858 id_data : 20 * BIG TIME 371.0001440048218 (271.00081276893616, 5, 0.24365342, 0, 0, 0, 0, 0.38418204, 0, 0.34177557, 0.9720000085830689, 0.0041, 0.014999971222877502, 2.9, 0.061000473976135255, -0.2516670016447703) on 15 1049310132 2021-09-07 08:09:54.010082 id_data : 51 * BIG TIME 461.0001001358032 (301.0006546974182, 0, 0.5752453, 0, 0, 0, 0, 0, 0, 0, 1.0228999980926514, 0.0056, 0.02589997522830963, 2.9, 0.009999968051910401, -0.0) on 18 1049310905 2021-09-07 08:18:54.009936 id_data : 60 * BIG TIME 370.0001759529114 (359.0003435611725, 5, 0, 0, 0, 0, 0, 0.85983855, 0, 0, 1.0898999773979188, 0.0078, 0.04109999623298645, 2.9, 0.008999762058258056, -0.0) on 24 1049311767 2021-09-07 08:28:24.010105 id_data : 81 *** BIG TIME 411.0001149177551 (557.9999935626984, 2, 0, 0, 0.66983944, 0, 0, 0, 0, 0, 1.1558999848842622, 0.0094, 0.050199996829032895, 2.9, 0.00900000500679016, -0.0) on 32 1049312208 2021-09-07 08:40:04.010052 id_data : 97 * BIG TIME 549.9999330043793 (557.9999935626984, 2, 0, 0, 0.66983944, 0, 0, 0, 0, 0, 1.1558999848842622, 0.0094, 0.050199996829032895, 2.9, 0.00900000500679016, -0.0) on 32 1049312363 2021-09-07 08:49:14.009985 id_data : 98 ** BIG TIME 168.99987387657166 (867.0004575252533, 2, 0, 0, 0.5498895, 0, 0, 0, 0, 0.29987606, 1.293000004196167, 0.0123, 0.06009994525909424, 0.9, 0.011000201940536499, -0.0) on 49 1049312508 2021-09-07 08:58:23.009966 id_data : 123 * BIG TIME 259.99999809265137 (867.0004575252533, 2, 0, 0, 0.5498895, 0, 0, 0, 0, 0.29987606, 1.293000004196167, 0.0123, 0.06009994525909424, 0.9, 0.011000201940536499, -0.0) on 49 1049312556 2021-09-07 09:02:43.009964 id_data : 124 * BIG TIME 190.00016593933105 (929.000762462616, 5, 0, 0, 0.44379362, 0, 0, 0.54574114, 0, 0, 1.3459999933004378, 0.0135, 0.06409994735717774, 2.9, 0.009999895095825195, -0.0) on 55 1049312803 2021-09-07 09:07:34.010149 id_data : 135 * BIG TIME 180.0000081062317 (929.000762462616, 5, 0, 0, 0.44379362, 0, 0, 0.54574114, 0, 0, 1.3459999933004378, 0.0135, 0.06409994735717774, 2.9, 0.009999895095825195, -0.0) on 55 1049312984 2021-09-07 09:10:34.010157 id_data : 136 * BIG TIME 1480.0000269412994 (939.0006575584412, 5, 0, 0, 0.2945285, 0, 0, 0.48689777, 0, 0.20073189, 1.3838999820947646, 0.0138, 0.06409994735717774, 2.9, 0.018999608993530273, -0.6316664799054463) on 56 1049316209 2021-09-07 09:35:23.009898 id_data : 138 * BIG TIME 668.9998891353607 (939.0006575584412, 5, 0, 0, 0.2945285, 0, 0, 0.48689777, 0, 0.20073189, 1.3838999820947646, 0.0138, 0.06409994735717774, 2.9, 0.018999608993530273, -0.6316664799054463) on 56 1049316332 2021-09-07 09:47:53.009987 id_data : 147 * BIG TIME 649.9999890327454 (1086.000019311905, 5, 0, 0, 0, 0, 0, 0.69907516, 0, 0.23055789, 1.6300000094890594, 0.0168, 0.08039999685287476, 2.9, 0.01100021505355835, -0.0) on 68 1049317197 2021-09-07 10:02:34.010134 id_data : 168 * BIG TIME 540.0001981258392 (1189.0002081394196, 0, 0.8074409, 0, 0, 0, 0, 0, 0, 0, 1.7199999867916107, 0.0194, 0.09519999706745148, 2.9, 0.009999808073043823, -0.0) on 78 1049318212 2021-09-07 10:16:24.010117 id_data : 198 * BIG TIME 190.00007104873657 (1199.0000162124634, 5, 0, 0.22708784, 0, 0, 0, 0.7244179, 0, 0, 1.781000003194809, 0.0202, 0.10109996955394746, 2.9, 0.011000241041183472, -0.0) on 79 1049318219 2021-09-07 10:20:04.010153 id_data : 202 **Count Time bigger than 30s : 31 #Number Photos for regression : {'07092021': {2107751280: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 80.99965000152588, 2107751017: 0}, 2107750907: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 49.000049114227295, 2107751017: 0}, 2107750908: {2107751013: 0, 2107751014: 11.000201940536499, 2107751015: 0, 2107751016: 534.9997780323029, 2107751017: 0}, 2107750909: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 2107750910: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 31.000057697296143, 2107751017: 0}, 2107750911: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 564.0013737678528, 2107751017: 19.999656200408936}, 2107750912: {2107751013: 0, 2107751014: 0, 2107751015: 0, 2107751016: 0, 2107751017: 0}, 2107750913: {2107751013: 0, 2107751014: 8.999944925308228, 2107751015: 0, 2107751016: 89.99986672401428, 2107751017: 9.999994993209839}}} 07092021|rungis_aluminium, 05102018_papier_non_papier_dense:0 07092021|rungis_aluminium, 05102018_papier_non_papier_peu_dense:0 07092021|rungis_aluminium, 05102018_papier_non_papier_presque_vide:0 07092021|rungis_aluminium, 05102018_papier_non_papier_tres_dense:80.99965000152588 07092021|rungis_aluminium, 05102018_papier_non_papier_tres_peu_dense:0 07092021|rungis_carton, 05102018_papier_non_papier_dense:0 07092021|rungis_carton, 05102018_papier_non_papier_peu_dense:0 07092021|rungis_carton, 05102018_papier_non_papier_presque_vide:0 07092021|rungis_carton, 05102018_papier_non_papier_tres_dense:49.000049114227295 07092021|rungis_carton, 05102018_papier_non_papier_tres_peu_dense:0 07092021|rungis_papier, 05102018_papier_non_papier_dense:0 07092021|rungis_papier, 05102018_papier_non_papier_peu_dense:11.000201940536499 07092021|rungis_papier, 05102018_papier_non_papier_presque_vide:0 07092021|rungis_papier, 05102018_papier_non_papier_tres_dense:534.9997780323029 07092021|rungis_papier, 05102018_papier_non_papier_tres_peu_dense:0 07092021|rungis_plastique_clair, 05102018_papier_non_papier_dense:0 07092021|rungis_plastique_clair, 05102018_papier_non_papier_peu_dense:0 07092021|rungis_plastique_clair, 05102018_papier_non_papier_presque_vide:0 07092021|rungis_plastique_clair, 05102018_papier_non_papier_tres_dense:0 07092021|rungis_plastique_clair, 05102018_papier_non_papier_tres_peu_dense:0 07092021|rungis_plastique_dur, 05102018_papier_non_papier_dense:0 07092021|rungis_plastique_dur, 05102018_papier_non_papier_peu_dense:0 07092021|rungis_plastique_dur, 05102018_papier_non_papier_presque_vide:0 07092021|rungis_plastique_dur, 05102018_papier_non_papier_tres_dense:31.000057697296143 07092021|rungis_plastique_dur, 05102018_papier_non_papier_tres_peu_dense:0 07092021|rungis_plastique_fonce, 05102018_papier_non_papier_dense:0 07092021|rungis_plastique_fonce, 05102018_papier_non_papier_peu_dense:0 07092021|rungis_plastique_fonce, 05102018_papier_non_papier_presque_vide:0 07092021|rungis_plastique_fonce, 05102018_papier_non_papier_tres_dense:564.0013737678528 07092021|rungis_plastique_fonce, 05102018_papier_non_papier_tres_peu_dense:19.999656200408936 07092021|rungis_tapis_vide, 05102018_papier_non_papier_dense:0 07092021|rungis_tapis_vide, 05102018_papier_non_papier_peu_dense:0 07092021|rungis_tapis_vide, 05102018_papier_non_papier_presque_vide:0 07092021|rungis_tapis_vide, 05102018_papier_non_papier_tres_dense:0 07092021|rungis_tapis_vide, 05102018_papier_non_papier_tres_peu_dense:0 07092021|rungis_tetrapak, 05102018_papier_non_papier_dense:0 07092021|rungis_tetrapak, 05102018_papier_non_papier_peu_dense:8.999944925308228 07092021|rungis_tetrapak, 05102018_papier_non_papier_presque_vide:0 07092021|rungis_tetrapak, 05102018_papier_non_papier_tres_dense:89.99986672401428 07092021|rungis_tetrapak, 05102018_papier_non_papier_tres_peu_dense:9.999994993209839 #Number Photos for regression amount gros magasin papier (time_diff then nb_photo) : We have not displayed the number of photos removed for one material since Rungis_Papier wasn't in the thcl used ! 07092021_time_diff_distrib Number amount portfolio for this type of dechet : aluminium 8 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=07092021_aluminium_05102018_papier_non_papier_tres_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20582924 with name like 07092021_aluminium_05102018_papier_non_papier_tres_dense Number amount portfolio for this type of dechet : carton 6 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=07092021_carton_05102018_papier_non_papier_tres_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20582925 with name like 07092021_carton_05102018_papier_non_papier_tres_dense Number amount portfolio for this type of dechet : papier 29 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=07092021_papier_05102018_papier_non_papier_peu_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20582926 with name like 07092021_papier_05102018_papier_non_papier_peu_dense https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=07092021_papier_05102018_papier_non_papier_tres_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20582927 with name like 07092021_papier_05102018_papier_non_papier_tres_dense Number amount portfolio for this type of dechet : plastique_clair 0 Number amount portfolio for this type of dechet : plastique_dur 2 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=07092021_plastique_dur_05102018_papier_non_papier_tres_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20582928 with name like 07092021_plastique_dur_05102018_papier_non_papier_tres_dense Number amount portfolio for this type of dechet : plastique_fonce 42 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=07092021_plastique_fonce_05102018_papier_non_papier_tres_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20582929 with name like 07092021_plastique_fonce_05102018_papier_non_papier_tres_dense https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=07092021_plastique_fonce_05102018_papier_non_papier_tres_peu_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20582930 with name like 07092021_plastique_fonce_05102018_papier_non_papier_tres_peu_dense Number amount portfolio for this type of dechet : tapis_vide 0 Number amount portfolio for this type of dechet : tetrapak 11 https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=07092021_tetrapak_05102018_papier_non_papier_peu_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20582931 with name like 07092021_tetrapak_05102018_papier_non_papier_peu_dense https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=07092021_tetrapak_05102018_papier_non_papier_tres_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20582932 with name like 07092021_tetrapak_05102018_papier_non_papier_tres_dense https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=07092021_tetrapak_05102018_papier_non_papier_tres_peu_dense&access_token=0fc1cdda0f63f39f777d9cb33b1aa204 Created to study and clean : 20582933 with name like 07092021_tetrapak_05102018_papier_non_papier_tres_peu_dense NUMBER BATCH : 15 list_ponderation used : [0.001, 0.001, 0.001, 0.001, 0.001] , list_hashtag_class_create_as_list : ['pcnc', 'pcm', 'jrm', 'flux_dev', 'pehd_pp', 'papier', 'carton', 'plastique_dur', 'plastique_clair', 'pet_clair', 'plastique_fonce', 'tetrapak', 'aluminium', 'carton_emr', 'grands_cartons', 'gros_de_magasin', 'tapis_vide'] We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_papier:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 10, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 191.00026988983154, 3: 0, 4: 0}, 'duration': 9008.999763965607, 'nb_balles_papier': 0.19500026988983155, 'begin_time_port': 'image_07092021_05_20_04_010050m0.jpg 0.001 for time 1, id_amount 3 this amount prod time diff : 0.001'} Production hashtag (incorrect ponderation at 20-10-18) : 0.19500026988983155 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_plastique_fonce:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 25, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 225.99965572357178, 3: 0, 4: 0}, 'duration': 2329.999878883362, 'nb_balles_papier': 0.2299996557235718, 'begin_time_port': 'image_07092021_07_50_23_010046m0.jpg 0.010000231981277466 for time 10.000231981277466, id_amount 3 this amount prod time diff : 0.010000231981277466'} Production hashtag (incorrect ponderation at 20-10-18) : 0.2299996557235718 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_papier:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 4, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 141.00006794929504, 3: 0, 4: 0}, 'duration': 189.9997718334198, 'nb_balles_papier': 0.14100006794929504, 'begin_time_port': 'image_07092021_08_29_24_010122m0.jpg 0.011000197172164917 for time 11.000197172164917, id_amount 3 this amount prod time diff : 0.011000197172164917'} Production hashtag (incorrect ponderation at 20-10-18) : 0.14100006794929504 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_plastique_fonce:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 1, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 9.000005006790161, 3: 0, 4: 0}, 'duration': 0, 'nb_balles_papier': 0.00900000500679016, 'begin_time_port': 'image'} Production hashtag (incorrect ponderation at 20-10-18) : 0.00900000500679016 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_papier:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 5, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 148.99991703033447, 3: 0, 4: 0}, 'duration': 698.9998500347137, 'nb_balles_papier': 0.15099991703033447, 'begin_time_port': 'image_07092021_08_40_04_010052m0.jpg 0.001 for time 1, id_amount 3 this amount prod time diff : 0.001'} Production hashtag (incorrect ponderation at 20-10-18) : 0.15099991703033447 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_plastique_fonce:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 1, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 11.000216960906982, 3: 0, 4: 0}, 'duration': 0, 'nb_balles_papier': 0.011000216960906983, 'begin_time_port': 'image'} Production hashtag (incorrect ponderation at 20-10-18) : 0.011000216960906983 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_papier:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 2, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 28.9998140335083, 3: 0, 4: 0}, 'duration': 0, 'nb_balles_papier': 0.0289998140335083, 'begin_time_port': 'image'} Production hashtag (incorrect ponderation at 20-10-18) : 0.0289998140335083 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_plastique_fonce:{'day': '07092021', 'map_nb_amount': {0: 1, 1: 0, 2: 11, 3: 0, 4: 0}, 'map_time_amount': {0: 11.000201940536499, 1: 0, 2: 111.00051093101501, 3: 0, 4: 0}, 'duration': 330.0000479221344, 'nb_balles_papier': 0.12300071287155151, 'begin_time_port': 'image_07092021_08_52_53_009918m0.jpg 0.01 for time 10.0, id_amount 3 this amount prod time diff : 0.01'} Production hashtag (incorrect ponderation at 20-10-18) : 0.12300071287155151 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_papier:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 8, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 60.99999809265137, 3: 0, 4: 0}, 'duration': 291.0001850128174, 'nb_balles_papier': 0.06299999809265137, 'begin_time_port': 'image_07092021_09_02_43_009964m0.jpg 0.001 for time 1, id_amount 3 this amount prod time diff : 0.001'} Production hashtag (incorrect ponderation at 20-10-18) : 0.06299999809265137 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_plastique_fonce:{'day': '07092021', 'map_nb_amount': {0: 1, 1: 0, 2: 16, 3: 0, 4: 0}, 'map_time_amount': {0: 8.999944925308228, 1: 0, 2: 148.99963188171387, 3: 0, 4: 0}, 'duration': 3119.999976873398, 'nb_balles_papier': 0.16199957680702212, 'begin_time_port': 'image_07092021_09_10_34_010157m0.jpg 0.001 for time 1, id_amount 3 this amount prod time diff : 0.001'} Production hashtag (incorrect ponderation at 20-10-18) : 0.16199957680702212 We filter photos on hashtag condition ! result_one_balle_Type_aluminium:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 7, 3: 1, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 72.00012874603271, 3: 9.999994993209839, 4: 0}, 'duration': 150.00017404556274, 'nb_balles_papier': 0.08200012373924254, 'begin_time_port': 'image_07092021_10_03_24_009930m0.jpg 0.009999775886535644 for time 9.999775886535645, id_amount 3 this amount prod time diff : 0.009999775886535644'} Production hashtag (incorrect ponderation at 20-10-18) : 0.08200012373924254 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_tetrapak:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 2, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 19.99965810775757, 3: 0, 4: 0}, 'duration': 0, 'nb_balles_papier': 0.01999965810775757, 'begin_time_port': 'image'} Production hashtag (incorrect ponderation at 20-10-18) : 0.01999965810775757 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_plastique_fonce:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 10, 3: 2, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 81.00049686431885, 3: 19.999656200408936, 4: 0}, 'duration': 428.99973487854004, 'nb_balles_papier': 0.10300015306472779, 'begin_time_port': 'image_07092021_10_16_24_010117m0.jpg 0.001 for time 1, id_amount 3 this amount prod time diff : 0.001'} Production hashtag (incorrect ponderation at 20-10-18) : 0.10300015306472779 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_papier:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 4, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 40.00009298324585, 3: 0, 4: 0}, 'duration': 38.99979090690613, 'nb_balles_papier': 0.04000009298324585, 'begin_time_port': 'image_07092021_10_23_44_010139m0.jpg 0.011000287055969239 for time 11.000287055969238, id_amount 3 this amount prod time diff : 0.011000287055969239'} Production hashtag (incorrect ponderation at 20-10-18) : 0.04000009298324585 We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! result_one_balle_Type_plastique_fonce:{'day': '07092021', 'map_nb_amount': {0: 0, 1: 0, 2: 6, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 60.00031113624573, 3: 0, 4: 0}, 'duration': 98.99990916252136, 'nb_balles_papier': 0.060000311136245724, 'begin_time_port': 'image_07092021_10_24_34_010156m0.jpg 0.011000226020812989 for time 11.000226020812988, id_amount 3 this amount prod time diff : 0.011000226020812989'} Production hashtag (incorrect ponderation at 20-10-18) : 0.060000311136245724 We filter photos on hashtag condition ! We have rejected 0 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 15 list_same_port_ids : [13545772] find same portfolio which already exist 13545772 , we will use it list_same_port_ids : [13545774] find same portfolio which already exist 13545774 , we will use it list_same_port_ids : [13545777] find same portfolio which already exist 13545777 , we will use it list_same_port_ids : [5570414] find same portfolio which already exist 5570414 , we will use it list_same_port_ids : [13545779] find same portfolio which already exist 13545779 , we will use it list_same_port_ids : [13545780] find same portfolio which already exist 13545780 , we will use it list_same_port_ids : [13545783] find same portfolio which already exist 13545783 , we will use it list_same_port_ids : [13545785] find same portfolio which already exist 13545785 , we will use it list_same_port_ids : [13545787] find same portfolio which already exist 13545787 , we will use it list_same_port_ids : [13545788] find same portfolio which already exist 13545788 , we will use it list_same_port_ids : [13543473] find same portfolio which already exist 13543473 , we will use it list_same_port_ids : [13543474] find same portfolio which already exist 13543474 , we will use it list_same_port_ids : [13543475] find same portfolio which already exist 13543475 , we will use it list_same_port_ids : [13543476] find same portfolio which already exist 13543476 , we will use it list_same_port_ids : [13543477] find same portfolio which already exist 13543477 , we will use it # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! DataTypes for each output/input checked ! TODO SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13545772 To do Qualite : 0.005814130015432098 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 10257 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 10261 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 10261 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 10263 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 10264 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10260 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 10259 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 10259 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 10306 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 11081 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 10260 doesn't seem to be define in the database( WARNING : type of input 3 of step 10259 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 10260 doesn't seem to be define in the database( WARNING : output 1 of step 10258 have datatype=7 whereas input 1 of step 10260 have datatype=None WARNING : type of output 2 of step 10257 doesn't seem to be define in the database( WARNING : type of input 2 of step 10261 doesn't seem to be define in the database( WARNING : output 0 of step 10257 have datatype=16 whereas input 0 of step 10264 have datatype=1 WARNING : output 1 of step 10257 have datatype=2 whereas input 1 of step 10264 have datatype=7 WARNING : output 0 of step 10263 have datatype=6 whereas input 2 of step 10264 have datatype=5 WARNING : type of output 2 of step 10264 doesn't seem to be define in the database( WARNING : type of input 1 of step 10258 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 10260 have datatype=10 whereas input 3 of step 10306 have datatype=6 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13545774 AND mptpi.`type`=4199 To do Qualite : 0.1888521086140681 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! DataTypes for each output/input checked ! TODO SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13545777 To do Qualite : 0.007415846836419753 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 10257 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 10261 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 10261 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 10263 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 10264 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10260 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 10259 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 10259 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 10306 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 11081 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 10260 doesn't seem to be define in the database( WARNING : type of input 3 of step 10259 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 10260 doesn't seem to be define in the database( WARNING : output 1 of step 10258 have datatype=7 whereas input 1 of step 10260 have datatype=None WARNING : type of output 2 of step 10257 doesn't seem to be define in the database( WARNING : type of input 2 of step 10261 doesn't seem to be define in the database( WARNING : output 0 of step 10257 have datatype=16 whereas input 0 of step 10264 have datatype=1 WARNING : output 1 of step 10257 have datatype=2 whereas input 1 of step 10264 have datatype=7 WARNING : output 0 of step 10263 have datatype=6 whereas input 2 of step 10264 have datatype=5 WARNING : type of output 2 of step 10264 doesn't seem to be define in the database( WARNING : type of input 1 of step 10258 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 10260 have datatype=10 whereas input 3 of step 10306 have datatype=6 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=5570414 AND mptpi.`type`=4199 To do # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! DataTypes for each output/input checked ! TODO SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13545779 To do # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 10257 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 10261 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 10261 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 10263 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 10264 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10260 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 10259 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 10259 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 10306 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 11081 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 10260 doesn't seem to be define in the database( WARNING : type of input 3 of step 10259 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 10260 doesn't seem to be define in the database( WARNING : output 1 of step 10258 have datatype=7 whereas input 1 of step 10260 have datatype=None WARNING : type of output 2 of step 10257 doesn't seem to be define in the database( WARNING : type of input 2 of step 10261 doesn't seem to be define in the database( WARNING : output 0 of step 10257 have datatype=16 whereas input 0 of step 10264 have datatype=1 WARNING : output 1 of step 10257 have datatype=2 whereas input 1 of step 10264 have datatype=7 WARNING : output 0 of step 10263 have datatype=6 whereas input 2 of step 10264 have datatype=5 WARNING : type of output 2 of step 10264 doesn't seem to be define in the database( WARNING : type of input 1 of step 10258 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 10260 have datatype=10 whereas input 3 of step 10306 have datatype=6 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13545780 AND mptpi.`type`=4199 To do # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! DataTypes for each output/input checked ! TODO SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13545783 To do Qualite : 0.00907640496399177 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 10257 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 10261 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 10261 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 10263 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 10264 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10260 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 10259 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 10259 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 10306 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 11081 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 10260 doesn't seem to be define in the database( WARNING : type of input 3 of step 10259 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 10260 doesn't seem to be define in the database( WARNING : output 1 of step 10258 have datatype=7 whereas input 1 of step 10260 have datatype=None WARNING : type of output 2 of step 10257 doesn't seem to be define in the database( WARNING : type of input 2 of step 10261 doesn't seem to be define in the database( WARNING : output 0 of step 10257 have datatype=16 whereas input 0 of step 10264 have datatype=1 WARNING : output 1 of step 10257 have datatype=2 whereas input 1 of step 10264 have datatype=7 WARNING : output 0 of step 10263 have datatype=6 whereas input 2 of step 10264 have datatype=5 WARNING : type of output 2 of step 10264 doesn't seem to be define in the database( WARNING : type of input 1 of step 10258 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 10260 have datatype=10 whereas input 3 of step 10306 have datatype=6 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13545785 AND mptpi.`type`=4199 To do # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! DataTypes for each output/input checked ! TODO SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13545787 To do Qualite : 0.01485129824918373 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 10257 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 10261 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 10261 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 10263 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 10264 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10260 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 10259 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 10259 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 10306 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 11081 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 10260 doesn't seem to be define in the database( WARNING : type of input 3 of step 10259 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 10260 doesn't seem to be define in the database( WARNING : output 1 of step 10258 have datatype=7 whereas input 1 of step 10260 have datatype=None WARNING : type of output 2 of step 10257 doesn't seem to be define in the database( WARNING : type of input 2 of step 10261 doesn't seem to be define in the database( WARNING : output 0 of step 10257 have datatype=16 whereas input 0 of step 10264 have datatype=1 WARNING : output 1 of step 10257 have datatype=2 whereas input 1 of step 10264 have datatype=7 WARNING : output 0 of step 10263 have datatype=6 whereas input 2 of step 10264 have datatype=5 WARNING : type of output 2 of step 10264 doesn't seem to be define in the database( WARNING : type of input 1 of step 10258 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 10260 have datatype=10 whereas input 3 of step 10306 have datatype=6 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13545788 AND mptpi.`type`=4199 To do # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 0 init_dummy_multi_datou is not linked in the step_by_step architecture ! WARNING : step 1294 init_dummy_multi_datou is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! TODO SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13543473 To do # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : step 0 init_dummy_multi_datou is not linked in the step_by_step architecture ! WARNING : step 1294 init_dummy_multi_datou is not linked in the step_by_step architecture ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! TODO SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13543474 To do Qualite : 0.003848153410463827 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 10257 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 10261 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 10261 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 10263 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 10264 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10260 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 10259 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 10259 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 10306 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 11081 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 10260 doesn't seem to be define in the database( WARNING : type of input 3 of step 10259 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 10260 doesn't seem to be define in the database( WARNING : output 1 of step 10258 have datatype=7 whereas input 1 of step 10260 have datatype=None WARNING : type of output 2 of step 10257 doesn't seem to be define in the database( WARNING : type of input 2 of step 10261 doesn't seem to be define in the database( WARNING : output 0 of step 10257 have datatype=16 whereas input 0 of step 10264 have datatype=1 WARNING : output 1 of step 10257 have datatype=2 whereas input 1 of step 10264 have datatype=7 WARNING : output 0 of step 10263 have datatype=6 whereas input 2 of step 10264 have datatype=5 WARNING : type of output 2 of step 10264 doesn't seem to be define in the database( WARNING : type of input 1 of step 10258 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 10260 have datatype=10 whereas input 3 of step 10306 have datatype=6 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13543475 AND mptpi.`type`=4199 To do Qualite : 0.11478003563407302 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! DataTypes for each output/input checked ! TODO SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13543476 To do Qualite : 0.019897576026366652 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 10257 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 10261 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 10261 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 10263 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 10264 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10258 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 10260 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 10259 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 10259 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 10306 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 11081 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 10260 doesn't seem to be define in the database( WARNING : type of input 3 of step 10259 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 10260 doesn't seem to be define in the database( WARNING : output 1 of step 10258 have datatype=7 whereas input 1 of step 10260 have datatype=None WARNING : type of output 2 of step 10257 doesn't seem to be define in the database( WARNING : type of input 2 of step 10261 doesn't seem to be define in the database( WARNING : output 0 of step 10257 have datatype=16 whereas input 0 of step 10264 have datatype=1 WARNING : output 1 of step 10257 have datatype=2 whereas input 1 of step 10264 have datatype=7 WARNING : output 0 of step 10263 have datatype=6 whereas input 2 of step 10264 have datatype=5 WARNING : type of output 2 of step 10264 doesn't seem to be define in the database( WARNING : type of input 1 of step 10258 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 10260 have datatype=10 whereas input 3 of step 10306 have datatype=6 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=13543477 AND mptpi.`type`=4199 To do elapsed_time : count_nb_balles_and_create_portfolio 26.417771100997925 # DISPLAY ALL COLLECTED DATA : {'07092021': {'nb_upload': 232, 'nb_taggue_class': 232, 'nb_taggue_densite': 232, 'nb_descriptors': 232, 'number_port': 15, 'count_photo_in_port': 117, 'nb_port_per_class': {'rungis_aluminium': {'nb_photos': 8, 'nb_portfolios': 1}, 'rungis_carton': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_papier': {'nb_photos': 33, 'nb_portfolios': 6}, 'rungis_plastique_clair': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_plastique_dur': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_plastique_fonce': {'nb_photos': 74, 'nb_portfolios': 7}, 'rungis_tapis_vide': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_tetrapak': {'nb_photos': 2, 'nb_portfolios': 1}}}} time spend for datou_step_exec : 54.54829549789429 time spend to save output : 2.2172927856445312e-05 total time spend for step 1 : 54.548317670822144 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1049318362, 1049318360, 1049318358, 1049318356, 1049318342, 1049318339, 1049318337, 1049318311, 1049318310, 1049318309, 1049318294, 1049318293, 1049318291, 1049318289, 1049318288, 1049318287, 1049318279, 1049318276, 1049318273, 1049318271, 1049318268, 1049318265, 1049318260, 1049318257, 1049318253, 1049318250, 1049318247, 1049318246, 1049318222, 1049318219, 1049318216, 1049318214, 1049318213, 1049318212, 1049317554, 1049317551, 1049317549, 1049317546, 1049317542, 1049317536, 1049317526, 1049317525, 1049317524, 1049317522, 1049317520, 1049317517, 1049317497, 1049317493, 1049317491, 1049317489, 1049317487, 1049317485, 1049317468, 1049317461, 1049317457, 1049317453, 1049317444, 1049317440, 1049317359, 1049317333, 1049317282, 1049317225, 1049317210, 1049317197, 1049316790, 1049316785, 1049316782, 1049316778, 1049316752, 1049316749, 1049316610, 1049316600, 1049316597, 1049316594, 1049316588, 1049316582, 1049316545, 1049316543, 1049316540, 1049316537, 1049316534, 1049316520, 1049316338, 1049316336, 1049316332, 1049316331, 1049316257, 1049316255, 1049316222, 1049316216, 1049316214, 1049316212, 1049316210, 1049316209, 1049313025, 1049312984, 1049312803, 1049312588, 1049312585, 1049312583, 1049312579, 1049312574, 1049312573, 1049312571, 1049312568, 1049312566, 1049312562, 1049312556, 1049312508, 1049312489, 1049312488, 1049312487, 1049312485, 1049312484, 1049312464, 1049312463, 1049312462, 1049312461, 1049312460, 1049312449, 1049312445, 1049312444, 1049312442, 1049312440, 1049312438, 1049312429, 1049312426, 1049312424, 1049312422, 1049312420, 1049312409, 1049312406, 1049312404, 1049312363, 1049312208, 1049311964, 1049311963, 1049311962, 1049311961, 1049311960, 1049311943, 1049311938, 1049311937, 1049311935, 1049311934, 1049311932, 1049311795, 1049311793, 1049311791, 1049311771, 1049311767, 1049311267, 1049311266, 1049311263, 1049311252, 1049311199, 1049311136, 1049311073, 1049311009, 1049311006, 1049310994, 1049310992, 1049310991, 1049310984, 1049310982, 1049310981, 1049310919, 1049310914, 1049310911, 1049310909, 1049310907, 1049310905, 1049310165, 1049310162, 1049310159, 1049310145, 1049310141, 1049310139, 1049310138, 1049310134, 1049310132, 1049309737, 1049309734, 1049309732, 1049309706, 1049309703, 1049309701, 1049309686, 1049309681, 1049309677, 1049309675, 1049309672, 1049309670, 1049309658, 1049309657, 1049309656, 1049309655, 1049309653, 1049309651, 1049309605, 1049309603, 1049309599, 1049309597, 1049309595, 1049309592, 1049309385, 1049309383, 1049309382, 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None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049308276', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049308275', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049308235', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049307693', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049306823', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049306804', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049306792', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049306791', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049306635', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049306205', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049304810', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049303925', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049296996', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049296121', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049294990', None, None, None, None, None, None) ('3789', None, None, None, None, None, None, None, None) ('3789', '4599398', '1049293230', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 233 time used for this insertion : 0.7882049083709717 save_final save missing photos in datou_result : After save, about to update current ! Result test rubbia : {'4599398': ([[0, 7, 8, 9, 11, 12, 13, 14, 17, 18], [19, 20, 22, 23, 25, 26, 27, 38, 39, 40, 51, 52, 53, 55, 60, 61, 62, 63, 71, 76, 77, 81, 82, 83, 84], [85, 86, 91, 92], [93], [97, 98, 99, 100, 101], [102], [103, 104], [107, 108, 109, 110, 112, 113, 116, 117, 118, 121, 122, 123], [124, 126, 128, 129, 130, 131, 134, 135], [136, 137, 138, 147, 148, 149, 150, 151, 152, 153, 154, 157, 158, 161, 162, 167, 168], [173, 176, 177, 178, 182, 183, 187, 188], [189, 193], [198, 201, 202, 207, 208, 209, 210, 211, 212, 213, 214, 215], [216, 217, 218, 220], [221, 224, 225, 226, 227, 231]], {'rungis_aluminium': [(10, 11)], 'rungis_carton': [], 'rungis_papier': [(0, 1), (2, 3), (4, 5), (6, 7), (8, 9), (13, 14)], 'rungis_plastique_clair': [], 'rungis_plastique_dur': [], 'rungis_plastique_fonce': [(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (12, 13), (14, 15)], 'rungis_tapis_vide': [], 'rungis_tetrapak': [(11, 12)]}, {13545772: {'list_of_photos': [1049293230, 1049306791, 1049294990, 1049306792, 1049306823, 1049307693, 1049308235, 1049308275, 1049308376, 1049308381], 'hashtag': 'papier'}, 13545774: {'list_of_photos': [1049308384, 1049309345, 1049309380, 1049309381, 1049309383, 1049309385, 1049309592, 1049309658, 1049309670, 1049309672, 1049310132, 1049310134, 1049310138, 1049310141, 1049310905, 1049310907, 1049310909, 1049310911, 1049310994, 1049311199, 1049311252, 1049311767, 1049311771, 1049311791, 1049311793], 'hashtag': 'plastique_fonce'}, 13545777: {'list_of_photos': [1049311795, 1049311932, 1049311943, 1049311960], 'hashtag': 'papier'}, 5570414: {'list_of_photos': [1049311961], 'hashtag': 'plastique_fonce'}, 13545779: {'list_of_photos': [1049312208, 1049312363, 1049312404, 1049312406, 1049312409], 'hashtag': 'papier'}, 13545780: {'list_of_photos': [1049312420], 'hashtag': 'plastique_fonce'}, 13545783: {'list_of_photos': [1049312422, 1049312424], 'hashtag': 'papier'}, 13545785: {'list_of_photos': [1049312438, 1049312440, 1049312442, 1049312444, 1049312449, 1049312460, 1049312463, 1049312464, 1049312484, 1049312488, 1049312489, 1049312508], 'hashtag': 'plastique_fonce'}, 13545787: {'list_of_photos': [1049312556, 1049312566, 1049312571, 1049312573, 1049312574, 1049312579, 1049312588, 1049312803], 'hashtag': 'papier'}, 13545788: {'list_of_photos': [1049312984, 1049313025, 1049316209, 1049316332, 1049316336, 1049316338, 1049316520, 1049316534, 1049316537, 1049316540, 1049316543, 1049316588, 1049316594, 1049316610, 1049316749, 1049316790, 1049317197], 'hashtag': 'plastique_fonce'}, 13543473: {'list_of_photos': [1049317359, 1049317453, 1049317457, 1049317461, 1049317489, 1049317491, 1049317520, 1049317522], 'hashtag': 'aluminium'}, 13543474: {'list_of_photos': [1049317524, 1049317542], 'hashtag': 'tetrapak'}, 13543475: {'list_of_photos': [1049318212, 1049318216, 1049318219, 1049318253, 1049318257, 1049318260, 1049318265, 1049318268, 1049318271, 1049318273, 1049318276, 1049318279], 'hashtag': 'plastique_fonce'}, 13543476: {'list_of_photos': [1049318287, 1049318288, 1049318289, 1049318293], 'hashtag': 'papier'}, 13543477: {'list_of_photos': [1049318294, 1049318311, 1049318337, 1049318339, 1049318342, 1049318362], 'hashtag': 'plastique_fonce'}}, {2107751280: 8, 2107750907: 0, 2107750908: 33, 2107750909: 0, 2107750910: 0, 2107750911: 74, 2107750912: 0, 2107750913: 2}, {'amount_uploaded_and_tagged': {'07092021': {'nb_upload': 232, 'nb_taggue_class': 232, 'nb_taggue_densite': 232, 'nb_descriptors': 232, 'number_port': 15, 'count_photo_in_port': 117, 'nb_port_per_class': {'rungis_aluminium': {'nb_photos': 8, 'nb_portfolios': 1}, 'rungis_carton': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_papier': {'nb_photos': 33, 'nb_portfolios': 6}, 'rungis_plastique_clair': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_plastique_dur': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_plastique_fonce': {'nb_photos': 74, 'nb_portfolios': 7}, 'rungis_tapis_vide': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_tetrapak': {'nb_photos': 2, 'nb_portfolios': 1}}}}, 'map_all_result_after_group_moy_exp': {'number_port': 15, 'count_photo_in_port': 117, 'nb_port_per_class': {'rungis_aluminium': {'nb_photos': 8, 'nb_portfolios': 1}, 'rungis_carton': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_papier': {'nb_photos': 33, 'nb_portfolios': 6}, 'rungis_plastique_clair': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_plastique_dur': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_plastique_fonce': {'nb_photos': 74, 'nb_portfolios': 7}, 'rungis_tapis_vide': {'nb_photos': 0, 'nb_portfolios': 0}, 'rungis_tetrapak': {'nb_photos': 2, 'nb_portfolios': 1}}}, 'map_info_after_moyenne_mobile': {'07092021': {'distrib_time_diff': {'nb': 207, 'mean': 12.512076641626404, 'stddev': 12.296218880583977, 'min': 0.0, 'max': 119.00011491775513, 'quantil_10': {'min': [8.999778032302856], 'max': [11.000291109085083]}, 'quantil_100': {'min': [8.999709129333496], 'max': [61.00024700164795]}, 'quantil_1000': {'min': [0.0], 'max': [119.00011491775513]}, 'quantil_5000': {'min': [0.0], 'max': [119.00011491775513]}, 'quantil_10000': {'min': [0.0], 'max': [119.00011491775513]}}, 'time_diff': {'rungis_aluminium': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 80.99965000152588, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_carton': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 49.000049114227295, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_papier': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 11.000201940536499, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 534.9997780323029, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_clair': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_dur': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 31.000057697296143, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_fonce': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 564.0013737678528, '05102018_papier_non_papier_tres_peu_dense': 19.999656200408936}, 'rungis_tapis_vide': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_tetrapak': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 8.999944925308228, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 89.99986672401428, '05102018_papier_non_papier_tres_peu_dense': 9.999994993209839}}, 'time_diff_removed': {'rungis_aluminium': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 11.000208854675293, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 158.99993062019348, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_carton': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 101.00013995170593, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_papier': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 18.999826192855835, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 168.99926328659058, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_clair': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_dur': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_fonce': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 21.00012707710266, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 489.9993727207184, '05102018_papier_non_papier_tres_peu_dense': 11.000169038772583}, 'rungis_tapis_vide': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_tetrapak': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 38.99988508224487, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 170.0003685951233, '05102018_papier_non_papier_tres_peu_dense': 0}}, 'nb_photos': {'rungis_aluminium': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 8, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_carton': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 6, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_papier': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 1, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 28, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_clair': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_dur': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 2, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_fonce': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 40, '05102018_papier_non_papier_tres_peu_dense': 2}, 'rungis_tapis_vide': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_tetrapak': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 1, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 9, '05102018_papier_non_papier_tres_peu_dense': 1}}, 'nb_photos_removed': {'rungis_aluminium': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 1, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 16, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_carton': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 5, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_papier': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 2, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 16, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_clair': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_dur': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_plastique_fonce': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 1, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 46, '05102018_papier_non_papier_tres_peu_dense': 1}, 'rungis_tapis_vide': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 0, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 0, '05102018_papier_non_papier_tres_peu_dense': 0}, 'rungis_tetrapak': {'05102018_papier_non_papier_dense': 0, '05102018_papier_non_papier_peu_dense': 4, '05102018_papier_non_papier_presque_vide': 0, '05102018_papier_non_papier_tres_dense': 17, '05102018_papier_non_papier_tres_peu_dense': 0}}}}, 'map_amount_per_hashtag': {'rungis_aluminium': [(10, 11)], 'rungis_carton': [], 'rungis_papier': [(0, 1), (2, 3), (4, 5), (6, 7), (8, 9), (13, 14)], 'rungis_plastique_clair': [], 'rungis_plastique_dur': [], 'rungis_plastique_fonce': [(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (12, 13), (14, 15)], 'rungis_tapis_vide': [], 'rungis_tetrapak': [(11, 12)]}, 'count': {'rungis_aluminium': [(10, 11)], 'rungis_carton': [], 'rungis_papier': [(0, 1), (2, 3), (4, 5), (6, 7), (8, 9), (13, 14)], 'rungis_plastique_clair': [], 'rungis_plastique_dur': [], 'rungis_plastique_fonce': [(1, 2), (3, 4), (5, 6), (7, 8), (9, 10), (12, 13), (14, 15)], 'rungis_tapis_vide': [], 'rungis_tetrapak': [(11, 12)]}})}| Result context_with_local_rubbia.cache_model_config.map_io test rubbia : {'input': {}, 'output': {}}| ############################### TEST rubbia_split_dark ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : split_time_score_with_photo list_input_json : [] origin We have 1 , BBBBBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFFBFBFBFFBFBFFFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 64 ; length of list_pids : 64 ; length of list_args : 64 time to download the photos : 4.1687846183776855 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False we use local cache db, so we are in local job, but when commit will be implemented for local cache db, we could again use save number of steps : 1 step1:split_time_score_with_photo Sat Feb 15 05:27:28 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec ----- Debut du copier-coller des param necessaire pour fonction main de STS ----- TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('18', 4), ('19', 5), ('20', 5), ('24', 8), ('26', 6), ('17', 1), ('27', 9), ('51', 7), ('28', 2), ('21', 4), ('52', 2), ('25', 6), ('50', 3), ('22', 2)) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 06102021 4608689 Nombre de photos uploadées : 64 / 23040 (0%) 06102021 4608689 Nombre de photos taguées (types de déchets): 0 / 64 (0%) 06102021 4608689 Nombre de photos taguées (volume) : 0 / 64 (0%) elapsed_time : load_data_split_time_score 1.4066696166992188e-05 elapsed_time : order_list_meta_photo_and_scores 1.6927719116210938e-05 ???????????????????????????????????????????????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.006925106048583984 elapsed_time : insert_dashboard_record_day_entry 0.026001691818237305 ***** BEGIN SPLIT BY DARK ***** To DO 08/10/21 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 1 time used for this insertion : 0.014269590377807617 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 2 time used for this insertion : 0.008950948715209961 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 3 time used for this insertion : 0.008951663970947266 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 4 time used for this insertion : 0.008967876434326172 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 5 time used for this insertion : 0.008968353271484375 elapsed_time : SPLIT_BY_DARK 0.06544637680053711 ***** END SPLIT BY DARK ***** ((1055001085,), (1055008638,), (1055010730,), (1055011086,), (1055012686,)) ***** BEGIN SPLIT TIME ***** False [12, 20, 29, 38, 51] 1633478400.0 `1633508253.0 1633507200.0 `1633508284.0 1633507200.0 `1633508316.0 1633507200.0 `1633508323.0 1633507200.0 `1633508333.0 1633507200.0 `1633508340.0 1633507200.0 `1633508358.0 1633507200.0 `1633508369.0 1633507200.0 `1633508385.0 1633507200.0 `1633508398.0 1633507200.0 `1633508416.0 1633507200.0 `1633508425.0 1633507200.0 `1633508434.0 1633507200.0 `1633508449.0 1633507200.0 `1633508458.0 1633507200.0 `1633508470.0 1633507200.0 `1633508491.0 1633507200.0 `1633508499.0 1633507200.0 `1633508508.0 1633507200.0 `1633508521.0 1633507200.0 `1633508524.0 1633507200.0 `1633508644.0 1633507200.0 `1633508652.0 1633507200.0 `1633508657.0 1633507200.0 `1633508669.0 1633507200.0 `1633508678.0 1633507200.0 `1633508684.0 1633507200.0 `1633508690.0 1633507200.0 `1633508696.0 1633507200.0 `1633508701.0 1633507200.0 `1633508725.0 1633507200.0 `1633508733.0 1633507200.0 `1633508739.0 1633507200.0 `1633508748.0 1633507200.0 `1633508759.0 1633507200.0 `1633508766.0 1633507200.0 `1633508772.0 1633507200.0 `1633508778.0 1633507200.0 `1633508781.0 1633507200.0 `1633508805.0 1633507200.0 `1633508813.0 1633507200.0 `1633508820.0 1633507200.0 `1633508824.0 1633507200.0 `1633508829.0 1633507200.0 `1633508833.0 1633507200.0 `1633508849.0 1633507200.0 `1633508858.0 1633507200.0 `1633508865.0 1633507200.0 `1633508871.0 1633507200.0 `1633508877.0 1633507200.0 `1633508886.0 1633507200.0 `1633508891.0 1633507200.0 `1633524639.0 1633521600.0 `1633524648.0 1633521600.0 `1633524657.0 1633521600.0 `1633524662.0 1633521600.0 `1633524675.0 1633521600.0 `1633524680.0 1633521600.0 `1633524683.0 1633521600.0 `1633524694.0 1633521600.0 `1633524700.0 1633521600.0 `1633524718.0 1633521600.0 `1633524722.0 1633521600.0 `1633524741.0 1633521600.0 list printed: [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [13, 14, 15, 16, 17, 18, 19], [21, 22, 23, 24, 25, 26, 27, 28], [30, 31, 32, 33, 34, 35, 36, 37], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50], [], [52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]] forced_hashtag: jrm force hashtag to jrm elapsed_time : SPLIT_TIME 0.007803678512573242 ***** END SPLIT TIME ***** NUMBER BATCH : 7 list_ponderation used : [0.001, 0.001, 0.001, 0.001, 0.001] , list_hashtag_class_create_as_list : ['refus', 'jrm'] ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 172.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_101733.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 72.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_102049.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 52.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_102404.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 53.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_102525.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 81.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_102645.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 Empty batch, bug or could have been filtered ! ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info result_one_balle_Type_jrm:{'day': '06102021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 102.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20211006_145039.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 We have rejected 0 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 6 list_same_port_ids : [4938484] find same portfolio which already exist 4938484 , we will use it list_same_port_ids : [4938485] find same portfolio which already exist 4938485 , we will use it list_same_port_ids : [4938486] find same portfolio which already exist 4938486 , we will use it list_same_port_ids : [4938487] find same portfolio which already exist 4938487 , we will use it list_same_port_ids : [4938488] find same portfolio which already exist 4938488 , we will use it list_same_port_ids : [4756245] find same portfolio which already exist 4756245 , we will use it Qualite : 0.049377889059021136 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4938484 AND mptpi.`type`=4038 To do Qualite : 0.051267724965616025 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4938485 AND mptpi.`type`=4038 To do Qualite : 0.06573670331612967 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4938486 AND mptpi.`type`=4038 To do Qualite : 0.12804353375222421 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4938487 AND mptpi.`type`=4038 To do Qualite : 0.07355022343618775 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4938488 AND mptpi.`type`=4038 To do Qualite : 0.10644996740301908 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4756245 AND mptpi.`type`=4038 To do elapsed_time : count_nb_balles_and_create_portfolio 1.0815513134002686 # DISPLAY ALL COLLECTED DATA : {'06102021': {'nb_upload': 64, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}} ------ Fin du Copier-Coller ------ ---------- ONE RESULT --------- ([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [13, 14, 15, 16, 17, 18, 19], [21, 22, 23, 24, 25, 26, 27, 28], [30, 31, 32, 33, 34, 35, 36, 37], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50], [], [52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]], {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, {4938484: {'list_of_photos': [1055000228, 1055000055, 1055003357, 1055007950, 1055003348, 1055007953, 1055000059, 1055007992, 1055008181, 1055003197, 1055003198, 1055008184], 'hashtag': 'jrm'}, 4938485: {'list_of_photos': [1055000063, 1055004600, 1055008597, 1055003134, 1055008599, 1055003679, 1055004627], 'hashtag': 'jrm'}, 4938486: {'list_of_photos': [1055004217, 1055010143, 1055004278, 1055010723, 1055003131, 1055003202, 1055010725, 1055000068], 'hashtag': 'jrm'}, 4938487: {'list_of_photos': [1055010737, 1055010739, 1055003278, 1055010743, 1055011072, 1055011074, 1055011076, 1055000070], 'hashtag': 'jrm'}, 4938488: {'list_of_photos': [1055011441, 1055011454, 1055003185, 1055011459, 1055001092, 1055001542, 1055003292, 1055011726, 1055011733, 1055011740, 1055012684, 1055002045], 'hashtag': 'jrm'}, 4756245: {'list_of_photos': [1055012722, 1055004798, 1055004608, 1055012727, 1055013693, 1055013724, 1055003249, 1055001545, 1055003259, 1055013727, 1055003266, 1055003261], 'hashtag': 'jrm'}}, {2107757407: 59}, {'amount_uploaded_and_tagged': {'06102021': {'nb_upload': 64, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}}, 'map_amount_per_hashtag': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, 'count': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}}) ---------- END de ONE RESULT ---------- Suppression des photos Telecharges time spend for datou_step_exec : 6.920277118682861 time spend to save output : 0.00010037422180175781 total time spend for step 1 : 6.920377492904663 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : split_time_score_with_photo we use saveGeneral [1055003131, 1055002045, 1055001545, 1055001542, 1055001092, 1055001085, 1055000228, 1055000070, 1055000068, 1055000063, 1055000059, 1055000055, 1055013727, 1055013724, 1055013693, 1055012727, 1055012722, 1055012686, 1055012684, 1055011740, 1055011733, 1055011726, 1055011459, 1055011454, 1055011441, 1055011086, 1055011076, 1055011074, 1055011072, 1055010743, 1055010739, 1055010737, 1055010730, 1055010725, 1055010723, 1055010143, 1055008638, 1055008599, 1055003357, 1055003348, 1055003292, 1055003278, 1055003266, 1055003261, 1055003259, 1055003249, 1055003202, 1055003198, 1055003197, 1055003185, 1055003134, 1055008597, 1055008184, 1055008181, 1055007992, 1055007953, 1055007950, 1055004798, 1055004627, 1055004608, 1055004600, 1055004278, 1055004217, 1055003679] Looping around the photos to save general results len do output : 5 /[[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [13, 14, 15, 16, 17, 18, 19], [21, 22, 23, 24, 25, 26, 27, 28], [30, 31, 32, 33, 34, 35, 36, 37], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50], [], [52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]] /{'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]} /{4938484: {'list_of_photos': [1055000228, 1055000055, 1055003357, 1055007950, 1055003348, 1055007953, 1055000059, 1055007992, 1055008181, 1055003197, 1055003198, 1055008184], 'hashtag': 'jrm'}, 4938485: {'list_of_photos': [1055000063, 1055004600, 1055008597, 1055003134, 1055008599, 1055003679, 1055004627], 'hashtag': 'jrm'}, 4938486: {'list_of_photos': [1055004217, 1055010143, 1055004278, 1055010723, 1055003131, 1055003202, 1055010725, 1055000068], 'hashtag': 'jrm'}, 4938487: {'list_of_photos': [1055010737, 1055010739, 1055003278, 1055010743, 1055011072, 1055011074, 1055011076, 1055000070], 'hashtag': 'jrm'}, 4938488: {'list_of_photos': [1055011441, 1055011454, 1055003185, 1055011459, 1055001092, 1055001542, 1055003292, 1055011726, 1055011733, 1055011740, 1055012684, 1055002045], 'hashtag': 'jrm'}, 4756245: {'list_of_photos': [1055012722, 1055004798, 1055004608, 1055012727, 1055013693, 1055013724, 1055003249, 1055001545, 1055003259, 1055013727, 1055003266, 1055003261], 'hashtag': 'jrm'}} /{2107757407: 59} /{'amount_uploaded_and_tagged': {'06102021': {'nb_upload': 64, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}}, 'map_amount_per_hashtag': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, 'count': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}} before output type Managing all output in save final without adding information in the mtr_datou_result ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003131', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055002045', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055001545', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055001542', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055001092', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055001085', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000228', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000070', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000068', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000063', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000059', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055000055', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055013727', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055013724', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055013693', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055012727', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055012722', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055012686', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055012684', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011740', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011733', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011726', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011459', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011454', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011441', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011086', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011076', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011074', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055011072', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010743', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010739', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010737', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010730', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010725', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010723', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055010143', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055008638', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055008599', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003357', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003348', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003292', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003278', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003266', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003261', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003259', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003249', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003202', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003198', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003197', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003185', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003134', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055008597', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055008184', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055008181', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055007992', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055007953', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055007950', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004798', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004627', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004608', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004600', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004278', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055004217', None, None, None, None, None, None) ('3787', None, None, None, None, None, None, None, None) ('3787', '4608689', '1055003679', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 64 time used for this insertion : 0.07634615898132324 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : ([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [13, 14, 15, 16, 17, 18, 19], [21, 22, 23, 24, 25, 26, 27, 28], [30, 31, 32, 33, 34, 35, 36, 37], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50], [], [52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]], {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, {4938484: {'list_of_photos': [1055000228, 1055000055, 1055003357, 1055007950, 1055003348, 1055007953, 1055000059, 1055007992, 1055008181, 1055003197, 1055003198, 1055008184], 'hashtag': 'jrm'}, 4938485: {'list_of_photos': [1055000063, 1055004600, 1055008597, 1055003134, 1055008599, 1055003679, 1055004627], 'hashtag': 'jrm'}, 4938486: {'list_of_photos': [1055004217, 1055010143, 1055004278, 1055010723, 1055003131, 1055003202, 1055010725, 1055000068], 'hashtag': 'jrm'}, 4938487: {'list_of_photos': [1055010737, 1055010739, 1055003278, 1055010743, 1055011072, 1055011074, 1055011076, 1055000070], 'hashtag': 'jrm'}, 4938488: {'list_of_photos': [1055011441, 1055011454, 1055003185, 1055011459, 1055001092, 1055001542, 1055003292, 1055011726, 1055011733, 1055011740, 1055012684, 1055002045], 'hashtag': 'jrm'}, 4756245: {'list_of_photos': [1055012722, 1055004798, 1055004608, 1055012727, 1055013693, 1055013724, 1055003249, 1055001545, 1055003259, 1055013727, 1055003266, 1055003261], 'hashtag': 'jrm'}}, {2107757407: 59}, {'amount_uploaded_and_tagged': {'06102021': {'nb_upload': 64, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}}, 'map_amount_per_hashtag': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, 'count': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}}) Result test split dark : ([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], [13, 14, 15, 16, 17, 18, 19], [21, 22, 23, 24, 25, 26, 27, 28], [30, 31, 32, 33, 34, 35, 36, 37], [39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50], [], [52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63]], {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, {4938484: {'list_of_photos': [1055000228, 1055000055, 1055003357, 1055007950, 1055003348, 1055007953, 1055000059, 1055007992, 1055008181, 1055003197, 1055003198, 1055008184], 'hashtag': 'jrm'}, 4938485: {'list_of_photos': [1055000063, 1055004600, 1055008597, 1055003134, 1055008599, 1055003679, 1055004627], 'hashtag': 'jrm'}, 4938486: {'list_of_photos': [1055004217, 1055010143, 1055004278, 1055010723, 1055003131, 1055003202, 1055010725, 1055000068], 'hashtag': 'jrm'}, 4938487: {'list_of_photos': [1055010737, 1055010739, 1055003278, 1055010743, 1055011072, 1055011074, 1055011076, 1055000070], 'hashtag': 'jrm'}, 4938488: {'list_of_photos': [1055011441, 1055011454, 1055003185, 1055011459, 1055001092, 1055001542, 1055003292, 1055011726, 1055011733, 1055011740, 1055012684, 1055002045], 'hashtag': 'jrm'}, 4756245: {'list_of_photos': [1055012722, 1055004798, 1055004608, 1055012727, 1055013693, 1055013724, 1055003249, 1055001545, 1055003259, 1055013727, 1055003266, 1055003261], 'hashtag': 'jrm'}}, {2107757407: 59}, {'amount_uploaded_and_tagged': {'06102021': {'nb_upload': 64, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}}, 'map_amount_per_hashtag': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}, 'count': {'Rungis_jrm': [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6)]}})| ############################### TEST rubbia_append ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : split_time_score list_input_json : [] origin We have 1 , We have 1 , we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 0.027517318725585938 About to test input to load Calling datou_exec Inside datou_exec : verbose : False we use local cache db, so we are in local job, but when commit will be implemented for local cache db, we could again use save number of steps : 1 step1:split_time_score Sat Feb 15 05:27:35 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('30', 1), ('36', 1), ('43', 1)) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 21092021 4599006 Nombre de photos uploadées : 3 / 23040 (0%) 21092021 4599006 Nombre de photos taguées (types de déchets): 0 / 3 (0%) 21092021 4599006 Nombre de photos taguées (volume) : 0 / 3 (0%) elapsed_time : load_data_split_time_score 3.814697265625e-06 elapsed_time : order_list_meta_photo_and_scores 8.821487426757812e-06 ??? elapsed_time : fill_and_build_computed_from_old_data 0.0004749298095703125 elapsed_time : insert_dashboard_record_day_entry 0.025570392608642578 ---------- APPEND TASK BEGIN ---------- ---------- APPEND TASK END ---------- We will return after consolidate but for now we need the day, how to get it, for now depending on the previous heavy steps find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 4599006 order by id desc limit 1 NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'21092021': {'nb_upload': 3, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}} TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('12', 1), ('-0', 3)) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 21092021 4505992 Nombre de photos uploadées : 1 / 23040 (0%) 21092021 4505992 Nombre de photos taguées (types de déchets): 0 / 1 (0%) 21092021 4505992 Nombre de photos taguées (volume) : 0 / 1 (0%) elapsed_time : load_data_split_time_score 3.814697265625e-06 elapsed_time : order_list_meta_photo_and_scores 9.5367431640625e-06 ? elapsed_time : fill_and_build_computed_from_old_data 0.0002079010009765625 elapsed_time : insert_dashboard_record_day_entry 0.03481411933898926 ---------- APPEND TASK BEGIN ---------- ---------- APPEND TASK END ---------- We will return after consolidate but for now we need the day, how to get it, for now depending on the previous heavy steps find url: select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 4599006 order by id desc limit 1 find url: https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_COD_P4505992_21-09-2021.pdf select completion_json, dashboard_run_id from MTRPhoto.dashboard_results where mtr_portfolio_id = 4505992 order by id desc limit 1 NUMBER BATCH : 0 # DISPLAY ALL COLLECTED DATA : {'21092021': {'nb_upload': 1, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}} time spend for datou_step_exec : 2.4951155185699463 time spend to save output : 7.581710815429688e-05 total time spend for step 1 : 2.4951913356781006 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1054572537, 1054572534, 1054572532, 1051605195] Looping around the photos to save general results len do output : 2 /4599006Didn't retrieve data . /4505992Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3856', None, None, None, None, None, None, None, None) ('3856', '4599006', '1054572537', None, None, None, None, None, None) ('3856', None, None, None, None, None, None, None, None) ('3856', '4599006', '1054572534', None, None, None, None, None, None) ('3856', None, None, None, None, None, None, None, None) ('3856', '4599006', '1054572532', None, None, None, None, None, None) ('3856', None, None, None, None, None, None, None, None) ('3856', '4505992', '1051605195', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 0.016194581985473633 save_final save missing photos in datou_result : After save, about to update current ! ############################### TEST rubbia_horaire ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : split_time_score list_input_json : [] origin We have 1 , we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 0.09141921997070312 About to test input to load Calling datou_exec Inside datou_exec : verbose : False we use local cache db, so we are in local job, but when commit will be implemented for local cache db, we could again use save number of steps : 1 step1:split_time_score Sat Feb 15 05:27:38 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('02', 6), ('05', 8), ('06', 19)) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 08032021 3609515 Nombre de photos uploadées : 33 / 23040 (0%) 08032021 3609515 Nombre de photos taguées (types de déchets): 0 / 33 (0%) 08032021 3609515 Nombre de photos taguées (volume) : 0 / 33 (0%) elapsed_time : load_data_split_time_score 6.4373016357421875e-06 elapsed_time : order_list_meta_photo_and_scores 1.1682510375976562e-05 ????????????????????????????????? elapsed_time : fill_and_build_computed_from_old_data 0.0035965442657470703 elapsed_time : insert_dashboard_record_day_entry 0.031189680099487305 Creating list_photo_total elapsed_time : select_descriptors 0.012121915817260742 08032021 3609515 Nombre de photos avec descriptors (type 3963) : 0 / 33 (0%) Missing descriptors for photos 0 and 1014054233 0:00:00|ON:Missing descriptors for photos 1014054233 and 1014054232 Missing descriptors for photos 1014054232 and 1014054231 Missing descriptors for photos 1014054231 and 1014054230 Missing descriptors for photos 1014054230 and 1014054235 Missing descriptors for photos 1014054235 and 1014054234 Missing descriptors for photos 1014054234 and 1014097492 Missing descriptors for photos 1014097492 and 1014097499 Missing descriptors for photos 1014097499 and 1014097497 Missing descriptors for photos 1014097497 and 1014097580 Missing descriptors for photos 1014097580 and 1014097924 Missing descriptors for photos 1014097924 and 1014098236 Missing descriptors for photos 1014098236 and 1014098602 Missing descriptors for photos 1014098602 and 1014099035 Missing descriptors for photos 1014099035 and 1014105778 Missing descriptors for photos 1014105778 and 1014105777 Missing descriptors for photos 1014105777 and 1014105784 Missing descriptors for photos 1014105784 and 1014105783 Missing descriptors for photos 1014105783 and 1014105782 Missing descriptors for photos 1014105782 and 1014105781 Missing descriptors for photos 1014105781 and 1014105786 Missing descriptors for photos 1014105786 and 1014105785 Missing descriptors for photos 1014105785 and 1014105791 Missing descriptors for photos 1014105791 and 1014105790 Missing descriptors for photos 1014105790 and 1014105798 Missing descriptors for photos 1014105798 and 1014105797 Missing descriptors for photos 1014105797 and 1014105796 Missing descriptors for photos 1014105796 and 1014105795 Missing descriptors for photos 1014105795 and 1014105800 Missing descriptors for photos 1014105800 and 1014105799 Missing descriptors for photos 1014105799 and 1014106095 Missing descriptors for photos 1014106095 and 1014106094 Missing descriptors for photos 1014106094 and 1014106093 08032021 Removing 0 photos because of the 'same image' condition Total on : 0 Total off : 0.0 list_time_off Warning in study_and_display_distrib_list : min=max : 0.0 0.0 dist_desc Warning in study_and_display_distrib_list : min=max : -1 -1 begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 33 time used for this insertion : 0.02148723602294922 photos_removed : len 0 elapsed_time : remove_photo_duplicate 0.05094623565673828 To do, maybe not at the correct place ! .................................force hashtag to JRM elapsed_time : CREATE_PORT_BATCH_BY_HOUR 0.007241487503051758 NUMBER BATCH : 3 list_ponderation used : [1e-05, 1e-05, 1e-05, 1e-05, 1e-05] , list_hashtag_class_create_as_list : ['jrm'] We filter photos on hashtag condition ! We filter photos on hashtag condition ! We filter photos on hashtag condition ! We have rejected 0 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 0 elapsed_time : count_nb_balles_and_create_portfolio 0.0316922664642334 # DISPLAY ALL COLLECTED DATA : {'08032021': {'nb_upload': 33, 'nb_taggue_class': 0, 'nb_taggue_densite': 0, 'nb_descriptors': 0}} time spend for datou_step_exec : 0.4101870059967041 time spend to save output : 2.6464462280273438e-05 total time spend for step 1 : 0.4102134704589844 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1014106095, 1014106094, 1014106093, 1014105800, 1014105799, 1014105798, 1014105797, 1014105796, 1014105795, 1014105791, 1014105790, 1014105786, 1014105785, 1014105784, 1014105783, 1014105782, 1014105781, 1014105778, 1014105777, 1014099035, 1014098602, 1014098236, 1014097924, 1014097580, 1014097499, 1014097497, 1014097492, 1014054235, 1014054234, 1014054233, 1014054232, 1014054231, 1014054230] Looping around the photos to save general results len do output : 1 /3609515Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014106095', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014106094', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014106093', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105800', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105799', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105798', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105797', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105796', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105795', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105791', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105790', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105786', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105785', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105784', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105783', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105782', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105781', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105778', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014105777', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014099035', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014098602', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014098236', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014097924', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014097580', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014097499', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014097497', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014097492', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014054235', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014054234', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014054233', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014054232', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014054231', None, None, None, None, None, None) ('3181', None, None, None, None, None, None, None, None) ('3181', '3609515', '1014054230', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 34 time used for this insertion : 0.03735709190368652 save_final save missing photos in datou_result : After save, about to update current ! got : {'Rungis_JRM': []} expected : {'Rungis_JRM': [(0, 1), (1, 2), (2, 3)]} ERROR rubbia_horaire FAILED ############################### TEST rle_unique_nms_with_priority ################################ t Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : rle_unique_nms_with_priority list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.20351386070251465 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:rle_unique_nms_with_priority Sat Feb 15 05:27:39 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Begin step rle-unique-nms batch 1 Loaded 10 chid ids of type : 2804 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 10 nb_hashtags : 2 time to prepare the origin masks : 0.3790912628173828 time for calcul the mask position with numpy : 0.0050029754638671875 nb_pixel_total : 217207 time to create 1 rle with new method : 0.03775167465209961 time for calcul the mask position with numpy : 0.0028009414672851562 nb_pixel_total : 1008 time to create 1 rle with old method : 0.002351522445678711 time for calcul the mask position with numpy : 0.002682209014892578 nb_pixel_total : 751 time to create 1 rle with old method : 0.0017480850219726562 time for calcul the mask position with numpy : 0.0026769638061523438 nb_pixel_total : 722 time to create 1 rle with old method : 0.001695871353149414 time for calcul the mask position with numpy : 0.0025866031646728516 nb_pixel_total : 2949 time to create 1 rle with old method : 0.006693124771118164 time for calcul the mask position with numpy : 0.002714872360229492 nb_pixel_total : 497 time to create 1 rle with old method : 0.0011773109436035156 time for calcul the mask position with numpy : 0.0027310848236083984 nb_pixel_total : 1086 time to create 1 rle with old method : 0.002457857131958008 time for calcul the mask position with numpy : 0.0026514530181884766 nb_pixel_total : 1924 time to create 1 rle with old method : 0.0043926239013671875 time for calcul the mask position with numpy : 0.002630949020385742 nb_pixel_total : 413 time to create 1 rle with old method : 0.0009753704071044922 time for calcul the mask position with numpy : 0.002650022506713867 nb_pixel_total : 526 time to create 1 rle with old method : 0.0011992454528808594 create new chi : 0.08996844291687012 time to delete rle : 0.015643596649169922 batch 1 Loaded 10 chid ids of type : 2805 Number RLEs to save : 1674 TO DO : save crop sub photo not yet done ! save time : 0.24248528480529785 map_output_result : {998957128: (0.0, 'Should be the crop_list due to order', 0)} End step rle-unique-nms time spend for datou_step_exec : 0.9801058769226074 time spend to save output : 0.00011754035949707031 total time spend for step 1 : 0.9802234172821045 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {998957128: (0.0, 'Should be the crop_list due to order', 0)} Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : rle_unique_nms_with_priority list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.27431416511535645 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:rle_unique_nms_with_priority Sat Feb 15 05:27:40 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Begin step rle-unique-nms batch 1 Loaded 10 chid ids of type : 4169 seulement à utiliser dans la step consolidation batch 1 Loaded 10 chid ids of type : 2805 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 0.0333402156829834 map_output_result : {1066511071: (0.0, 'Should be the crop_list due to order', 0)} End step rle-unique-nms time spend for datou_step_exec : 0.39687585830688477 time spend to save output : 3.9577484130859375e-05 total time spend for step 1 : 0.3969154357910156 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1066511071: (0.0, 'Should be the crop_list due to order', 0)} Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : rle_unique_nms_with_priority list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.21190905570983887 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:rle_unique_nms_with_priority Sat Feb 15 05:27:41 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Begin step rle-unique-nms batch 1 Loaded 91 chid ids of type : 2596 +++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 43 nb_hashtags : 2 time to prepare the origin masks : 29.300936222076416 time for calcul the mask position with numpy : 0.24169135093688965 nb_pixel_total : 5233657 time to create 1 rle with new method : 0.4918477535247803 time for calcul the mask position with numpy : 0.03388381004333496 nb_pixel_total : 11972 time to create 1 rle with old method : 0.027672767639160156 time for calcul the mask position with numpy : 0.032648324966430664 nb_pixel_total : 15054 time to create 1 rle with old method : 0.034502267837524414 time for calcul the mask position with numpy : 0.03325605392456055 nb_pixel_total : 13954 time to create 1 rle with old method : 0.03151535987854004 time for calcul the mask position with numpy : 0.03341197967529297 nb_pixel_total : 4888 time to create 1 rle with old method : 0.011225223541259766 time for calcul the mask position with numpy : 0.044249773025512695 nb_pixel_total : 1188492 time to create 1 rle with new method : 0.3769834041595459 time for calcul the mask position with numpy : 0.03480076789855957 nb_pixel_total : 184585 time to create 1 rle with new method : 0.3905978202819824 time for calcul the mask position with numpy : 0.032828569412231445 nb_pixel_total : 18620 time to create 1 rle with old method : 0.04125833511352539 time for calcul the mask position with numpy : 0.033442020416259766 nb_pixel_total : 62945 time to create 1 rle with old method : 0.14312052726745605 time for calcul the mask position with numpy : 0.03405427932739258 nb_pixel_total : 9427 time to create 1 rle with old method : 0.022748708724975586 time for calcul the mask position with numpy : 0.034273624420166016 nb_pixel_total : 9081 time to create 1 rle with old method : 0.019994735717773438 time for calcul the mask position with numpy : 0.03188347816467285 nb_pixel_total : 15987 time to create 1 rle with old method : 0.03457522392272949 time for calcul the mask position with numpy : 0.03268289566040039 nb_pixel_total : 33276 time to create 1 rle with old method : 0.0723104476928711 time for calcul the mask position with numpy : 0.03206610679626465 nb_pixel_total : 17533 time to create 1 rle with old method : 0.03771328926086426 time for calcul the mask position with numpy : 0.032094478607177734 nb_pixel_total : 4876 time to create 1 rle with old method : 0.01447749137878418 time for calcul the mask position with numpy : 0.03485417366027832 nb_pixel_total : 25226 time to create 1 rle with old method : 0.05450153350830078 time for calcul the mask position with numpy : 0.031126022338867188 nb_pixel_total : 30773 time to create 1 rle with old method : 0.06382012367248535 time for calcul the mask position with numpy : 0.03133034706115723 nb_pixel_total : 65671 time to create 1 rle with old method : 0.1521470546722412 time for calcul the mask position with numpy : 0.038118600845336914 nb_pixel_total : 12230 time to create 1 rle with old method : 0.031614065170288086 time for calcul the mask position with numpy : 0.03298473358154297 nb_pixel_total : 29560 time to create 1 rle with old method : 0.06742548942565918 time for calcul the mask position with numpy : 0.032796621322631836 nb_pixel_total : 14310 time to create 1 rle with old method : 0.031380414962768555 time for calcul the mask position with numpy : 0.03301358222961426 nb_pixel_total : 15117 time to create 1 rle with old method : 0.03355121612548828 time for calcul the mask position with numpy : 0.04038405418395996 nb_pixel_total : 301487 time to create 1 rle with new method : 0.3255898952484131 time for calcul the mask position with numpy : 0.0323491096496582 nb_pixel_total : 29821 time to create 1 rle with old method : 0.06472158432006836 time for calcul the mask position with numpy : 0.032811641693115234 nb_pixel_total : 40299 time to create 1 rle with old method : 0.08870410919189453 time for calcul the mask position with numpy : 0.032668113708496094 nb_pixel_total : 12680 time to create 1 rle with old method : 0.028395652770996094 time for calcul the mask position with numpy : 0.03171133995056152 nb_pixel_total : 9449 time to create 1 rle with old method : 0.020267724990844727 time for calcul the mask position with numpy : 0.032317161560058594 nb_pixel_total : 15168 time to create 1 rle with old method : 0.03818655014038086 time for calcul the mask position with numpy : 0.0327298641204834 nb_pixel_total : 11140 time to create 1 rle with old method : 0.030516624450683594 time for calcul the mask position with numpy : 0.034860849380493164 nb_pixel_total : 29065 time to create 1 rle with old method : 0.06553006172180176 time for calcul the mask position with numpy : 0.03328967094421387 nb_pixel_total : 22774 time to create 1 rle with old method : 0.051149845123291016 time for calcul the mask position with numpy : 0.03515505790710449 nb_pixel_total : 13880 time to create 1 rle with old method : 0.03059220314025879 time for calcul the mask position with numpy : 0.03435182571411133 nb_pixel_total : 155366 time to create 1 rle with new method : 0.34574246406555176 time for calcul the mask position with numpy : 0.03700065612792969 nb_pixel_total : 63941 time to create 1 rle with old method : 0.13988399505615234 time for calcul the mask position with numpy : 0.03256845474243164 nb_pixel_total : 7836 time to create 1 rle with old method : 0.017262935638427734 time for calcul the mask position with numpy : 0.03178691864013672 nb_pixel_total : 7460 time to create 1 rle with old method : 0.017112016677856445 time for calcul the mask position with numpy : 0.0331575870513916 nb_pixel_total : 44600 time to create 1 rle with old method : 0.09876132011413574 time for calcul the mask position with numpy : 0.03279519081115723 nb_pixel_total : 11879 time to create 1 rle with old method : 0.026927709579467773 time for calcul the mask position with numpy : 0.03598809242248535 nb_pixel_total : 44195 time to create 1 rle with old method : 0.09833025932312012 time for calcul the mask position with numpy : 0.03294515609741211 nb_pixel_total : 23652 time to create 1 rle with old method : 0.05174374580383301 time for calcul the mask position with numpy : 0.03314328193664551 nb_pixel_total : 30006 time to create 1 rle with old method : 0.06975722312927246 time for calcul the mask position with numpy : 0.03346395492553711 nb_pixel_total : 15880 time to create 1 rle with old method : 0.03589677810668945 time for calcul the mask position with numpy : 0.03301358222961426 nb_pixel_total : 29845 time to create 1 rle with old method : 0.06712794303894043 time for calcul the mask position with numpy : 0.03426694869995117 nb_pixel_total : 144263 time to create 1 rle with old method : 0.31838274002075195 create new chi : 6.037065267562866 time to delete rle : 0.3787496089935303 batch 1 Loaded 44 chid ids of type : 2805 Number RLEs to save : 27884 TO DO : save crop sub photo not yet done ! save time : 5.112599611282349 map_output_result : {996751167: (1.0, 'Should be the crop_list due to order', 1.0)} End step rle-unique-nms time spend for datou_step_exec : 41.08974003791809 time spend to save output : 0.00019621849060058594 total time spend for step 1 : 41.08993625640869 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {996751167: (1.0, 'Should be the crop_list due to order', 1.0)} batch 1 Loaded 54 chid ids of type : 2805 ############################### TEST random_deformation ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : random_deformation list_input_json : [] origin We have 1 , BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.09644150733947754 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:random_deformation Sat Feb 15 05:28:26 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec beginning of datou step random deformation get user info for portfolio 3288640 About to upload 4 photos upload in portfolio : 3287159 init cache_photo without model_param we have 4 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593708_3820514 we have uploaded 4 photos in the portfolio 3287159 time of upload the photos Elapsed time : 1.2820312976837158 time spend for datou_step_exec : 3.3646128177642822 time spend to save output : 7.772445678710938e-05 total time spend for step 1 : 3.3646905422210693 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : random_deformation we use saveGeneral [1006293201] Looping around the photos to save general results len do output : 4 /1337814799Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814800Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814801Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1337814802Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('2896', None, None, None, None, None, None, None, None) ('2896', '3288640', '1006293201', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 13 time used for this insertion : 0.013568878173828125 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1337814799: ['1006293201', 'temp/1006293201_random_deformation_0.png', []], 1337814800: ['1006293201', 'temp/1006293201_random_deformation_1.png', []], 1337814801: ['1006293201', 'temp/1006293201_random_deformation_2.png', []], 1337814802: ['1006293201', 'temp/1006293201_random_deformation_3.png', []]} name 'urllib' is not defined can't unload the photo : 1006293201 t ############################### TEST tile ################################ test tile avec chi rectangles, rles, polygones Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : tile list_input_json : [] origin We have 1 , BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.39165163040161133 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:tile Sat Feb 15 05:28:30 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec verbose : False param_json : {'ETA': 3600, 'new_width': 640, 'new_height': 640, 'token': '5d93a4b2b749464f208c339a1324b78f', 'stride': 0, 'stride_relative': 0, 'portfolio_name': 'results_test_tile', 'crop_hashtag_type_tiled': 3243, 'crop_hashtag_type': 3242, 'arg_aux_upload': {'type_upload': 'python'}, 'host': 'www.fotonower.com'} type(crop_hashtag_type) : type(crop_hashtag_type_tiled) : We consider crop_hashtag_type is an integer ! map_chi_type_to_chi_type_cropped : {3242: 3243} TO DEPRECATE VR 14-6-18 map_filenames : {1008283903: 'temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53.jpg'} list_pids : 1 list_pids : 2 list_subpids to replace list_pids : 0 batch 1 Loaded 2 chid ids of type : 3242 ++https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=results_test_tile&access_token=5d93a4b2b749464f208c339a1324b78f created feed_id_new_photos : 20582970 with name results_test_tile feed_id_new_photos : 20582970 filename : temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53.jpg photo_id : 1008283903 height_image_input : 2464 width_image_input : 3280 new_width : 640 new_height : 640 stride : 0 stride_relative : 0 chi to copy from the main photo to the tiled photo input_chi_for_this_image_as_chi : 2 list_bib_to_crops : 24 [(0, 640, 0, 640, 0), (0, 640, 640, 1280, 1), (0, 640, 1280, 1920, 2), (0, 640, 1824, 2464, 3), (640, 1280, 0, 640, 4), (640, 1280, 640, 1280, 5), (640, 1280, 1280, 1920, 6), (640, 1280, 1824, 2464, 7), (1280, 1920, 0, 640, 8), (1280, 1920, 640, 1280, 9), (1280, 1920, 1280, 1920, 10), (1280, 1920, 1824, 2464, 11), (1920, 2560, 0, 640, 12), (1920, 2560, 640, 1280, 13), (1920, 2560, 1280, 1920, 14), (1920, 2560, 1824, 2464, 15), (2560, 3200, 0, 640, 16), (2560, 3200, 640, 1280, 17), (2560, 3200, 1280, 1920, 18), (2560, 3200, 1824, 2464, 19), (2640, 3280, 0, 640, 20), (2640, 3280, 640, 1280, 21), (2640, 3280, 1280, 1920, 22), (2640, 3280, 1824, 2464, 23)] new_crops_tiles : 24 crop_transformed : 7 batch 1 Loaded 24 chid ids of type : 17 treat the image : temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53.jpg , 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23 before upload mediasElapsed time : 0.3318006992340088 on upload les photos avec python init cache_photo without model_param we have 24 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593718_3820514 we have uploaded 24 photos in the portfolio 20582970 Importing ! upload mediasElapsed time : 7.223343849182129 , 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23Saving 7 CHIs. batch 1 Loaded 7 chid ids of type : 3243 Number RLEs to save : 2937 TO DO : save crop sub photo not yet done ! end of tileElapsed time : 7.928942680358887 time spend for datou_step_exec : 15.355286359786987 time spend to save output : 4.410743713378906e-05 total time spend for step 1 : 15.355330467224121 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'1337814809': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_0.jpg'], '1337814810': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_1.jpg'], '1337814811': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_2.jpg'], '1337814812': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_3.jpg'], '1337814813': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_4.jpg'], '1337814814': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_5.jpg'], '1337814815': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_6.jpg'], '1337814816': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_7.jpg'], '1337814817': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_8.jpg'], '1337814818': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_9.jpg'], '1337814819': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_10.jpg'], '1337814820': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_11.jpg'], '1337814821': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_12.jpg'], '1337814822': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_13.jpg'], '1337814823': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_14.jpg'], '1337814824': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_15.jpg'], '1337814825': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_16.jpg'], '1337814826': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_17.jpg'], '1337814827': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_18.jpg'], '1337814828': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_19.jpg'], '1337814829': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_20.jpg'], '1337814830': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_21.jpg'], '1337814831': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_22.jpg'], '1337814832': ['temp/1739593710_3820514_1008283903_6d008d31a1477b2e98cbafa96bd48e53_23.jpg']} batch 1 Loaded 7 chid ids of type : 3243 ++++++++++++++fin du test de tile ############################### TEST rotate_chi ################################ test rotate avec chi rectangles, rles, polygones Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : rotate list_input_json : [] origin We have 1 , BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.8188028335571289 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:rotate Sat Feb 15 05:28:47 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step_rotate ! Warning, new_feed_id is empty ! We are in a linear step without datou_depend ! rotate photos of 0,90,180,270 degres batch 1 Loaded 16 chid ids of type : 3086 ++++++++++++++++ map_chi of length : 1 https://marlene.fotonower.com/api/v1/secured/portfolio/new?access_token=78d09a0790ec6ecbf119343125a81fdc feed_id_new_photos : 20582971 time for calcul the mask position with numpy : 0.010558843612670898 nb_pixel_total : 110633 time to create 1 rle with old method : 0.25347208976745605 .time for calcul the mask position with numpy : 0.01340627670288086 nb_pixel_total : 15826 time to create 1 rle with old method : 0.039150238037109375 .time for calcul the mask position with numpy : 0.008934736251831055 nb_pixel_total : 5286 time to create 1 rle with old method : 0.011847972869873047 .time for calcul the mask position with numpy : 0.009163379669189453 nb_pixel_total : 1633 time to create 1 rle with old method : 0.0037975311279296875 .time for calcul the mask position with numpy : 0.012265920639038086 nb_pixel_total : 105533 time to create 1 rle with old method : 0.22651267051696777 .time for calcul the mask position with numpy : 0.008585691452026367 nb_pixel_total : 4393 time to create 1 rle with old method : 0.009666681289672852 .time for calcul the mask position with numpy : 0.008947372436523438 nb_pixel_total : 632 time to create 1 rle with old method : 0.0015301704406738281 .time for calcul the mask position with numpy : 0.010681867599487305 nb_pixel_total : 62627 time to create 1 rle with old method : 0.14166641235351562 .time for calcul the mask position with numpy : 0.009764671325683594 nb_pixel_total : 33681 time to create 1 rle with old method : 0.07555222511291504 .time for calcul the mask position with numpy : 0.009389638900756836 nb_pixel_total : 37724 time to create 1 rle with old method : 0.08767819404602051 .time for calcul the mask position with numpy : 0.010330677032470703 nb_pixel_total : 48775 time to create 1 rle with old method : 0.1101527214050293 .time for calcul the mask position with numpy : 0.05213332176208496 nb_pixel_total : 1171703 time to create 1 rle with new method : 0.160186767578125 .time for calcul the mask position with numpy : 0.009176492691040039 nb_pixel_total : 2310 time to create 1 rle with old method : 0.005233287811279297 .time for calcul the mask position with numpy : 0.00879526138305664 nb_pixel_total : 2256 time to create 1 rle with old method : 0.0052297115325927734 .time for calcul the mask position with numpy : 0.009617328643798828 nb_pixel_total : 3112 time to create 1 rle with old method : 0.007027626037597656 .time for calcul the mask position with numpy : 0.008601903915405273 nb_pixel_total : 1662 time to create 1 rle with old method : 0.003875732421875 .Needs to change image size ! time for calcul the mask position with numpy : 0.011163949966430664 nb_pixel_total : 110633 time to create 1 rle with old method : 0.25448179244995117 .time for calcul the mask position with numpy : 0.02149224281311035 nb_pixel_total : 15826 time to create 1 rle with old method : 0.040064334869384766 .time for calcul the mask position with numpy : 0.009318113327026367 nb_pixel_total : 5286 time to create 1 rle with old method : 0.012351512908935547 .time for calcul the mask position with numpy : 0.008518218994140625 nb_pixel_total : 1633 time to create 1 rle with old method : 0.0037009716033935547 .time for calcul the mask position with numpy : 0.009490966796875 nb_pixel_total : 105533 time to create 1 rle with old method : 0.22234725952148438 .time for calcul the mask position with numpy : 0.009001016616821289 nb_pixel_total : 4393 time to create 1 rle with old method : 0.010093212127685547 .time for calcul the mask position with numpy : 0.009042501449584961 nb_pixel_total : 632 time to create 1 rle with old method : 0.0015749931335449219 .time for calcul the mask position with numpy : 0.009940147399902344 nb_pixel_total : 62627 time to create 1 rle with old method : 0.16553235054016113 .time for calcul the mask position with numpy : 0.009464740753173828 nb_pixel_total : 33681 time to create 1 rle with old method : 0.07697653770446777 .time for calcul the mask position with numpy : 0.009680986404418945 nb_pixel_total : 37724 time to create 1 rle with old method : 0.08493733406066895 .time for calcul the mask position with numpy : 0.00943446159362793 nb_pixel_total : 48775 time to create 1 rle with old method : 0.1074225902557373 .time for calcul the mask position with numpy : 0.03847956657409668 nb_pixel_total : 1171703 time to create 1 rle with new method : 0.13195204734802246 .time for calcul the mask position with numpy : 0.008750677108764648 nb_pixel_total : 2310 time to create 1 rle with old method : 0.005231618881225586 .time for calcul the mask position with numpy : 0.009356260299682617 nb_pixel_total : 2256 time to create 1 rle with old method : 0.005140781402587891 .time for calcul the mask position with numpy : 0.009498834609985352 nb_pixel_total : 3112 time to create 1 rle with old method : 0.006888151168823242 .time for calcul the mask position with numpy : 0.010256528854370117 nb_pixel_total : 1662 time to create 1 rle with old method : 0.003939151763916016 .time for calcul the mask position with numpy : 0.010418415069580078 nb_pixel_total : 110633 time to create 1 rle with old method : 0.2641007900238037 .time for calcul the mask position with numpy : 0.009354591369628906 nb_pixel_total : 15826 time to create 1 rle with old method : 0.03449678421020508 .time for calcul the mask position with numpy : 0.009094953536987305 nb_pixel_total : 5286 time to create 1 rle with old method : 0.015410184860229492 .time for calcul the mask position with numpy : 0.009078264236450195 nb_pixel_total : 1633 time to create 1 rle with old method : 0.003629922866821289 .time for calcul the mask position with numpy : 0.010898113250732422 nb_pixel_total : 105533 time to create 1 rle with old method : 0.23573732376098633 .time for calcul the mask position with numpy : 0.00916147232055664 nb_pixel_total : 4393 time to create 1 rle with old method : 0.010650157928466797 .time for calcul the mask position with numpy : 0.009421825408935547 nb_pixel_total : 632 time to create 1 rle with old method : 0.0015041828155517578 .time for calcul the mask position with numpy : 0.01000356674194336 nb_pixel_total : 62627 time to create 1 rle with old method : 0.143754243850708 .time for calcul the mask position with numpy : 0.009491682052612305 nb_pixel_total : 33681 time to create 1 rle with old method : 0.07604312896728516 .time for calcul the mask position with numpy : 0.00928187370300293 nb_pixel_total : 37724 time to create 1 rle with old method : 0.08333396911621094 .time for calcul the mask position with numpy : 0.0092315673828125 nb_pixel_total : 48775 time to create 1 rle with old method : 0.10425877571105957 .time for calcul the mask position with numpy : 0.03981733322143555 nb_pixel_total : 1171703 time to create 1 rle with new method : 0.13536453247070312 .time for calcul the mask position with numpy : 0.009882450103759766 nb_pixel_total : 2310 time to create 1 rle with old method : 0.005204439163208008 .time for calcul the mask position with numpy : 0.010186433792114258 nb_pixel_total : 2256 time to create 1 rle with old method : 0.005036830902099609 .time for calcul the mask position with numpy : 0.009672164916992188 nb_pixel_total : 3112 time to create 1 rle with old method : 0.00706171989440918 .time for calcul the mask position with numpy : 0.009535789489746094 nb_pixel_total : 1662 time to create 1 rle with old method : 0.003760814666748047 .Needs to change image size ! time for calcul the mask position with numpy : 0.010940790176391602 nb_pixel_total : 110633 time to create 1 rle with old method : 0.23121142387390137 .time for calcul the mask position with numpy : 0.009967565536499023 nb_pixel_total : 15826 time to create 1 rle with old method : 0.033411264419555664 .time for calcul the mask position with numpy : 0.009201526641845703 nb_pixel_total : 5286 time to create 1 rle with old method : 0.010851144790649414 .time for calcul the mask position with numpy : 0.009723901748657227 nb_pixel_total : 1633 time to create 1 rle with old method : 0.003558635711669922 .time for calcul the mask position with numpy : 0.009657621383666992 nb_pixel_total : 105533 time to create 1 rle with old method : 0.2139911651611328 .time for calcul the mask position with numpy : 0.010441780090332031 nb_pixel_total : 4393 time to create 1 rle with old method : 0.009124517440795898 .time for calcul the mask position with numpy : 0.009281158447265625 nb_pixel_total : 632 time to create 1 rle with old method : 0.0014438629150390625 .time for calcul the mask position with numpy : 0.010385751724243164 nb_pixel_total : 62627 time to create 1 rle with old method : 0.13351702690124512 .time for calcul the mask position with numpy : 0.010127544403076172 nb_pixel_total : 33681 time to create 1 rle with old method : 0.07554745674133301 .time for calcul the mask position with numpy : 0.008982658386230469 nb_pixel_total : 37724 time to create 1 rle with old method : 0.08033418655395508 .time for calcul the mask position with numpy : 0.009813547134399414 nb_pixel_total : 48775 time to create 1 rle with old method : 0.10627555847167969 .time for calcul the mask position with numpy : 0.05261707305908203 nb_pixel_total : 1171703 time to create 1 rle with new method : 0.12683343887329102 .time for calcul the mask position with numpy : 0.008639812469482422 nb_pixel_total : 2310 time to create 1 rle with old method : 0.0056018829345703125 .time for calcul the mask position with numpy : 0.008773326873779297 nb_pixel_total : 2256 time to create 1 rle with old method : 0.005194664001464844 .time for calcul the mask position with numpy : 0.009117364883422852 nb_pixel_total : 3112 time to create 1 rle with old method : 0.007222652435302734 .time for calcul the mask position with numpy : 0.008927345275878906 nb_pixel_total : 1662 time to create 1 rle with old method : 0.0037326812744140625 . About to upload 4 photos upload in portfolio : 20582971 init cache_photo without model_param we have 4 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593741_3820514 we have uploaded 4 photos in the portfolio 20582971 time of upload the photos Elapsed time : 1.8222057819366455 Len new_chis : 4 Len list_new_chi_with_photo_id : 64 of type : 3230 batch 1 Loaded 64 chid ids of type : 3230 Number RLEs to save : 24654 TO DO : save crop sub photo not yet done ! batch 1 Loaded 64 chid ids of type : 3230 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 64 chid ids of type : 3230 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 64 chid ids of type : 3230 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! time spend for datou_step_exec : 20.20368528366089 time spend to save output : 0.0001506805419921875 total time spend for step 1 : 20.20383596420288 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1337814842: ['1003369118', 'temp/1739593726_3820514_1003369118_58171420504d0b5f05a1233b6c515509_658263370.jpg', [, , , , , , , , , , , , , , , ]], 1337814843: ['1003369118', 'temp/1739593726_3820514_1003369118_58171420504d0b5f05a1233b6c515509_6582633790.jpg', [, , , , , , , , , , , , , , , ]], 1337814844: ['1003369118', 'temp/1739593726_3820514_1003369118_58171420504d0b5f05a1233b6c515509_65826337180.jpg', [, , , , , , , , , , , , , , , ]], 1337814845: ['1003369118', 'temp/1739593726_3820514_1003369118_58171420504d0b5f05a1233b6c515509_65826337270.jpg', [, , , , , , , , , , , , , , , ]]} batch 1 Loaded 64 chid ids of type : 3230 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++fin du test de rotate_chi Ayatollah of tests excluded it ! (Bon le prochain developpeur qui passe ici peut enlever ayatollah VR 11-2-21) name : rubbia_carac_pet_clair_0121 not run because too long ############################### TEST rubbia_carac_pet_clair_0121_no_cnn ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 6479 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 6480 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7445 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 6509 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 6479 doesn't seem to be define in the database( WARNING : type of input 1 of step 6480 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 6479 doesn't seem to be define in the database( WARNING : type of input 1 of step 7445 doesn't seem to be define in the database( WARNING : type of output 1 of step 7445 doesn't seem to be define in the database( WARNING : type of input 3 of step 6509 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! DataTypes for each output/input checked ! List Step Type Loaded in datou : merge_mask_thcl_custom, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final list_input_json : [] origin We have 1 , BBFFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 2 ; length of list_pids : 2 ; length of list_args : 2 time to download the photos : 0.22797274589538574 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 4 step1:merge_mask_thcl_custom Sat Feb 15 05:29:07 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Begin step merge_mask_thcl_custom batch 1 Loaded 82 chid ids of type : 2800 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++As expected we have just one thcl present begin to find the sub_photo_id : begin to find the sub_photo_id : batch 1 Loaded 76 chid ids of type : 2913 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! batch 1 Loaded 76 chid ids of type : 2913 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++End of step merge_mask_thcl_custom time spend for datou_step_exec : 2.5487966537475586 time spend to save output : 7.557868957519531e-05 total time spend for step 1 : 2.548872232437134 step2:rle_unique_nms_with_priority Sat Feb 15 05:29:10 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 43 chid ids of type : 2913 +++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 0 nb_hashtags : 2 time to prepare the origin masks : 2.2816390991210938 create new chi : 3.9577484130859375e-05 time to delete rle : 0.030181884765625 save time : 4.172325134277344e-05 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 2.36547589302063 create new chi : 4.458427429199219e-05 time to delete rle : 0.012041568756103516 save time : 2.09808349609375e-05 map_output_result : {1009068683: (0.002588053987919006, 'Should be the crop_list due to order', 0.005176107975838012), 1009068724: (0.002588053987919006, 'Should be the crop_list due to order', 0.0)} End step rle-unique-nms time spend for datou_step_exec : 5.153663158416748 time spend to save output : 0.00010752677917480469 total time spend for step 2 : 5.153770685195923 step3:ventilate_hashtags_in_portfolio Sat Feb 15 05:29:15 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 3373196 get user id for portfolio 3373196 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=3373196 AND mptpi.`type`=2913 AND mptpi.`min_score`=0.7 To do To do ! Use context local managing function ! time spend for datou_step_exec : 1.8439769744873047 time spend to save output : 4.839897155761719e-05 total time spend for step 3 : 1.8440253734588623 step4:final Sat Feb 15 05:29:17 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 2 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou step final ! Catched exception ! Connect or reconnect ! time spend for datou_step_exec : 0.11049866676330566 time spend to save output : 5.2928924560546875e-05 total time spend for step 4 : 0.11055159568786621 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False original output for save of step final : {1009068683: ('0.0025316977085267163',), 1009068724: ('0.0025316977085267163',)} new output for save of step final : {1009068683: ('0.0025316977085267163',), 1009068724: ('0.0025316977085267163',)} [1009068683, 1009068724] Looping around the photos to save general results len do output : 2 /1009068683.Didn't retrieve data . /1009068724.Didn't retrieve data . before output type Used above Used above Managing all output in save final without adding information in the mtr_datou_result ('2719', None, None, None, None, None, None, None, None) ('2719', '3373196', '1009068683', None, None, None, None, None, None) ('2719', None, None, None, None, None, None, None, None) ('2719', '3373196', '1009068724', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 0.02569746971130371 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 4 output : {1009068683: ('0.0025316977085267163',), 1009068724: ('0.0025316977085267163',)} {1009068683: ('0.0025316977085267163',), 1009068724: ('0.0025316977085267163',)} ############################### TEST rubbia_carac_jrm_no_mask_detect ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Step 7557 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 7556 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 7561 merge_mask_and_thcl is not consistent : 3 used against 1 in the step definition ! WARNING : number of inputs for step 7558 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7560 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7559 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7560 doesn't seem to be define in the database( WARNING : type of input 3 of step 7559 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7556 have datatype=6 whereas input 0 of step 7561 have datatype=20 WARNING : type of output 1 of step 7561 doesn't seem to be define in the database( WARNING : type of input 1 of step 7558 doesn't seem to be define in the database( WARNING : type of output 2 of step 7561 doesn't seem to be define in the database( WARNING : type of input 1 of step 7560 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : crop_condition, thcl, argmax, merge_mask_and_thcl, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final list_input_json : [] origin We have 1 , BBBBBFBFBFBFBFBFFBFBFBFBFFFFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 14 ; length of list_pids : 14 ; length of list_args : 14 time to download the photos : 1.1685945987701416 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 7 step1:crop_condition Sat Feb 15 05:29:18 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Loading chi in step crop with photo_hashtag_type : 3336 Loading chi in step crop for list_pids : 14 ! batch 1 Loaded 121 chid ids of type : 3336 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ begin to crop the class : teint_dans_la_masse param for this class : {'min_score': 0.7} filtre for class : teint_dans_la_masse hashtag_id of this class : 2107752385 map_result returned by crop_photo_return_map_crop : length : 0 About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! we have finished the crop for the class : teint_dans_la_masse begin to crop the class : autre_refus param for this class : {'min_score': 0.7} filtre for class : autre_refus hashtag_id of this class : 2107752406 map_result returned by crop_photo_return_map_crop : length : 0 About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! we have finished the crop for the class : autre_refus begin to crop the class : carton_gris param for this class : {'min_score': 0.7} filtre for class : carton_gris hashtag_id of this class : 2107753020 map_result returned by crop_photo_return_map_crop : length : 0 About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! we have finished the crop for the class : carton_gris begin to crop the class : cartonnette param for this class : {'min_score': 0.7} filtre for class : cartonnette hashtag_id of this class : 702398920 map_result returned by crop_photo_return_map_crop : length : 0 About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! we have finished the crop for the class : cartonnette begin to crop the class : carton_brun param for this class : {'min_score': 0.7} filtre for class : carton_brun hashtag_id of this class : 2107753024 map_result returned by crop_photo_return_map_crop : length : 0 About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! we have finished the crop for the class : carton_brun begin to crop the class : plastique param for this class : {'min_score': 0.7} filtre for class : plastique hashtag_id of this class : 492725882 begin to crop the class : kraft param for this class : {'min_score': 0.7} filtre for class : kraft hashtag_id of this class : 493202403 begin to crop the class : metal param for this class : {'min_score': 0.7} filtre for class : metal hashtag_id of this class : 492628673 time spend for datou_step_exec : 9.787991285324097 time spend to save output : 0.0006930828094482422 total time spend for step 1 : 9.788684368133545 step2:thcl Sat Feb 15 05:29:28 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure No keys ! Beginning of datou step Thcl ! no input time spend for datou_step_exec : 0.0005214214324951172 time spend to save output : 2.574920654296875e-05 total time spend for step 2 : 0.0005471706390380859 step3:argmax Sat Feb 15 05:29:28 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure No keys ! Beginning of datou_step Argmax ! no input time spend for datou_step_exec : 4.887580871582031e-05 time spend to save output : 8.58306884765625e-06 total time spend for step 3 : 5.745887756347656e-05 step4:merge_mask_and_thcl Sat Feb 15 05:29:28 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure No keys ! debut de la step merge mask and classif time spend for datou_step_exec : 0.00010371208190917969 time spend to save output : 1.621246337890625e-05 total time spend for step 4 : 0.00011992454528808594 step5:rle_unique_nms_with_priority Sat Feb 15 05:29:28 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 26 chid ids of type : 3418 ++++++++++++++++++++++++++++nb_obj : 0 nb_hashtags : 2 time to prepare the origin masks : 1.3666255474090576 create new chi : 0.006142377853393555 time to delete rle : 0.34083056449890137 save time : 1.5020370483398438e-05 nb_obj : 0 nb_hashtags : 2 time to prepare the origin masks : 1.719362735748291 create new chi : 0.010304450988769531 time to delete rle : 0.30853962898254395 save time : 1.9788742065429688e-05 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.0762343406677246 create new chi : 3.528594970703125e-05 time to delete rle : 0.33287596702575684 save time : 1.811981201171875e-05 nb_obj : 0 nb_hashtags : 2 time to prepare the origin masks : 1.1661696434020996 create new chi : 0.006478548049926758 time to delete rle : 0.4199984073638916 save time : 7.3909759521484375e-06 nb_obj : 0 nb_hashtags : 2 time to prepare the origin masks : 1.132803201675415 create new chi : 0.007077455520629883 time to delete rle : 0.6289985179901123 save time : 7.152557373046875e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 0.796147346496582 create new chi : 0.007846355438232422 time to delete rle : 0.5595762729644775 save time : 8.106231689453125e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.338911771774292 create new chi : 2.4080276489257812e-05 time to delete rle : 0.5035545825958252 save time : 8.106231689453125e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.6822412014007568 create new chi : 6.914138793945312e-05 time to delete rle : 0.44916701316833496 save time : 1.2636184692382812e-05 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 0.7606472969055176 create new chi : 0.007003068923950195 time to delete rle : 0.4667212963104248 save time : 2.3365020751953125e-05 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.014132022857666 create new chi : 3.4809112548828125e-05 time to delete rle : 0.8912794589996338 save time : 1.9550323486328125e-05 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.509467601776123 create new chi : 2.5510787963867188e-05 time to delete rle : 0.533048152923584 save time : 1.33514404296875e-05 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.1001479625701904 create new chi : 2.0503997802734375e-05 time to delete rle : 0.37584567070007324 save time : 7.62939453125e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 0.8024113178253174 create new chi : 0.0066378116607666016 time to delete rle : 0.41947150230407715 save time : 6.9141387939453125e-06 nb_obj : 0 nb_hashtags : 1 time to prepare the origin masks : 1.3380393981933594 create new chi : 3.981590270996094e-05 time to delete rle : 0.4418613910675049 save time : 3.361701965332031e-05 map_output_result : {1008921601: (0.005230650193135238, 'Should be the crop_list due to order', 0.01189037070001202), 1008921600: (0.005230650193135238, 'Should be the crop_list due to order', 0.012566967797237925), 1008922130: (0.005230650193135238, 'Should be the crop_list due to order', 0.009172696586949636), 1008922101: (0.005230650193135238, 'Should be the crop_list due to order', 0.001800476457962238), 1008922097: (0.005230650193135238, 'Should be the crop_list due to order', 0.0021337986371828908), 1008922095: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008922073: (0.005230650193135238, 'Should be the crop_list due to order', 0.0034527686490338928), 1008922072: (0.005230650193135238, 'Should be the crop_list due to order', 0.006595957396262274), 1008921657: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921656: (0.005230650193135238, 'Should be the crop_list due to order', 0.0018834633354450428), 1008921602: (0.005230650193135238, 'Should be the crop_list due to order', 0.011059624445676274), 1008922003: (0.005230650193135238, 'Should be the crop_list due to order', 0.010260185698447893), 1008922002: (0.005230650193135238, 'Should be the crop_list due to order', 0.0), 1008921786: (0.005230650193135238, 'Should be the crop_list due to order', 0.0024127929996832437)} End step rle-unique-nms time spend for datou_step_exec : 26.402034997940063 time spend to save output : 0.00012493133544921875 total time spend for step 5 : 26.402159929275513 step6:ventilate_hashtags_in_portfolio Sat Feb 15 05:29:54 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step ventilate_hashtags_in_portfolio : To implement ! To do loadFromThcl(), then load ParamDescType : thcl2456 thcls : [{'id': 2456, 'mtr_user_id': 31, 'name': 'learn_qualipapia_papier_refus_from_vlg_data_aug', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'papier,refus', 'svm_portfolios_learning': '3028087,3028251', 'photo_hashtag_type': 3049, 'photo_desc_type': 4999, 'type_classification': 'caffe', 'hashtag_id_list': '492668766,538914404'}] thcl {'id': 2456, 'mtr_user_id': 31, 'name': 'learn_qualipapia_papier_refus_from_vlg_data_aug', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'papier,refus', 'svm_portfolios_learning': '3028087,3028251', 'photo_hashtag_type': 3049, 'photo_desc_type': 4999, 'type_classification': 'caffe', 'hashtag_id_list': '492668766,538914404'} Update svm_hashtag_type_desc : 4999 Iterating over portfolio : 3364276 get user id for portfolio 3364276 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=3535038 AND mptpi.`type`=3418 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('refus','papier')) AND mptpi.`min_score`=0.7 To do To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=3364276 AND mptpi.`type`=3418 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('refus','papier')) AND mptpi.`min_score`=0.7 To do To do ! Use context local managing function ! time spend for datou_step_exec : 2.005645513534546 time spend to save output : 0.00012755393981933594 total time spend for step 6 : 2.0057730674743652 step7:final Sat Feb 15 05:29:56 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 2 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou step final ! time spend for datou_step_exec : 0.08860254287719727 time spend to save output : 4.220008850097656e-05 total time spend for step 7 : 0.08864474296569824 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False original output for save of step final : {1008921601: ('0.005252307643909098',), 1008921600: ('0.005252307643909098',), 1008922130: ('0.005252307643909098',), 1008922101: ('0.005252307643909098',), 1008922097: ('0.005252307643909098',), 1008922095: ('0.005252307643909098',), 1008922073: ('0.005252307643909098',), 1008922072: ('0.005252307643909098',), 1008921657: ('0.005252307643909098',), 1008921656: ('0.005252307643909098',), 1008921602: ('0.005252307643909098',), 1008922003: ('0.005252307643909098',), 1008922002: ('0.005252307643909098',), 1008921786: ('0.005252307643909098',)} new output for save of step final : {1008921601: ('0.005252307643909098',), 1008921600: ('0.005252307643909098',), 1008922130: ('0.005252307643909098',), 1008922101: ('0.005252307643909098',), 1008922097: ('0.005252307643909098',), 1008922095: ('0.005252307643909098',), 1008922073: ('0.005252307643909098',), 1008922072: ('0.005252307643909098',), 1008921657: ('0.005252307643909098',), 1008921656: ('0.005252307643909098',), 1008921602: ('0.005252307643909098',), 1008922003: ('0.005252307643909098',), 1008922002: ('0.005252307643909098',), 1008921786: ('0.005252307643909098',)} [1008921601, 1008921600, 1008922130, 1008922101, 1008922097, 1008922095, 1008922073, 1008922072, 1008921657, 1008921656, 1008921602, 1008922003, 1008922002, 1008921786] Looping around the photos to save general results len do output : 14 /1008921601.Didn't retrieve data . /1008921600.Didn't retrieve data . /1008922130.Didn't retrieve data . /1008922101.Didn't retrieve data . /1008922097.Didn't retrieve data . /1008922095.Didn't retrieve data . /1008922073.Didn't retrieve data . /1008922072.Didn't retrieve data . /1008921657.Didn't retrieve data . /1008921656.Didn't retrieve data . /1008921602.Didn't retrieve data . /1008922003.Didn't retrieve data . /1008922002.Didn't retrieve data . /1008921786.Didn't retrieve data . before output type Used above Used above Managing all output in save final without adding information in the mtr_datou_result ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921601', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921600', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922130', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922101', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922097', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922095', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922073', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922072', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921657', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921656', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921602', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922003', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008922002', None, None, None, None, None, None) ('3164', None, None, None, None, None, None, None, None) ('3164', '3364276', '1008921786', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 42 time used for this insertion : 0.022630929946899414 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 7 output : {1008921601: ('0.005252307643909098',), 1008921600: ('0.005252307643909098',), 1008922130: ('0.005252307643909098',), 1008922101: ('0.005252307643909098',), 1008922097: ('0.005252307643909098',), 1008922095: ('0.005252307643909098',), 1008922073: ('0.005252307643909098',), 1008922072: ('0.005252307643909098',), 1008921657: ('0.005252307643909098',), 1008921656: ('0.005252307643909098',), 1008921602: ('0.005252307643909098',), 1008922003: ('0.005252307643909098',), 1008922002: ('0.005252307643909098',), 1008921786: ('0.005252307643909098',)} {1008921601: ('0.005252307643909098',), 1008921600: ('0.005252307643909098',), 1008922130: ('0.005252307643909098',), 1008922101: ('0.005252307643909098',), 1008922097: ('0.005252307643909098',), 1008922095: ('0.005252307643909098',), 1008922073: ('0.005252307643909098',), 1008922072: ('0.005252307643909098',), 1008921657: ('0.005252307643909098',), 1008921656: ('0.005252307643909098',), 1008921602: ('0.005252307643909098',), 1008922003: ('0.005252307643909098',), 1008922002: ('0.005252307643909098',), 1008921786: ('0.005252307643909098',)} ############################### TEST ventilate_hashtags_in_portfolio ################################ DELETE FROM MTRUser.mtr_portfolio_photos where mtr_portfolio_id = 5486631; Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : ventilate_hashtags_in_portfolio list_input_json : [] origin We have 1 , we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 0.017005443572998047 About to test input to load Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:ventilate_hashtags_in_portfolio Sat Feb 15 05:29:57 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 5363525 get user id for portfolio 5363525 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=5363525 AND mptpi.`type`=4268 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_clair','error','environment')) AND mptpi.`min_score`=0.3 To do To do ! Use context local managing function ! time spend for datou_step_exec : 0.10889267921447754 time spend to save output : 0.00012230873107910156 total time spend for step 1 : 0.10901498794555664 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1075306598, 1075306564, 1075306534, 1075306522, 1075304668] Looping around the photos to save general results len do output : 1 /5363525. before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3070', None, None, None, None, None, None, None, None) ('3070', '5363525', '1075306598', None, None, None, None, None, None) ('3070', None, None, None, None, None, None, None, None) ('3070', '5363525', '1075306564', None, None, None, None, None, None) ('3070', None, None, None, None, None, None, None, None) ('3070', '5363525', '1075306534', None, None, None, None, None, None) ('3070', None, None, None, None, None, None, None, None) ('3070', '5363525', '1075306522', None, None, None, None, None, None) ('3070', None, None, None, None, None, None, None, None) ('3070', '5363525', '1075304668', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 0.04398179054260254 save_final save missing photos in datou_result : After save, about to update current ! Ayatollah of tests excluded it ! (Bon le prochain developpeur qui passe ici peut enlever ayatollah VR 11-2-21) name : merge_qualipapia_like not run because too long ############################### TEST poly_ro_rle ################################ test creation de rle a partir de polygon Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : poly_to_rle list_input_json : [] origin We have 1 , BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.18926191329956055 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:poly_to_rle Sat Feb 15 05:29:57 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec can't find the hashtag_type_input ,set the output_type same as the input_type batch 1 Loaded 16 chid ids of type : 3391 ++++++++++++++++time for calcul the mask position with numpy : 0.009048700332641602 nb_pixel_total : 110633 time to create 1 rle with old method : 0.2621898651123047 time for calcul the mask position with numpy : 0.007270336151123047 nb_pixel_total : 15826 time to create 1 rle with old method : 0.03638267517089844 time for calcul the mask position with numpy : 0.007332563400268555 nb_pixel_total : 5286 time to create 1 rle with old method : 0.012974262237548828 time for calcul the mask position with numpy : 0.007429838180541992 nb_pixel_total : 1633 time to create 1 rle with old method : 0.004060983657836914 time for calcul the mask position with numpy : 0.00823831558227539 nb_pixel_total : 105533 time to create 1 rle with old method : 0.24213552474975586 time for calcul the mask position with numpy : 0.0075380802154541016 nb_pixel_total : 4393 time to create 1 rle with old method : 0.01056981086730957 time for calcul the mask position with numpy : 0.0071027278900146484 nb_pixel_total : 632 time to create 1 rle with old method : 0.0016415119171142578 time for calcul the mask position with numpy : 0.00799107551574707 nb_pixel_total : 62627 time to create 1 rle with old method : 0.1396045684814453 time for calcul the mask position with numpy : 0.007250070571899414 nb_pixel_total : 33681 time to create 1 rle with old method : 0.07172322273254395 time for calcul the mask position with numpy : 0.007491350173950195 nb_pixel_total : 37724 time to create 1 rle with old method : 0.08356714248657227 time for calcul the mask position with numpy : 0.007529258728027344 nb_pixel_total : 48775 time to create 1 rle with old method : 0.11644172668457031 time for calcul the mask position with numpy : 0.04038214683532715 nb_pixel_total : 1171703 time to create 1 rle with new method : 0.23903608322143555 time for calcul the mask position with numpy : 0.007135868072509766 nb_pixel_total : 2310 time to create 1 rle with old method : 0.0052068233489990234 time for calcul the mask position with numpy : 0.007338047027587891 nb_pixel_total : 2256 time to create 1 rle with old method : 0.005774497985839844 time for calcul the mask position with numpy : 0.006918668746948242 nb_pixel_total : 3112 time to create 1 rle with old method : 0.007097005844116211 time for calcul the mask position with numpy : 0.007511138916015625 nb_pixel_total : 1662 time to create 1 rle with old method : 0.004130363464355469 batch 1 Loaded 16 chid ids of type : 3391 ++++++++++++++++Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! time spend for datou_step_exec : 1.6840105056762695 time spend to save output : 0.0001163482666015625 total time spend for step 1 : 1.684126853942871 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1003369118: 'temp/1739593797_3820514_1003369118_58171420504d0b5f05a1233b6c515509_65826337.jpg'} batch 1 Loaded 16 chid ids of type : 3391 ++++++++++++++++fin du test de poly_to_rle ############################### TEST cod_sts ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : split_time_score list_input_json : [] origin We have 1 , we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 1.156911849975586 About to test input to load Calling datou_exec Inside datou_exec : verbose : False we use local cache db, so we are in local job, but when commit will be implemented for local cache db, we could again use save number of steps : 1 step1:split_time_score Sat Feb 15 05:30:00 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec TODO : Insert select and so on Begin split_port_in_batch_balle thcls : [{'id': 861, 'mtr_user_id': 31, 'name': 'Rungis_class_dechets_1212', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'Rungis_Aluminium,Rungis_Carton,Rungis_Papier,Rungis_Plastique_clair,Rungis_Plastique_dur,Rungis_Plastique_fonce,Rungis_Tapis_vide,Rungis_Tetrapak', 'svm_portfolios_learning': '1160730,571842,571844,571839,571933,571840,571841,572307', 'photo_hashtag_type': 999, 'photo_desc_type': 3963, 'type_classification': 'caffe', 'hashtag_id_list': '2107751280,2107750907,2107750908,2107750909,2107750910,2107750911,2107750912,2107750913'}] thcls : [{'id': 758, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 856, 'photo_desc_type': 3853, 'type_classification': 'caffe', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] (('48', 4), ('42', 3)) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {} 17082021 4453840 Nombre de photos uploadées : 7 / 23040 (0%) 17082021 4453840 Nombre de photos taguées (types de déchets): 0 / 7 (0%) 17082021 4453840 Nombre de photos taguées (volume) : 0 / 7 (0%) elapsed_time : load_data_split_time_score 8.821487426757812e-06 elapsed_time : order_list_meta_photo_and_scores 1.621246337890625e-05 ??????? elapsed_time : fill_and_build_computed_from_old_data 0.0012438297271728516 elapsed_time : insert_dashboard_record_day_entry 0.26552438735961914 TODO 20-09-21 https://github.com/fotonower/raspi-fotonower-x/issues/253#issuecomment-923099773 TODO 20-9-21 TODO 20-9-21 ***** BEGIN SPLIT TIME ***** False 1629158400.0 `1629186488.0 1629186300.0 `1629186488.0 1629186300.0 `1629186512.0 1629186300.0 `1629186512.0 1629186300.0 `1629189733.0 1629189600.0 `1629189733.0 1629189600.0 `1629189736.0 1629189600.0 list printed: [[0, 1, 2, 3], [4, 5, 6]] forced_hashtag: jrm force hashtag to jrm elapsed_time : SPLIT_TIME 0.006276369094848633 ***** END SPLIT TIME ***** NUMBER BATCH : 2 list_ponderation used : [0.001, 0.001, 0.001, 0.001, 0.001] , list_hashtag_class_create_as_list : ['jrm'] ERROR missing amount info ERROR missing amount info ERROR missing amount info ERROR missing amount info result_one_balle_Type_jrm:{'day': '17082021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 24.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20210817_094808.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 ERROR missing amount info ERROR missing amount info ERROR missing amount info result_one_balle_Type_jrm:{'day': '17082021', 'map_nb_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 3.0, 'nb_balles_papier': 0, 'begin_time_port': 'IMG_20210817_104213.jpg'} Production hashtag (incorrect ponderation at 20-10-18) : 0 We have rejected 0 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 2 list_same_port_ids : [4453926] find same portfolio which already exist 4453926 , we will use it list_same_port_ids : [4652336] find same portfolio which already exist 4652336 , we will use it Qualite : 0.5219450480102605 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4453926 AND mptpi.`type`=4038 To do Qualite : 0.1657989516453152 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 8564 mask_detect is not consistent : 4 used against 2 in the step definition ! WARNING : number of outputs for step 8572 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8573 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 8567 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 8567 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 8566 argmax have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 8568 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8569 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 9453 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 9453 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 8571 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 8570 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 8570 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 8574 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Step 9126 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 8564 doesn't seem to be define in the database( WARNING : type of input 2 of step 8567 doesn't seem to be define in the database( WARNING : output 0 of step 8566 have datatype=6 whereas input 2 of step 8568 have datatype=5 WARNING : output 1 of step 8564 have datatype=2 whereas input 1 of step 8568 have datatype=7 WARNING : output 0 of step 8564 have datatype=16 whereas input 0 of step 8568 have datatype=1 WARNING : type of output 2 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 8568 doesn't seem to be define in the database( WARNING : type of input 1 of step 8571 doesn't seem to be define in the database( WARNING : type of output 1 of step 8571 doesn't seem to be define in the database( WARNING : type of input 3 of step 8570 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 8571 have datatype=10 whereas input 2 of step 8574 have datatype=6 WARNING : type of input 2 of step 9453 doesn't seem to be define in the database( WARNING : output 1 of step 8569 have datatype=7 whereas input 2 of step 9453 have datatype=None WARNING : type of output 3 of step 9453 doesn't seem to be define in the database( WARNING : type of input 2 of step 8571 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8572 doesn't seem to be define in the database( WARNING : type of output 3 of step 8564 doesn't seem to be define in the database( WARNING : type of input 1 of step 8573 doesn't seem to be define in the database( WARNING : type of output 1 of step 8572 doesn't seem to be define in the database( WARNING : type of input 3 of step 8567 doesn't seem to be define in the database( WARNING : type of output 1 of step 8573 doesn't seem to be define in the database( WARNING : type of input 4 of step 8567 doesn't seem to be define in the database( DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4652336 AND mptpi.`type`=4038 To do elapsed_time : count_nb_balles_and_create_portfolio 4.049018144607544 # DISPLAY ALL COLLECTED DATA : {'17082021': {'nb_upload': 7, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}} time spend for datou_step_exec : 4.370237112045288 time spend to save output : 0.00011229515075683594 total time spend for step 1 : 4.370349407196045 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1050302186, 1050302153, 1050302152, 1050302146, 1050302113, 1050302110, 1050302106] Looping around the photos to save general results len do output : 1 /4453840Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302186', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302153', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302152', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302146', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302113', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302110', None, None, None, None, None, None) ('3781', None, None, None, None, None, None, None, None) ('3781', '4453840', '1050302106', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 8 time used for this insertion : 0.050246477127075195 save_final save missing photos in datou_result : After save, about to update current ! Result test cod : {4453840: ([[0, 1, 2, 3], [4, 5, 6]], {'Rungis_jrm': [(0, 1), (1, 2)]}, {4453926: {'list_of_photos': [1050302106, 1050302146, 1050302110, 1050302152], 'hashtag': 'jrm'}, 4652336: {'list_of_photos': [1050302113, 1050302153, 1050302186], 'hashtag': 'jrm'}}, {2107757407: 7}, {'amount_uploaded_and_tagged': {'17082021': {'nb_upload': 7, 'nb_taggue_class': 0, 'nb_taggue_densite': 0}}, 'map_amount_per_hashtag': {'Rungis_jrm': [(0, 1), (1, 2)]}, 'count': {'Rungis_jrm': [(0, 1), (1, 2)]}})}| ############################### TEST cod_download ################################ warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data [] [] ############################### TEST sendgrid ################################ test sendgrid senders@fotonower.com no problem of authentification, for test if the email can be received, try with a real receiver fin du test de sendgrid ############################### TEST rym_consolidate ################################ test_rym_consolidate Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 9321 copy_chis is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 9357 consolidate_hashtags_from_manual_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 9318 rle_unique_nms_with_priority is not consistent : 3 used against 1 in the step definition ! WARNING : number of outputs for step 9318 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 9410 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 9319 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 9328 blur_detection have less inputs used (0) than in the step definition (1) : maybe we manage optionnal inputs ! Step 9327 brightness have less inputs used (0) than in the step definition (1) : maybe we manage optionnal inputs ! Step 9326 send_mail_cod have less inputs used (4) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 9321 have datatype=11 whereas input 0 of step 9318 have datatype=2 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 9357 doesn't seem to be define in the database( WARNING : type of input 1 of step 9318 doesn't seem to be define in the database( WARNING : type of output 1 of step 9357 doesn't seem to be define in the database( WARNING : type of input 3 of step 9319 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 9410 doesn't seem to be define in the database( WARNING : output 1 of step 9318 have datatype=7 whereas input 1 of step 9410 have datatype=None WARNING : type of output 1 of step 9410 doesn't seem to be define in the database( WARNING : type of input 4 of step 9319 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 9410 have datatype=10 whereas input 3 of step 9326 have datatype=6 WARNING : type of output 1 of step 9321 doesn't seem to be define in the database( WARNING : type of input 1 of step 9357 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : copy_chis, consolidate_hashtags_from_manual_portfolio, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final, blur_detection, brightness, send_mail_cod list_input_json : [] origin We have 1 , BBFFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 2 ; length of list_pids : 2 ; length of list_args : 2 time to download the photos : 0.7319252490997314 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 8 step1:copy_chis Sat Feb 15 05:30:09 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Begin step datou_step_copy_crop batch 1 Loaded 0 chid ids of type : 0 time spend for datou_step_exec : 1.2919962406158447 time spend to save output : 4.38690185546875e-05 total time spend for step 1 : 1.2920401096343994 step2:consolidate_hashtags_from_manual_portfolio Sat Feb 15 05:30:10 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step consolidate_hashtags_from_manual_portfolio Iterating over portfolio : 4709558 on est dans le IF portfolio mere 26T SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4709558 AND mptpi.`type`=4016 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_clair','etiquette','bouchon','pehd','barquette_avec_film','metal','pet_fonce','aluminium','carton','film_plastique','papier','autre')) To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4709558 AND mptpi.`type`=4016 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_clair','etiquette','bouchon','pehd','barquette_avec_film','metal','pet_fonce','aluminium','carton','film_plastique','papier','autre')) To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4683188 AND mptpi.`type`=4016 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('pet_clair','etiquette','bouchon','pehd','barquette_avec_film','metal','pet_fonce','aluminium','carton','film_plastique','papier','autre')) To do TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673496 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673497 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673498 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673500 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673501 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673502 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673503 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673504 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673505 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673506 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673507 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4673508 AND mpp.hide_status=0 ORDER BY ph.size desc To test ! Use context local managing function ! time spend for datou_step_exec : 117.54359316825867 time spend to save output : 8.869171142578125e-05 total time spend for step 2 : 117.54368185997009 step3:rle_unique_nms_with_priority Sat Feb 15 05:32:08 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 65 chid ids of type : 4016 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++nb_obj : 0 nb_hashtags : 3 time to prepare the origin masks : 20.708173036575317 create new chi : 5.793571472167969e-05 time to delete rle : 0.4916703701019287 save time : 3.62396240234375e-05 nb_obj : 0 nb_hashtags : 3 time to prepare the origin masks : 19.45438051223755 create new chi : 4.649162292480469e-05 time to delete rle : 0.4487435817718506 save time : 4.38690185546875e-05 map_output_result : {1057289546: (0.0, 'Should be the crop_list due to order', 0.0), 1057289467: (0.0, 'Should be the crop_list due to order', 0.0)} End step rle-unique-nms time spend for datou_step_exec : 44.973204374313354 time spend to save output : 0.00031828880310058594 total time spend for step 3 : 44.973522663116455 step4:ventilate_hashtags_in_portfolio Sat Feb 15 05:32:53 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 4709558 get user id for portfolio 4709558 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=4709558 AND mptpi.`type`=4016 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('environnement','mal_croppe','pet_clair','etiquette','bouchon','pehd','barquette_avec_film','metal','pet_fonce','aluminium','carton','film_plastique','papier','autre')) AND mptpi.`min_score`=0.7 To do To do ! Use context local managing function ! time spend for datou_step_exec : 0.5602383613586426 time spend to save output : 8.296966552734375e-05 total time spend for step 4 : 0.5603213310241699 step5:final Sat Feb 15 05:32:53 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 2 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou step final ! time spend for datou_step_exec : 0.14235591888427734 time spend to save output : 6.961822509765625e-05 total time spend for step 5 : 0.142425537109375 step6:blur_detection Sat Feb 15 05:32:54 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step blur_detection toutes les photos sont déjà traitées, on saute les calculs time spend for datou_step_exec : 0.6416306495666504 time spend to save output : 6.937980651855469e-05 total time spend for step 6 : 0.641700029373169 step7:brightness Sat Feb 15 05:32:54 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure inside step calcul brightness toutes les photos sont déjà traitées, on saute les calculs time spend for datou_step_exec : 0.10549354553222656 time spend to save output : 4.458427429199219e-05 total time spend for step 7 : 0.10553812980651855 step8:send_mail_cod Sat Feb 15 05:32:54 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 complete output_args for input 1 complete output_args for input 2 Inconsistent number of input and output, step which parrallelize and manage error in input by avoiding sending an output for this data can't be used in tree dependencies of input and output complete output_args for input 3 We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure dans la step send mail cod work_area: /data_2/data_log/job/2025/February/15022025/coverage in order to get the selector url, please entre the license of selector results_COD_P4709558_15-02-2025_05_32_54.pdf 4673494 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette46734941739593974 4673496 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette46734961739593975 4673497 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette46734971739593976 4673498 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette46734981739593978 4673500 change filename to text .change filename to text .imagette46735001739593979 4673501 change filename to text .imagette46735011739593980 4673502 imagette46735021739593980 4673503 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette46735031739593980 4673504 imagette46735041739593981 4673505 imagette46735051739593981 4673506 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette46735061739593982 4673507 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette46735071739593983 4673508 change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .change filename to text .imagette46735081739593984 velour_link : ce batch n'est pas dans un dashboard, on n'envoi pas de mail. si vous voulez quand même des mail , veuillez configurer no_mail = 2 args[1057289546] : ((1057289546, -4.333383571220791, 492609224), (1057289546, -0.5998675991292823, 501862349), '0.009511382621534484') apple ((1057289546, -4.333383571220791, 492609224), (1057289546, -0.5998675991292823, 501862349), '0.009511382621534484') We are sending mail with results at marine@fotonower.com args[1057289467] : ((1057289467, -4.424440243329978, 492609224), (1057289467, -0.4062218880770088, 496442774), '0.009511382621534484') apple ((1057289467, -4.424440243329978, 492609224), (1057289467, -0.4062218880770088, 496442774), '0.009511382621534484') We are sending mail with results at marine@fotonower.com refus_total : 0.009511382621534484 SELECT ph.photo_id,ph.url,ph.username,ph.uploaded_at,ph.text FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4709558 AND mpp.hide_status=0 ORDER BY mpp.order LIMIT 0, 1000 current_id not found list index out of range start upload file to ovh https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_COD_P4709558_15-02-2025_05_32_54.pdf results_COD_P4709558_15-02-2025_05_32_54.pdf uploaded to url https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_COD_P4709558_15-02-2025_05_32_54.pdf start insert file to database insert into MTRUser.mtr_files (mtd_id,mtr_portfolio_id,text,url,format,tags,file_size,value) values ('3818','4709558','results_COD_P4709558_15-02-2025_05_32_54.pdf','https://storage.sbg.cloud.ovh.net/v1/AUTH_3b171620e76e4af496c5fd050759c9f0/media.fotonower.com/results_COD_P4709558_15-02-2025_05_32_54.pdf','pdf','','0.48','0.009511382621534484') time spend for datou_step_exec : 13.10474944114685 time spend to save output : 3.838539123535156e-05 total time spend for step 8 : 13.104787826538086 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 8 output : fin du test de rym_consolidate ############################### TEST generate_new_image_add_crop ################################ test_generate_new_image_add_crop Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : generate_new_image list_input_json : [] origin We have 1 , BBBFFFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 3 ; length of list_pids : 3 ; length of list_args : 3 time to download the photos : 0.16866326332092285 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:generate_new_image Sat Feb 15 05:33:10 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4789595 ORDER BY ph.size desc We have 1 , we need 3 photos there is already 3 photos exist in our local_cache we have to download 0 photos we have successful downloaded 0 photos there are 0 photos missing finally, we can get 3 photo needed from our local_cache list of photo_id_missing : [] batch 1 Loaded 3 chid ids of type : 4021 +++we need 2 photos there is already 2 photos exist in our local_cache we have to download 0 photos we have successful downloaded 0 photos there are 0 photos missing finally, we can get 2 photo needed from our local_cache list of photo_id_missing : [] begin to treate photo :1057314774 add chi : 2208326713 , rotate : 113 (839, 839) (426, 550, 461, 580) (119, 124, 3) (119, 124) (839, 839, 3) time for calcul the mask position with numpy : 0.0022077560424804688 nb_pixel_total : 6831 time to create 1 rle with old method : 0.019994020462036133 batch 1 Loaded 0 chid ids of type : 0 time for calcul the mask position with numpy : 0.0013003349304199219 nb_pixel_total : 6831 time to create 1 rle with old method : 0.01538705825805664 begin to treate photo :1057314768 add chi : 2208326711 , rotate : 155 (850, 850) (561, 849, 163, 659) (496, 288, 3) (496, 288) (850, 850, 3) time for calcul the mask position with numpy : 0.0013051033020019531 nb_pixel_total : 65393 time to create 1 rle with old method : 0.14060640335083008 batch 1 Loaded 2 chid ids of type : 4021 ++time for calcul the mask position with numpy : 0.0018939971923828125 nb_pixel_total : 68595 time to create 1 rle with old method : 0.14913153648376465 time for calcul the mask position with numpy : 0.0015473365783691406 nb_pixel_total : 65393 time to create 1 rle with old method : 0.14809131622314453 time for calcul the mask position with numpy : 0.0012390613555908203 nb_pixel_total : 8755 time to create 1 rle with old method : 0.0200808048248291 begin to treate photo :1057314766 add chi : 2208326717 , rotate : 45 (905, 905) (532, 831, 269, 675) (406, 299, 3) (406, 299) (905, 905, 3) time for calcul the mask position with numpy : 0.0015521049499511719 nb_pixel_total : 80908 time to create 1 rle with old method : 0.17917704582214355 batch 1 Loaded 3 chid ids of type : 4021 +++time for calcul the mask position with numpy : 0.0020799636840820312 nb_pixel_total : 63323 time to create 1 rle with old method : 0.13827109336853027 time for calcul the mask position with numpy : 0.0014863014221191406 nb_pixel_total : 33045 time to create 1 rle with old method : 0.07390546798706055 time for calcul the mask position with numpy : 0.00138092041015625 nb_pixel_total : 6274 time to create 1 rle with old method : 0.013634681701660156 time for calcul the mask position with numpy : 0.0016870498657226562 nb_pixel_total : 80908 time to create 1 rle with old method : 0.17341852188110352 init cache_photo without model_param we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593993_3820514 we have uploaded 1 photos in the portfolio 4789106 batch 1 Loaded 1 chid ids of type : 4086 Number RLEs to save : 119 TO DO : save crop sub photo not yet done ! we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593994_3820514 we have uploaded 1 photos in the portfolio 4789106 batch 1 Loaded 3 chid ids of type : 4086 Number RLEs to save : 952 TO DO : save crop sub photo not yet done ! we have 1 photo to upload uploaded to storage server : ovh folder_temporaire : temp/1739593994_3820514 we have uploaded 1 photos in the portfolio 4789106 batch 1 Loaded 4 chid ids of type : 4086 Number RLEs to save : 1502 TO DO : save crop sub photo not yet done ! time spend for datou_step_exec : 4.194892883300781 time spend to save output : 9.34600830078125e-05 total time spend for step 1 : 4.194986343383789 caffe_path_current : About to save ! 0 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : None fin du test de generate_new_image ############################### TEST velours_tree ################################ test velours_tree - Retrieving photos to tag... query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=4837217 ORDER BY ph.size desc - Loading descriptors... Size : 512 len(descriptors) : 5 Compute structured hierarchical clustering... ward : AgglomerativeClustering(n_clusters=5) ward.labels_ : [4 3 2 1 0] Elapsed time: 0.006775379180908203 graph_id used : 1145 - Beta version, working pretty good on 11-5-16 ! fin du test de velours_tree ############################### TEST step ACP ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : acp list_input_json : [] origin We have 1 , we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 0.6324870586395264 About to test input to load Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:acp Sat Feb 15 05:33:19 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Cette step permet de calculer une ACP. ATTENTION : le size etait trop grand : 20, on a changé sa valeur à : 9 find save_photo_desc_type : 5705 On sauvegarde les nouveaux descripteurs dans le photo desc type : 5705 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5705, 'ACP_from_type_5619_size_9', 9, 9, 'ACP_from_type_5619_size_9', None, 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2022, 6, 16, 11, 6, 15), None) time to traite the descriptors : 0.0002620220184326172 storage_type for insertDescriptorsMulti : 3 Missing photo l117 : 1069306708 Missing photo l117 : 1069306710 Missing photo l117 : 1069306805 Missing photo l117 : 1069306815 Missing photo l117 : 1069306841 Missing photo l117 : 1069306843 Missing photo l117 : 1069306844 Missing photo l117 : 1069306954 Missing photo l117 : 1069306964 Missing photo l117 : 1069306967 To insert : 1069306708 To insert : 1069306710 To insert : 1069306805 To insert : 1069306815 To insert : 1069306841 To insert : 1069306843 To insert : 1069306844 To insert : 1069306954 To insert : 1069306964 To insert : 1069306967 time to insert the descriptors : 3.371156692504883 res : {'1069306708': b'\xc3\xbf\x00\x00\x00\x00\x08\x14\x03\x05', '1069306710': b'\x00\x00\x00\x00\x00\x00\x00"\xc2\xb3', '1069306805': b'\x00\x06\x00\x00\x00\x00\x00\xc2\x8a\x00', '1069306815': b'\x00l\x00\x00\x00\xc3\x84>\x00\x00', '1069306841': b'\x004\x00\xc3\xad@=sz\x00', '1069306843': b'\x00\x00-\x00\xc3\xb9\x00\x00\x00\x00', '1069306844': b'\x00\x00\x00\xc2\x86\x00T\x00\x00\x00', '1069306954': b'\x14\xc2\x83\xc3\xbf\x1f\x00\x00\x00\x00\x00', '1069306964': b'\x06\xc3\xbf\x00X\x1a\x00\x00\x00\x1f', '1069306967': b'\x00\x00\x00\x00\x00\x00\xc2\xab\x00\x00'} time spend for datou_step_exec : 5.372538328170776 time spend to save output : 6.914138793945312e-05 total time spend for step 1 : 5.372607469558716 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : acp we use saveGeneral [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708] Looping around the photos to save general results len do output : 10 /1069306708Didn't retrieve data . /1069306710Didn't retrieve data . /1069306805Didn't retrieve data . /1069306815Didn't retrieve data . /1069306841Didn't retrieve data . /1069306843Didn't retrieve data . /1069306844Didn't retrieve data . /1069306954Didn't retrieve data . /1069306964Didn't retrieve data . /1069306967Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306967', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306964', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306954', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306844', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306843', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306841', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306815', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306805', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306710', None, None, None, None, None, None) ('4208', None, None, None, None, None, None, None, None) ('4208', '5709050', '1069306708', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 20 time used for this insertion : 0.016841888427734375 save_final save missing photos in datou_result : After save, about to update current ! Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : acp list_input_json : [] origin We have 1 , we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 0.015022754669189453 About to test input to load Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:acp Sat Feb 15 05:33:24 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Cette step permet de calculer une ACP. ATTENTION : le size etait trop grand : 20, on a changé sa valeur à : 9 Sauvegarde du modèle et envoi sur OVH Attention : /data/models_weight/ACP_from_port_5709050_type_5619_size_9 existe, son contenu risque d'être écrasé model_param file didn't exist model didn't exist , save the new model in s3 local folder to save in s3 : /data/models_weight/ACP_from_port_5709050_type_5619_size_9 update : 1739594006.8421407 done ! 1739594006.9999852 {'files': [{'name': 'pca_model.pkl', 'size': 103314, 'last_modified': '2025-02-15T04:33:26.859960', 'hash': 'd7e2c6aa9a1ef592ffdfc4abe9c66263'}], 'directories': []} Création d'un nouveau thème de classification Le thème de classification 'ACP_from_port_5709050_type_5619_size_9' existe déjà, merci de relancer avec un nouveau nom dans les params-json. time spend for datou_step_exec : 2.4224376678466797 time spend to save output : 4.124641418457031e-05 total time spend for step 1 : 2.4224789142608643 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : acp we use saveGeneral [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708] Looping around the photos to save general results object of type 'int' has no len() begin to insert list_values into mtr_datou_result : length of list_values in save_final : 10 time used for this insertion : 0.11586546897888184 save_final save missing photos in datou_result : After save, about to update current ! Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : acp list_input_json : [] origin We have 1 , we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 0.014441728591918945 About to test input to load Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:acp Sat Feb 15 05:33:27 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Cette step permet de calculer une ACP. To do loadFromThcl(), then load ParamDescType : thcl3412 thcls : [{'id': 3412, 'mtr_user_id': 31, 'name': 'ACP_from_port_5709050_type_5619_size_9', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '', 'svm_portfolios_learning': '0', 'photo_hashtag_type': 4398, 'photo_desc_type': 5706, 'type_classification': 'ACP', 'hashtag_id_list': '0'}] thcl {'id': 3412, 'mtr_user_id': 31, 'name': 'ACP_from_port_5709050_type_5619_size_9', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '', 'svm_portfolios_learning': '0', 'photo_hashtag_type': 4398, 'photo_desc_type': 5706, 'type_classification': 'ACP', 'hashtag_id_list': '0'} Update svm_hashtag_type_desc : 5706 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5706, 'ACP_from_port_5709050_type_5619_size_9', 9, 9, 'ACP_from_port_5709050_type_5619_size_9', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2022, 6, 16, 11, 8, 14), datetime.datetime(2022, 6, 16, 11, 8, 14)) model_param file didn't exist model_name : ACP_from_port_5709050_type_5619_size_9 model_type : acp list file need : ['pca_model.pkl'] file exist in s3 : ['pca_model.pkl'] file manque in s3 : [] local folder : /data/models_weight/ACP_from_port_5709050_type_5619_size_9 /data/models_weight/ACP_from_port_5709050_type_5619_size_9/pca_model.pkl size_local : 103314 size in s3 : 103314 create time local : 2025-02-15 05:33:25 create time in s3 : 2025-02-15 04:33:26 pca_model.pkl already exist and didn't need to update model_name : ACP_from_port_5709050_type_5619_size_9 On sauvegarde les nouveaux descripteurs dans le photo desc type : 5706 time to traite the descriptors : 0.0003006458282470703 storage_type for insertDescriptorsMulti : 3 Missing photo l117 : 1069306708 Missing photo l117 : 1069306710 Missing photo l117 : 1069306805 Missing photo l117 : 1069306815 Missing photo l117 : 1069306841 Missing photo l117 : 1069306843 Missing photo l117 : 1069306844 Missing photo l117 : 1069306954 Missing photo l117 : 1069306964 Missing photo l117 : 1069306967 To insert : 1069306708 To insert : 1069306710 To insert : 1069306805 To insert : 1069306815 To insert : 1069306841 To insert : 1069306843 To insert : 1069306844 To insert : 1069306954 To insert : 1069306964 To insert : 1069306967 time to insert the descriptors : 2.8841795921325684 res : {'1069306708': b'\xc3\xbf\x00\x00\x00\x00\x08\x14\x03\x05', '1069306710': b'\x00\x00\x00\x00\x00\x00\x00"\xc2\xb3', '1069306805': b'\x00\x06\x00\x00\x00\x00\x00\xc2\x8a\x00', '1069306815': b'\x00l\x00\x00\x00\xc3\x84>\x00\x00', '1069306841': b'\x004\x00\xc3\xad@=sz\x00', '1069306843': b'\x00\x00-\x00\xc3\xb9\x00\x00\x00\x00', '1069306844': b'\x00\x00\x00\xc2\x86\x00T\x00\x00\x00', '1069306954': b'\x14\xc2\x83\xc3\xbf\x1f\x00\x00\x00\x00\x00', '1069306964': b'\x06\xc3\xbf\x00X\x1a\x00\x00\x00\x1f', '1069306967': b'\x00\x00\x00\x00\x00\x00\xc2\xab\x00\x00'} time spend for datou_step_exec : 4.400172472000122 time spend to save output : 3.838539123535156e-05 total time spend for step 1 : 4.400210857391357 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : acp we use saveGeneral [1069306967, 1069306964, 1069306954, 1069306844, 1069306843, 1069306841, 1069306815, 1069306805, 1069306710, 1069306708] Looping around the photos to save general results len do output : 10 /1069306708Didn't retrieve data . /1069306710Didn't retrieve data . /1069306805Didn't retrieve data . /1069306815Didn't retrieve data . /1069306841Didn't retrieve data . /1069306843Didn't retrieve data . /1069306844Didn't retrieve data . /1069306954Didn't retrieve data . /1069306964Didn't retrieve data . /1069306967Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306967', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306964', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306954', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306844', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306843', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306841', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306815', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306805', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306710', None, None, None, None, None, None) ('4212', None, None, None, None, None, None, None, None) ('4212', '5709050', '1069306708', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 20 time used for this insertion : 0.014621496200561523 save_final save missing photos in datou_result : After save, about to update current ! fin du test de la step acp ############################### TEST blur_crop ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : crop_condition list_input_json : [] origin We have 1 , BBFFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 2 ; length of list_pids : 2 ; length of list_args : 2 time to download the photos : 1.4839732646942139 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:crop_condition Sat Feb 15 05:33:33 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Loading chi in step crop with photo_hashtag_type : 4356 Loading chi in step crop for list_pids : 2 ! batch 1 Loaded 3 chid ids of type : 4356 +++++ begin to crop the class : Papier_Magazine param for this class : {} filtre for class : Papier_Magazine hashtag_id of this class : 2107752386 begin to crop the class : carton_brun param for this class : {} filtre for class : carton_brun hashtag_id of this class : 2107753024 begin to crop the class : carton_gris param for this class : {} filtre for class : carton_gris hashtag_id of this class : 2107753020 begin to crop the class : cartonnette param for this class : {} filtre for class : cartonnette hashtag_id of this class : 702398920 begin to crop the class : kraft param for this class : {} filtre for class : kraft hashtag_id of this class : 493202403 begin to crop the class : autre_refus param for this class : {} filtre for class : autre_refus hashtag_id of this class : 2107752406 begin to crop the class : metal param for this class : {} filtre for class : metal hashtag_id of this class : 492628673 begin to crop the class : plastique param for this class : {} filtre for class : plastique hashtag_id of this class : 492725882 begin to crop the class : teint_dans_la_masse param for this class : {} filtre for class : teint_dans_la_masse hashtag_id of this class : 2107752385 begin to crop the class : environnement param for this class : {} filtre for class : environnement hashtag_id of this class : 493012381 begin to crop the class : contaminant param for this class : {} filtre for class : contaminant hashtag_id of this class : 681467679 map_result returned by crop_photo_return_map_crop : length : 3 About to insert : list_path_to_insert length 0 new photo from crops ! About to upload 0 photos WARNING : list_path_to_insert is empty, cannot upload ! we have finished the crop for the class : contaminant time spend for datou_step_exec : 4.464311361312866 time spend to save output : 9.655952453613281e-05 total time spend for step 1 : 4.464407920837402 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : crop_condition we use saveGeneral [1105701516, 1105701500] Looping around the photos to save general results len do output : 3 /1105703686Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1105703688Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . /1105703689Didn't retrieve data .Didn't retrieve data .Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('3990', None, None, None, None, None, None, None, None) ('3990', '6135916', '1105701516', None, None, None, None, None, None) ('3990', None, None, None, None, None, None, None, None) ('3990', '6135916', '1105701500', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 11 time used for this insertion : 0.015941381454467773 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {1105703686: [1105701516, 'temp/1739594013_3820514_1105701516_047b0ce16fe5e308d8512c83125c4058_polygon_blur_2436374092_1.jpg', (25, 175, 137, 235)], 1105703688: [1105701500, 'temp/1739594013_3820514_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436373819_1.jpg', (108, 300, 16, 138)], 1105703689: [1105701500, 'temp/1739594013_3820514_1105701500_b57a1caec2d74ede6814095fdd28cb27_polygon_blur_2436374262_1.jpg', (47, 300, 91, 247)]} fin du test de la step crop option blur ############################### TEST pma_consolidate ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 12666 copy_chis is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 12667 consolidate_hashtags_from_manual_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 12664 rle_unique_nms_with_priority is not consistent : 3 used against 1 in the step definition ! WARNING : number of outputs for step 12664 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 12671 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 12666 have datatype=11 whereas input 0 of step 12664 have datatype=2 WARNING : type of output 1 of step 12667 doesn't seem to be define in the database( WARNING : type of input 3 of step 12665 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 12667 doesn't seem to be define in the database( WARNING : type of input 1 of step 12664 doesn't seem to be define in the database( WARNING : type of input 1 of step 12671 doesn't seem to be define in the database( WARNING : output 1 of step 12664 have datatype=7 whereas input 1 of step 12671 have datatype=None WARNING : type of output 1 of step 12671 doesn't seem to be define in the database( WARNING : type of input 4 of step 12665 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 12666 doesn't seem to be define in the database( WARNING : type of input 1 of step 12667 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : copy_chis, consolidate_hashtags_from_manual_portfolio, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final list_input_json : [] origin We have 1 , BBFFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 2 ; length of list_pids : 2 ; length of list_args : 2 time to download the photos : 0.23380470275878906 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 5 step1:copy_chis Sat Feb 15 05:33:37 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Begin step datou_step_copy_crop batch 1 Loaded 21 chid ids of type : 4482 batch 1 Loaded 88 chid ids of type : 4490 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! time spend for datou_step_exec : 6.1156370639801025 time spend to save output : 6.318092346191406e-05 total time spend for step 1 : 6.1157002449035645 step2:consolidate_hashtags_from_manual_portfolio Sat Feb 15 05:33:44 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step consolidate_hashtags_from_manual_portfolio Iterating over portfolio : 6549724 on est dans le IF portfolio mere 26T SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=6549724 AND mptpi.`type`=4483 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement')) AND mptpi.`min_score`=0.1 To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=6549724 AND mptpi.`type`=4490 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement')) AND mptpi.`min_score`=0.1 To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=9778120 AND mptpi.`type`=4483 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement')) AND mptpi.`min_score`=0.1 To do TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755323 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 101 chid ids of type : 4482 begin to find the sub_photo_id : begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755324 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 101 chid ids of type : 4482 begin to find the sub_photo_id : begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755325 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 53 chid ids of type : 4482 begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755326 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 101 chid ids of type : 4482 begin to find the sub_photo_id : begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755327 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755328 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 53 chid ids of type : 4482 begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755329 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755330 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755331 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755332 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755333 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 101 chid ids of type : 4482 begin to find the sub_photo_id : begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755334 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755335 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755336 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755337 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755338 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755339 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755340 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755341 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 48 chid ids of type : 4482 begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755342 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 101 chid ids of type : 4482 begin to find the sub_photo_id : begin to find the sub_photo_id : To test ! Use context local managing function ! time spend for datou_step_exec : 7.301064729690552 time spend to save output : 4.100799560546875e-05 total time spend for step 2 : 7.301105737686157 step3:rle_unique_nms_with_priority Sat Feb 15 05:33:51 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 88 chid ids of type : 4490 seulement à utiliser dans la step consolidation batch 1 Loaded 50 chid ids of type : 4490 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 0.0378873348236084 seulement à utiliser dans la step consolidation batch 1 Loaded 38 chid ids of type : 4490 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 0.03911733627319336 map_output_result : {1114046377: (0.09264291817443555, 'Should be the crop_list due to order', 0.14304832271019904), 1114046597: (0.09264291817443555, 'Should be the crop_list due to order', 0.042237513638672064)} End step rle-unique-nms time spend for datou_step_exec : 3.7452945709228516 time spend to save output : 6.67572021484375e-05 total time spend for step 3 : 3.745361328125 step4:ventilate_hashtags_in_portfolio Sat Feb 15 05:33:55 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 6549724 get user id for portfolio 6549724 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=6549724 AND mptpi.`type`=4490 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement','mal_croppe','flou')) AND mptpi.`min_score`=0.1 To do To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=6549724 AND mptpi.`type`=4483 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement','mal_croppe','flou')) AND mptpi.`min_score`=0.1 To do lien utilise dans velours : https://www.fotonower.com/velours/9755323,9755324,9755325,9755326,9755327,9755328,9755329,9755330,9755331,9755332,9755333,9755334,9755335,9755336,9755337,9755338,9755339,9755340,9755341,9755342,9755344,9755345?tags=papier,carton,metal,pet_clair,pehd,pet_fonce,pet_opaque,barquette_opaque,film_plastique,ela,sac,textiles,verre,organique,dasri,masque,encombrant,autre_emballage,autre_non_emballage,environnement,mal_croppe,flou&datou_id_consolidate=4387&port_consolidate=6549724 time spend for datou_step_exec : 0.42371392250061035 time spend to save output : 7.319450378417969e-05 total time spend for step 4 : 0.42378711700439453 step5:final Sat Feb 15 05:33:55 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! complete output_args for input 2 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou step final ! time spend for datou_step_exec : 1.3144207000732422 time spend to save output : 5.030632019042969e-05 total time spend for step 5 : 1.3144710063934326 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False original output for save of step final : {1114046377: ('0.3133414848207032',), 1114046597: ('0.3133414848207032',)} new output for save of step final : {1114046377: ('0.3133414848207032',), 1114046597: ('0.3133414848207032',)} [1114046377, 1114046597] Looping around the photos to save general results len do output : 2 /1114046377.Didn't retrieve data . /1114046597.Didn't retrieve data . before output type Used above Used above Managing all output in save final without adding information in the mtr_datou_result ('4492', None, None, None, None, None, None, None, None) ('4492', '6549724', '1114046377', None, None, None, None, None, None) ('4492', None, None, None, None, None, None, None, None) ('4492', '6549724', '1114046597', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 6 time used for this insertion : 0.028163909912109375 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 5 output : {1114046377: ('0.3133414848207032',), 1114046597: ('0.3133414848207032',)} fin du test de portfolio mere absolue dans consolidate ############################### TEST pma_ventilate ################################ Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 12795 copy_chis is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 12796 consolidate_hashtags_from_manual_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 12793 rle_unique_nms_with_priority is not consistent : 3 used against 1 in the step definition ! WARNING : number of outputs for step 12793 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : output 0 of step 12795 have datatype=11 whereas input 0 of step 12793 have datatype=2 WARNING : type of output 1 of step 12796 doesn't seem to be define in the database( WARNING : type of input 1 of step 12793 doesn't seem to be define in the database( WARNING : type of input 1 of step 12800 doesn't seem to be define in the database( WARNING : output 1 of step 12793 have datatype=7 whereas input 1 of step 12800 have datatype=None WARNING : type of output 1 of step 12795 doesn't seem to be define in the database( WARNING : type of input 1 of step 12796 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : copy_chis, consolidate_hashtags_from_manual_portfolio, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio list_input_json : [] origin We have 1 , BBFFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 2 ; length of list_pids : 2 ; length of list_args : 2 time to download the photos : 0.24260258674621582 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 4 step1:copy_chis Sat Feb 15 05:33:57 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Begin step datou_step_copy_crop batch 1 Loaded 21 chid ids of type : 4482 batch 1 Loaded 88 chid ids of type : 4490 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! time spend for datou_step_exec : 0.06584811210632324 time spend to save output : 8.58306884765625e-05 total time spend for step 1 : 0.0659339427947998 step2:consolidate_hashtags_from_manual_portfolio Sat Feb 15 05:33:57 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step consolidate_hashtags_from_manual_portfolio Iterating over portfolio : 6549724 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=6549724 AND mptpi.`type`=4483 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement')) To do SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=6549724 AND mptpi.`type`=4490 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement')) To do TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755323 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 101 chid ids of type : 4482 begin to find the sub_photo_id : begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755324 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 101 chid ids of type : 4482 begin to find the sub_photo_id : begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755325 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 53 chid ids of type : 4482 begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755326 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 101 chid ids of type : 4482 begin to find the sub_photo_id : begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755327 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755328 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 53 chid ids of type : 4482 begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755329 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755330 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755331 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755332 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755333 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 101 chid ids of type : 4482 begin to find the sub_photo_id : begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755334 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755335 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755336 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755337 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755338 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755339 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755340 AND mpp.hide_status=0 ORDER BY ph.size desc TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755341 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 48 chid ids of type : 4482 begin to find the sub_photo_id : TODO : # On doit donc construire les chi a partir des informations dans les photos filles query : SELECT ph.photo_id FROM MTRBack.photos ph, MTRUser.mtr_portfolio_photos mpp WHERE ph.photo_id=mpp.mtr_photo_id AND mpp.mtr_portfolio_id=9755342 AND mpp.hide_status=0 ORDER BY ph.size desc batch 1 Loaded 101 chid ids of type : 4482 begin to find the sub_photo_id : begin to find the sub_photo_id : To test ! Use context local managing function ! time spend for datou_step_exec : 1.8788530826568604 time spend to save output : 5.626678466796875e-05 total time spend for step 2 : 1.8789093494415283 step3:rle_unique_nms_with_priority Sat Feb 15 05:33:59 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 We expect there is only one output and this part is used while all output are not tuple or array We expect there is only one output and this part is used while all output are not tuple or array VR 22-3-18 : For now we do not clean correctly the datou structure Begin step rle-unique-nms batch 1 Loaded 88 chid ids of type : 4490 seulement à utiliser dans la step consolidation batch 1 Loaded 38 chid ids of type : 4490 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 0.035065412521362305 seulement à utiliser dans la step consolidation batch 1 Loaded 50 chid ids of type : 4490 Number RLEs to save : 0 TO DO : save crop sub photo not yet done ! save time : 0.10475373268127441 map_output_result : {1114046597: (0.09264291817443555, 'Should be the crop_list due to order', 0.042237513638672064), 1114046377: (0.09264291817443555, 'Should be the crop_list due to order', 0.14304832271019904)} End step rle-unique-nms time spend for datou_step_exec : 0.8666160106658936 time spend to save output : 5.626678466796875e-05 total time spend for step 3 : 0.8666722774505615 step4:ventilate_hashtags_in_portfolio Sat Feb 15 05:34:00 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed We should have FATAL ERROR but same_nb_input_output==True : this should be an optionnal input ! VR 22-3-18 : For now we do not clean correctly the datou structure beginning of datou step ventilate_hashtags_in_portfolio : To implement ! Iterating over portfolio : 6549724 get user id for portfolio 6549724 SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=9974548 AND mptpi.`type`=4490 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement','mal_croppe','flou')) AND mptpi.`min_score`=0.1 To do To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=6549724 AND mptpi.`type`=4490 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement','mal_croppe','flou')) AND mptpi.`min_score`=0.1 To do To do ! Use context local managing function ! SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=6549724 AND mptpi.`type`=4483 AND mptpi.`hashtag_id` in (select hashtag_id FROM MTRBack.hashtags where hashtag in ('papier','carton','metal','pet_clair','pehd','pet_fonce','pet_opaque','barquette_opaque','film_plastique','ela','sac','textiles','verre','organique','dasri','masque','encombrant','autre_emballage','autre_non_emballage','environnement','mal_croppe','flou')) AND mptpi.`min_score`=0.1 To do lien utilise dans velours : https://www.fotonower.com/velours/9755323,9755324,9755325,9755326,9755327,9755328,9755329,9755330,9755331,9755332,9755333,9755334,9755335,9755336,9755337,9755338,9755339,9755340,9755341,9755342,9755344,9755345?tags=papier,carton,metal,pet_clair,pehd,pet_fonce,pet_opaque,barquette_opaque,film_plastique,ela,sac,textiles,verre,organique,dasri,masque,encombrant,autre_emballage,autre_non_emballage,environnement,mal_croppe,flou&datou_id_consolidate=4387&port_consolidate=6549724 time spend for datou_step_exec : 1.8669092655181885 time spend to save output : 6.890296936035156e-05 total time spend for step 4 : 1.8669781684875488 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False saveOutput not yet implemented for datou_step.type : ventilate_hashtags_in_portfolio we use saveGeneral [1114046597, 1114046377] Looping around the photos to save general results len do output : 1 /6549724. before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('4553', None, None, None, None, None, None, None, None) ('4553', '6549724', '1114046597', None, None, None, None, None, None) ('4553', None, None, None, None, None, None, None, None) ('4553', '6549724', '1114046377', None, None, None, None, None, None) begin to insert list_values into mtr_datou_result : length of list_values in save_final : 3 time used for this insertion : 0.4745349884033203 save_final save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 4 output : {6549724: [{'papier': 9755346, 'carton': 9755347, 'metal': 9755348, 'pet_clair': 9755349, 'pehd': 9755350, 'pet_fonce': 9755351, 'pet_opaque': 9755352, 'barquette_opaque': 9755353, 'film_plastique': 9755354, 'ela': 9755355, 'sac': 9755356, 'textiles': 9755357, 'verre': 9755358, 'organique': 9755359, 'dasri': 9755360, 'masque': 9755361, 'encombrant': 9755362, 'autre_emballage': 9755363, 'autre_non_emballage': 9755364, 'environnement': 9755365, 'mal_croppe': 9755366, 'flou': 9755367}]} fin du test de portfolio mere absolue dans consolidate #&_#_#&_# TEST sam SUCCEEDED #&_#_#&_# #&_#_#&_# TEST frcnn SUCCEEDED #&_#_#&_# #&_#_#&_# TEST thcl SUCCEEDED #&_#_#&_# #&_#_#&_# TEST tfhub2 SUCCEEDED #&_#_#&_# #&_#_#&_# TEST ordonner SUCCEEDED #&_#_#&_# #&_#_#&_# TEST rotate SUCCEEDED #&_#_#&_# #&_#_#&_# TEST data_augmentation_ellipse_varroa_tile_rotate SUCCEEDED #&_#_#&_# #&_#_#&_# TEST flip SUCCEEDED #&_#_#&_# #&_#_#&_# TEST crop_rles SUCCEEDED #&_#_#&_# #&_#_#&_# TEST angular_coeff SUCCEEDED #&_#_#&_# #&_#_#&_# TEST detection_filter_by_crop SUCCEEDED #&_#_#&_# #&_#_#&_# TEST detection_filter_by_classif SUCCEEDED #&_#_#&_# #&_#_#&_# TEST blur_detection SUCCEEDED #&_#_#&_# #&_#_#&_# TEST detect_point_224x224 SUCCEEDED #&_#_#&_# #&_#_#&_# TEST certificat_qualite_papier FAILED #&_#_#&_# #&_#_#&_# TEST image_temperature_detection SUCCEEDED #&_#_#&_# #&_#_#&_# TEST broca SUCCEEDED #&_#_#&_# #&_#_#&_# TEST crop_conditional SUCCEEDED #&_#_#&_# #&_#_#&_# TEST image_blanchir SUCCEEDED #&_#_#&_# #&_#_#&_# TEST darker_image SUCCEEDED #&_#_#&_# #&_#_#&_# TEST img_aug SUCCEEDED #&_#_#&_# #&_#_#&_# TEST rubbia SUCCEEDED #&_#_#&_# #&_#_#&_# TEST rubbia_split_dark SUCCEEDED #&_#_#&_# #&_#_#&_# TEST rubbia_append SUCCEEDED #&_#_#&_# #&_#_#&_# TEST rubbia_horaire FAILED #&_#_#&_# #&_#_#&_# TEST rle_unique_nms_with_priority SUCCEEDED #&_#_#&_# #&_#_#&_# TEST random_deformation SUCCEEDED #&_#_#&_# #&_#_#&_# TEST tile SUCCEEDED #&_#_#&_# #&_#_#&_# TEST rotate_chi SUCCEEDED #&_#_#&_# #&_#_#&_# TEST rubbia_carac_pet_clair_0121_no_cnn SUCCEEDED #&_#_#&_# #&_#_#&_# TEST rubbia_carac_jrm_no_mask_detect SUCCEEDED #&_#_#&_# #&_#_#&_# TEST ventilate_hashtags_in_portfolio SUCCEEDED #&_#_#&_# #&_#_#&_# TEST poly_ro_rle SUCCEEDED #&_#_#&_# #&_#_#&_# TEST cod_sts SUCCEEDED #&_#_#&_# #&_#_#&_# TEST cod_download SUCCEEDED #&_#_#&_# #&_#_#&_# TEST sendgrid SUCCEEDED #&_#_#&_# #&_#_#&_# TEST rym_consolidate SUCCEEDED #&_#_#&_# #&_#_#&_# TEST generate_new_image_add_crop SUCCEEDED #&_#_#&_# #&_#_#&_# TEST velours_tree SUCCEEDED #&_#_#&_# #&_#_#&_# TEST step ACP SUCCEEDED #&_#_#&_# #&_#_#&_# TEST blur_crop SUCCEEDED #&_#_#&_# #&_#_#&_# TEST pma_consolidate SUCCEEDED #&_#_#&_# #&_#_#&_# TEST pma_ventilate SUCCEEDED #&_#_#&_# #&_# TEST FAILED #&_# : tests/datou_test #&_# #&_# END OF TEST #&_# : tests/datou_test #&_# #&_# BEGIN OF TEST : mtr/database_queries/CacheModelData_queries #&_# /home/admin/workarea/git/Velours/python/mtr/database_queries/CacheModelData_queries.py Test Cache Model Data test a faire VR 27-9-17 #&_# TEST SUCCEEDED #&_# : mtr/database_queries/CacheModelData_queries #&_# #&_# END OF TEST #&_# : mtr/database_queries/CacheModelData_queries #&_# #&_# BEGIN OF TEST : tests/cache_photo_data_test #&_# /home/admin/workarea/git/Velours/python/tests/cache_photo_data_test.py Test local_cache_photo ############################### test_download_photos_by_local_cache ################################ test download portfolio 1162416 : 574 photos We have 1 , we need 574 photos there is already 574 photos exist in our local_cache we have to download 0 photos we have successful downloaded 0 photos there are 0 photos missing finally, we can get 574 photo needed from our local_cache list of photo_id_missing : [] test download a list if photos : 10 photos (6 exist in ovh and 4 missing in ovh) we need 10 photos there is already 6 photos exist in our local_cache we have to download 4 photos download_photo : 1 to 2000 BBBBHTTP Error 404: Not Found can't download the photo : 1109585120 FHTTP Error 404: Not Found can't download the photo : 1109585109 FHTTP Error 404: Not Found can't download the photo : 1109585436 FHTTP Error 404: Not Found can't download the photo : 1109585121 Fwe have successful downloaded 0 photos there are 4 photos missing finally, we can get 6 photo needed from our local_cache list of photo_id_missing : [1109585120, 1109585109, 1109585436, 1109585121] ############################### test_update_time_created ################################ we need 1 photos there is already 1 photos exist in our local_cache we have to download 0 photos we have successful downloaded 0 photos there are 0 photos missing finally, we can get 1 photo needed from our local_cache list of photo_id_missing : [] #&_#_#&_# TEST cache photo data SUCCEEDED #&_#_#&_# #&_# TEST SUCCEEDED #&_# : tests/cache_photo_data_test #&_# #&_# END OF TEST #&_# : tests/cache_photo_data_test #&_# #&_# BEGIN OF TEST : mtr/mask_rcnn/prepare_maskdata #&_# /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/prepare_maskdata.py test prepare mask data 2096875719 599722655 batch 1 Loaded 20 chid ids of type : 840 ++++++++++++++++++++batch 1 Loaded 16 chid ids of type : 840 +++++++++batch 1 Loaded 20 chid ids of type : 840 ++++++++++++++++++++batch 1 Loaded 19 chid ids of type : 840 ++++++++++batch 1 Loaded 20 chid ids of type : 840 ++++++++++++{2096875719: 'Plaque-immatriculation', 599722655: 'capot'} logo-marque 2096875717 907850592 x0 : 38 y1 : 269 width : 32, height : 38, area : 1216, score : 1.0 None pare-choc 624624117 907850592 x0 : 0 y1 : 559 width : 362, height : 235, area : 85070, score : 1.0 None coffre 495920967 907850592 x0 : 0 y1 : 398 width : 302, height : 336, area : 101472, score : 1.0 None coffre 495920967 907850592 x0 : 626 y1 : 206 width : 18, height : 35, area : 630, score : 1.0 None aile-arriere 2106233861 907850592 x0 : 189 y1 : 476 width : 282, height : 235, area : 66270, score : 1.0 None roue 492689227 907850592 x0 : 275 y1 : 620 width : 170, height : 215, area : 36550, score : 1.0 None Plaque-immatriculation 2096875719 907850592 x0 : 10 y1 : 454 width : 108, height : 84, area : 9072, score : 1.0 None feu-arriere 2096875713 907850592 x0 : 192 y1 : 359 width : 147, height : 96, area : 14112, score : 1.0 None poignee 499500794 907850592 x0 : 437 y1 : 315 width : 42, height : 37, area : 1554, score : 1.0 None poignee 499500794 907850592 x0 : 567 y1 : 282 width : 25, height : 31, area : 775, score : 1.0 None Pot-echappement 2096875720 907850592 x0 : 155 y1 : 532 width : 21, height : 20, area : 420, score : 1.0 None toit 492731002 907850592 x0 : 136 y1 : 74 width : 281, height : 21, area : 5901, score : 1.0 None Pare-brise 2096875709 907850592 x0 : 1 y1 : 241 width : 285, height : 165, area : 47025, score : 1.0 None porte 492654799 907850592 x0 : 354 y1 : 442 width : 210, height : 380, area : 79800, score : 1.0 None porte 492654799 907850592 x0 : 501 y1 : 389 width : 135, height : 324, area : 43740, score : 1.0 None Info-modele 2096875721 907850592 x0 : 132 y1 : 295 width : 53, height : 31, area : 1643, score : 1.0 None vitre 492925064 907850592 x0 : 407 y1 : 201 width : 123, height : 122, area : 15006, score : 1.0 None vitre 492925064 907850592 x0 : 377 y1 : 201 width : 64, height : 118, area : 7552, score : 1.0 None vitre 492925064 907850592 x0 : 522 y1 : 203 width : 102, height : 120, area : 12240, score : 1.0 None Essuie-glace 2096875722 907850592 x0 : 7 y1 : 250 width : 72, height : 61, area : 4392, score : 1.0 None /data/data_root/test_preparedata/train/907850592.jpg logo-marque 2096875717 907862724 x0 : 100 y1 : 282 width : 35, height : 41, area : 1435, score : 1.0 None pare-choc 624624117 907862724 x0 : 1 y1 : 483 width : 435, height : 194, area : 84390, score : 1.0 None aile-arriere 2106233861 907862724 x0 : 399 y1 : 411 width : 110, height : 128, area : 14080, score : 1.0 None retroviseur 492844413 907862724 x0 : 600 y1 : 203 width : 41, height : 37, area : 1517, score : 1.0 None coffre 495920967 907862724 x0 : 5 y1 : 351 width : 369, height : 270, area : 99630, score : 1.0 None Cache-reservoir 2096875718 907862724 x0 : 417 y1 : 289 width : 50, height : 61, area : 3050, score : 1.0 None roue 492689227 907862724 x0 : 367 y1 : 541 width : 121, height : 190, area : 22990, score : 1.0 None poignee 499500794 907862724 x0 : 478 y1 : 275 width : 33, height : 25, area : 825, score : 1.0 None toit 492731002 907862724 x0 : 226 y1 : 110 width : 223, height : 36, area : 8028, score : 1.0 None feu-arriere 2096875713 907862724 x0 : 294 y1 : 331 width : 112, height : 146, area : 16352, score : 1.0 None poignee 499500794 907862724 x0 : 566 y1 : 252 width : 20, height : 27, area : 540, score : 1.0 None Plaque-immatriculation 2096875719 907862724 x0 : 55 y1 : 436 width : 142, height : 54, area : 7668, score : 1.0 None Pare-brise 2096875709 907862724 x0 : 6 y1 : 225 width : 366, height : 132, area : 48312, score : 1.0 None porte 492654799 907862724 x0 : 395 y1 : 391 width : 170, height : 311, area : 52870, score : 1.0 None porte 492654799 907862724 x0 : 508 y1 : 354 width : 101, height : 269, area : 27169, score : 1.0 None vitre 492925064 907862724 x0 : 451 y1 : 202 width : 85, height : 99, area : 8415, score : 1.0 None vitre 492925064 907862724 x0 : 524 y1 : 202 width : 70, height : 99, area : 6930, score : 1.0 None vitre 492925064 907862724 x0 : 428 y1 : 208 width : 50, height : 102, area : 5100, score : 1.0 None Essuie-glace 2096875722 907862724 x0 : 114 y1 : 218 width : 186, height : 27, area : 5022, score : 1.0 None Info-modele 2096875721 907862724 x0 : 10 y1 : 306 width : 41, height : 33, area : 1353, score : 1.0 None /data/data_root/test_preparedata/train/907862724.jpg porte 492654799 907863602 x0 : 129 y1 : 380 width : 300, height : 279, area : 83700, score : 1.0 None porte 492654799 907863602 x0 : 193 y1 : 345 width : 228, height : 215, area : 49020, score : 1.0 None porte 492654799 907863602 x0 : 379 y1 : 385 width : 257, height : 286, area : 73502, score : 1.0 None porte 492654799 907863602 x0 : 400 y1 : 365 width : 195, height : 248, area : 48360, score : 1.0 None roue 492689227 907863602 x0 : 0 y1 : 419 width : 124, height : 148, area : 18352, score : 1.0 None roue 492689227 907863602 x0 : 0 y1 : 411 width : 127, height : 129, area : 16383, score : 1.0 None roue 492689227 907863602 x0 : 580 y1 : 449 width : 60, height : 129, area : 7740, score : 1.0 None roue 492689227 907863602 x0 : 584 y1 : 444 width : 50, height : 126, area : 6300, score : 1.0 None retroviseur 492844413 907863602 x0 : 165 y1 : 225 width : 53, height : 51, area : 2703, score : 1.0 None vitre 492925064 907863602 x0 : 211 y1 : 218 width : 197, height : 109, area : 21473, score : 1.0 None vitre 492925064 907863602 x0 : 217 y1 : 214 width : 193, height : 99, area : 19107, score : 1.0 None vitre 492925064 907863602 x0 : 409 y1 : 214 width : 188, height : 98, area : 18424, score : 1.0 None vitre 492925064 907863602 x0 : 414 y1 : 206 width : 187, height : 96, area : 17952, score : 1.0 None poignee 499500794 907863602 x0 : 320 y1 : 271 width : 46, height : 19, area : 874, score : 1.0 None poignee 499500794 907863602 x0 : 321 y1 : 270 width : 44, height : 19, area : 836, score : 1.0 None poignee 499500794 907863602 x0 : 553 y1 : 270 width : 62, height : 25, area : 1550, score : 1.0 None poignee 499500794 907863602 x0 : 565 y1 : 266 width : 42, height : 16, area : 672, score : 1.0 None capot 599722655 907863602 x0 : -1 y1 : 215 width : 135, height : 37, area : 4995, score : 1.0 None capot 599722655 907863602 x0 : 242 y1 : 123 width : 330, height : 52, area : 17160, score : 1.0 None /data/data_root/test_preparedata/train/907863602.jpg porte 492654799 907863940 x0 : 109 y1 : 426 width : 283, height : 265, area : 74995, score : 1.0 None porte 492654799 907863940 x0 : 179 y1 : 399 width : 203, height : 221, area : 44863, score : 1.0 None porte 492654799 907863940 x0 : 354 y1 : 425 width : 277, height : 266, area : 73682, score : 1.0 None porte 492654799 907863940 x0 : 370 y1 : 407 width : 179, height : 233, area : 41707, score : 1.0 None roue 492689227 907863940 x0 : -1 y1 : 463 width : 98, height : 141, area : 13818, score : 1.0 None roue 492689227 907863940 x0 : 0 y1 : 468 width : 88, height : 147, area : 12936, score : 1.0 None roue 492689227 907863940 x0 : 523 y1 : 493 width : 117, height : 146, area : 17082, score : 1.0 None roue 492689227 907863940 x0 : 525 y1 : 493 width : 111, height : 147, area : 16317, score : 1.0 None retroviseur 492844413 907863940 x0 : 138 y1 : 278 width : 46, height : 44, area : 2024, score : 1.0 None vitre 492925064 907863940 x0 : 182 y1 : 266 width : 200, height : 95, area : 19000, score : 1.0 None vitre 492925064 907863940 x0 : 385 y1 : 257 width : 172, height : 90, area : 15480, score : 1.0 None vitre 492925064 907863940 x0 : 394 y1 : 256 width : 144, height : 86, area : 12384, score : 1.0 None vitre 492925064 907863940 x0 : 549 y1 : 253 width : 58, height : 53, area : 3074, score : 1.0 None poignee 499500794 907863940 x0 : 300 y1 : 306 width : 59, height : 17, area : 1003, score : 1.0 None poignee 499500794 907863940 x0 : 307 y1 : 313 width : 51, height : 24, area : 1224, score : 1.0 None poignee 499500794 907863940 x0 : 527 y1 : 308 width : 53, height : 22, area : 1166, score : 1.0 None poignee 499500794 907863940 x0 : 536 y1 : 310 width : 45, height : 24, area : 1080, score : 1.0 None capot 599722655 907863940 x0 : 219 y1 : 181 width : 370, height : 38, area : 14060, score : 1.0 None logo-roue 2106233859 907863940 x0 : 7 y1 : 419 width : 27, height : 43, area : 1161, score : 1.0 None logo-roue 2106233859 907863940 x0 : 594 y1 : 441 width : 26, height : 25, area : 650, score : 1.0 None /data/data_root/test_preparedata/val/907863940.jpg #&_#_#&_# TEST prepare mask data poly SUCCEEDED #&_#_#&_# 2107755846 batch 1 Loaded 15 chid ids of type : 2622 {2107755846: 'pet_clair'} environment 492622729 964453879 x0 : 0 y1 : 479 width : 112, height : 415, area : 46480, score : 1.0 None error 501120777 964453879 x0 : 142 y1 : 479 width : 28, height : 20, area : 560, score : 1.0 None error 501120777 964453879 x0 : 151 y1 : 99 width : 23, height : 42, area : 966, score : 1.0 None error 501120777 964453879 x0 : 175 y1 : 59 width : 117, height : 59, area : 6903, score : 1.0 None error 501120777 964453879 x0 : 282 y1 : 479 width : 35, height : 62, area : 2170, score : 1.0 None error 501120777 964453879 x0 : 315 y1 : 460 width : 19, height : 26, area : 494, score : 1.0 None error 501120777 964453879 x0 : 353 y1 : 361 width : 32, height : 41, area : 1312, score : 1.0 None error 501120777 964453879 x0 : 403 y1 : 215 width : 47, height : 51, area : 2397, score : 1.0 None error 501120777 964453879 x0 : 497 y1 : 253 width : 89, height : 55, area : 4895, score : 1.0 None error 501120777 964453879 x0 : 546 y1 : 195 width : 58, height : 68, area : 3944, score : 1.0 None error 501120777 964453879 x0 : 613 y1 : 323 width : 20, height : 32, area : 640, score : 1.0 None error 501120777 964453879 x0 : 638 y1 : 225 width : 17, height : 27, area : 459, score : 1.0 None pet_clair 2107755846 964453879 x0 : 0 y1 : 479 width : 719, height : 479, area : 344401, score : 1.0 None error 501120777 964453879 x0 : 546 y1 : 195 width : 60, height : 68, area : 4080, score : 1.0 None error 501120777 964453879 x0 : 613 y1 : 323 width : 22, height : 32, area : 704, score : 1.0 None /data/data_root/test_preparedata/val/964453879.jpg #&_#_#&_# TEST prepare mask data rle SUCCEEDED #&_#_#&_# time for calcul the mask position with numpy : 0.0001399517059326172 nb_pixel_total : 6 time to create 1 rle with old method : 6.413459777832031e-05 Sanity check PASSED : sum_rle_size : 12 height * width : 12 7 #&_#_#&_# TEST prepare mask data mat SUCCEEDED #&_#_#&_# #&_# TEST SUCCEEDED #&_# : mtr/mask_rcnn/prepare_maskdata #&_# #&_# END OF TEST #&_# : mtr/mask_rcnn/prepare_maskdata #&_# #&_# BEGIN OF TEST : mtr/database_queries/portfolio_queries #&_# /home/admin/workarea/git/Velours/python/mtr/database_queries/portfolio_queries.py test portfolio queries Catched exception ! Connect or reconnect ! #&_# TEST SUCCEEDED #&_# : mtr/database_queries/portfolio_queries #&_# #&_# END OF TEST #&_# : mtr/database_queries/portfolio_queries #&_# #&_# BEGIN OF TEST : prod/memo/memo #&_# /home/admin/workarea/git/Velours/python/prod/memo/memo.py SLA Mensuel python version used : 3 ############################### TEST memo ################################ Removing /home/admin/workarea/git/Velours/python/prod/memo/sla_mensuel VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier TODO : Insert select and so on # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier nb_day : (0, 31) VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier TODO : Insert select and so on # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier select count(distinct mtr_photo_id) from MTRUser.mtr_portfolio_photos where mtr_portfolio_id in (select id from MTRUser.mtr_portfolios where id in (select mtr_portfolio_id from MTRPhoto.dashboard_results where dashboard_run_id in(select last_run_id from MTRPhoto.dashboard_entry_day where dashboard_place_id in (select id from MTRPhoto.dashboard_places where name = 'Romainville_Presse_2' and date like '%2022-08%') and created_at like '%2022-08%'))); nb_day : (0, 31) after unwanted_material_data nb_day : (0, 31) after coverage_data after number_of_batch date_start : 2022-08-01 : dt_date_just_month_year : 2022-08-01 00:00:00 : VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! Error parsing crontab ! [Errno 2] No such file or directory: '' You better check your LOGRASPI env !!! after pl.get_datou_sts_from_crontab : verbose : False no sts found, try to find from database SELECT dri.id FROM MTRPhoto.dashboard_run_ids dri, MTRPhoto.dashboard_entry_day ded, MTRPhoto.dashboard_places dp WHERE dp.name= "Romainville_Presse_2" AND ded.dashboard_place_id=dp.id AND dri.dashboard_entry_day=ded.id AND dri.id=ded.last_run_id AND ded.date >= "2022-08-01" AND ded.date <= "2022-08-31" apple3 {'gm': {'mat': 'gm', 'pht': 4209, 'datou_carac_id': 3994, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'papier'}, 'emr': {'mat': 'emr', 'pht': 4207, 'datou_carac_id': 3993, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'carton'}, 'jrm': {'mat': 'jrm', 'pht': 3726, 'datou_carac_id': 3459, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'papier'}, 'ela': {'mat': 'ela', 'pht': 4203, 'datou_carac_id': 3991, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'ela'}, 'pehd_pp': {'mat': 'pehd_pp', 'pht': 4211, 'datou_carac_id': 3995, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'pehd'}, 'pet_fonce': {'mat': 'pet_fonce', 'pht': 4200, 'datou_carac_id': 4153, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'pet_fonce'}, 'aluminium': {'mat': 'aluminium', 'pht': 4205, 'datou_carac_id': 3992, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'metal'}, 'refus': {'mat': 'refus', 'pht': 3594, 'datou_carac_id': 3318, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'refus'}, 'pet_clair': {'mat': 'pet_clair', 'pht': 3327, 'datou_carac_id': 3804, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'pet_clair,bouchon,etiquette,barquette_avec_film'}} SELECT h.hashtag as unwanted_material, substr(dr.hashtag,8) as main_material, ptp.type as pht_type, sum(pcr.value*dr.nombre_balle)/sum(dr.nombre_balle) as ratio, count(distinct mpp.mtr_photo_id) as nb_photo, group_concat(distinct ptp.mtr_portfolio_id_2) as list_port_cont, group_concat(distinct concat(cast(ptp.mtr_portfolio_id_1 as char), ":", cast(ptp.mtr_portfolio_id_2 as char))) as assoc_port, group_concat(distinct concat(cast(ptp.mtr_portfolio_id_1 as char), ":", h.hashtag, ":", cast(ptp.type as char), ":", cast(ptp.mtr_portfolio_id_2 as char))) as assoc_mat FROM MTRPhoto.dashboard_results dr, MTRPhoto.mtr_port_to_port_ids ptp, MTRUser.mtr_portfolio_photos mpp, MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h WHERE dr.dashboard_run_id IN (448643,449568,454450,454465,454459,454472,456239,458795,461498,454567,457375,457649,459844,460382,461634,463066,472528,465865,469297,468129,475039,472453,474892,474538,475316,476524,479832,481665,479903) AND dr.mtr_portfolio_id=ptp.mtr_portfolio_id_1 AND dr.qualite >= 0 AND mpp.mtr_portfolio_id=ptp.mtr_portfolio_id_2 AND pcr.portfolio_id=ptp.mtr_portfolio_id_1 AND h.hashtag_id = pcr.hashtag_id AND ptp.type = pcr.hashtag_type AND mpp.hide_status = 0 AND ptp.hashtag_id=h.hashtag_id AND ptp.type IN (4209,4207,3726,4203,4211,4200,4205,3594,3327) group by h.hashtag, dr.hashtag, ptp.type; VR TODO TO BETTER PARSE ! ({'unwanted_material': 'barquette_opaque', 'main_material': 'emr', 'pht_type': 4207, 'ratio': 0.0001728785023265608, 'nb_photo': 18, 'list_port_cont': '6861407,6862123,6862547,6867908,6868674,6869389,6869558,6877707,6877972,6881690,6891352,6894202,6907047,6922714,6925593', 'assoc_port': '6790887:6862547,6794193:6862123,6834822:6877972,6840554:6877707,6845438:6869389,6846972:6869558,6851003:6868674,6853215:6861407,6864848:6867908,6881492:6881690,6889190:6891352,6894094:6894202,6906036:6907047,6921897:6922714,6925484:6925593', 'assoc_mat': '6790887:barquette_opaque:4207:6862547,6794193:barquette_opaque:4207:6862123,6834822:barquette_opaque:4207:6877972,6840554:barquette_opaque:4207:6877707,6845438:barquette_opaque:4207:6869389,6846972:barquette_opaque:4207:6869558,6851003:barquette_opaque:4207:6868674,6853215:barquette_opaque:4207:6861407,6864848:barquette_opaque:4207:6867908,6881492:barquette_opaque:4207:6881690,6889190:barquette_opaque:4207:6891352,6894094:barquette_opaque:4207:6894202,6906036:barquette_opaque:4207:6907047,6921897:barquette_opaque:4207:6922714,6925484:barquette_opaque:4207:6925593'}, {'unwanted_material': 'barquette_opaque', 'main_material': 'emr', 'pht_type': 4209, 'ratio': 8.469862336652651e-05, 'nb_photo': 44, 'list_port_cont': '6626450,6627857,6628405,6628829,6644425,6664932,6665236,6666075,6666652,6669243,6669771,6706891,6712605,6719637,6720391,6720629,6722154,6744912,6762879,6775287,6835808,6841133,6842925,6846016,6852775,6853230', 'assoc_port': '6625827:6626450,6627447:6627857,6627801:6628405,6628455:6628829,6630580:6664932,6630581:6665236,6630822:6666075,6631618:6669771,6639123:6644425,6665718:6666652,6668655:6669243,6706262:6706891,6708643:6712605,6719441:6719637,6719951:6720391,6720202:6720629,6721827:6722154,6744086:6744912,6762224:6762879,6774283:6775287,6834821:6835808,6840554:6841133,6842390:6842925,6845438:6846016,6852117:6852775,6852533:6853230', 'assoc_mat': '6625827:barquette_opaque:4209:6626450,6627447:barquette_opaque:4209:6627857,6627801:barquette_opaque:4209:6628405,6628455:barquette_opaque:4209:6628829,6630580:barquette_opaque:4209:6664932,6630581:barquette_opaque:4209:6665236,6630822:barquette_opaque:4209:6666075,6631618:barquette_opaque:4209:6669771,6639123:barquette_opaque:4209:6644425,6665718:barquette_opaque:4209:6666652,6668655:barquette_opaque:4209:6669243,6706262:barquette_opaque:4209:6706891,6708643:barquette_opaque:4209:6712605,6719441:barquette_opaque:4209:6719637,6719951:barquette_opaque:4209:6720391,6720202:barquette_opaque:4209:6720629,6721827:barquette_opaque:4209:6722154,6744086:barquette_opaque:4209:6744912,6762224:barquette_opaque:4209:6762879,6774283:barquette_opaque:4209:6775287,6834821:barquette_opaque:4209:6835808,6840554:barquette_opaque:4209:6841133,6842390:barquette_opaque:4209:6842925,6845438:barquette_opaque:4209:6846016,6852117:barquette_opaque:4209:6852775,6852533:barquette_opaque:4209:6853230'}, {'unwanted_material': 'carton', 'main_material': 'aluminium', 'pht_type': 4205, 'ratio': 0.01022994561299725, 'nb_photo': 16, 'list_port_cont': '6625532,6880743,6880786', 'assoc_port': '6625304:6625532,6880715:6880786,6880716:6880743', 'assoc_mat': '6625304:carton:4205:6625532,6880715:carton:4205:6880786,6880716:carton:4205:6880743'}, {'unwanted_material': 'carton', 'main_material': 'emr', 'pht_type': 4207, 'ratio': 0.9683717828305286, 'nb_photo': 2565, 'list_port_cont': 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{'unwanted_material': 'papier', 'main_material': 'gm', 'pht_type': 4209, 'ratio': 0.9902901831097267, 'nb_photo': 2955, 'list_port_cont': '6860598,6860874,6861066,6861173,6861345,6861539,6861959,6862604,6863422,6863593,6864917,6865058,6866086,6866174,6876761,6877571,6877655,6877751,6881620,6886395,6888025,6889756,6894811,6902822,6905423,6907081,6909151,6920947', 'assoc_port': '6860529:6861066,6860533:6861173,6860534:6860598,6860536:6860874,6861163:6861539,6861164:6861345,6861513:6861959,6861515:6862604,6863219:6863593,6863221:6863422,6864847:6866174,6864849:6865058,6864854:6864917,6865737:6866086,6876690:6876761,6877477:6877751,6877481:6877655,6877482:6877571,6881493:6881620,6886257:6886395,6887731:6888025,6889188:6889756,6894658:6894811,6899249:6909151,6900676:6902822,6903711:6907081,6905103:6905423,6920015:6920947', 'assoc_mat': '6860529:papier:4209:6861066,6860533:papier:4209:6861173,6860534:papier:4209:6860598,6860536:papier:4209:6860874,6861163:papier:4209:6861539,6861164:papier:4209:6861345,6861513:papier:4209:6861959,6861515:papier:4209:6862604,6863219:papier:4209:6863593,6863221:papier:4209:6863422,6864847:papier:4209:6866174,6864849:papier:4209:6865058,6864854:papier:4209:6864917,6865737:papier:4209:6866086,6876690:papier:4209:6876761,6877477:papier:4209:6877751,6877481:papier:4209:6877655,6877482:papier:4209:6877571,6881493:papier:4209:6881620,6886257:papier:4209:6886395,6887731:papier:4209:6888025,6889188:papier:4209:6889756,6894658:papier:4209:6894811,6899249:papier:4209:6909151,6900676:papier:4209:6902822,6903711:papier:4209:6907081,6905103:papier:4209:6905423,6920015:papier:4209:6920947'}, {'unwanted_material': 'papier', 'main_material': 'pet_fonce', 'pht_type': 4200, 'ratio': 0.010245453120925422, 'nb_photo': 31, 'list_port_cont': '6647707,6861711', 'assoc_port': '6647200:6647707,6861521:6861711', 'assoc_mat': '6647200:papier:4200:6647707,6861521:papier:4200:6861711'}, {'unwanted_material': 'pehd', 'main_material': 'emr', 'pht_type': 4209, 'ratio': 2.520265649788176e-05, 'nb_photo': 2, 'list_port_cont': '6678458', 'assoc_port': '6678032:6678458', 'assoc_mat': '6678032:pehd:4209:6678458'}, {'unwanted_material': 'pet_clair', 'main_material': 'emr', 'pht_type': 4207, 'ratio': 0.0009691335779369147, 'nb_photo': 50, 'list_port_cont': '6862208,6862361,6862535,6862580,6862650,6867917,6868229,6868248,6868281,6868376,6868672,6869102,6869324,6869466,6869550,6877011,6877046,6877191,6877677,6877777,6877812,6877923,6877993,6878035,6886875,6888290,6891353,6896153,6898498,6904509,6907044,6917257,6922719,6925591', 'assoc_port': '6790887:6862535,6832752:6877923,6833565:6878035,6834821:6877993,6836050:6877777,6838973:6877677,6842390:6877812,6846972:6869550,6846973:6869466,6848417:6869324,6851003:6868672,6852533:6869102,6861512:6868229,6861514:6868281,6861516:6868248,6861517:6868376,6861519:6862580,6861520:6862650,6861524:6862208,6861635:6862361,6864848:6867917,6876683:6877191,6876685:6877011,6876686:6877046,6886258:6886875,6887695:6888290,6889190:6891353,6895749:6896153,6898175:6898498,6904057:6904509,6906036:6907044,6917033:6917257,6921897:6922719,6925484:6925591', 'assoc_mat': '6790887:pet_clair:4207:6862535,6832752:pet_clair:4207:6877923,6833565:pet_clair:4207:6878035,6834821:pet_clair:4207:6877993,6836050:pet_clair:4207:6877777,6838973:pet_clair:4207:6877677,6842390:pet_clair:4207:6877812,6846972:pet_clair:4207:6869550,6846973:pet_clair:4207:6869466,6848417:pet_clair:4207:6869324,6851003:pet_clair:4207:6868672,6852533:pet_clair:4207:6869102,6861512:pet_clair:4207:6868229,6861514:pet_clair:4207:6868281,6861516:pet_clair:4207:6868248,6861517:pet_clair:4207:6868376,6861519:pet_clair:4207:6862580,6861520:pet_clair:4207:6862650,6861524:pet_clair:4207:6862208,6861635:pet_clair:4207:6862361,6864848:pet_clair:4207:6867917,6876683:pet_clair:4207:6877191,6876685:pet_clair:4207:6877011,6876686:pet_clair:4207:6877046,6886258:pet_clair:4207:6886875,6887695:pet_clair:4207:6888290,6889190:pet_clair:4207:6891353,6895749:pet_clair:4207:6896153,6898175:pet_clair:4207:6898498,6904057:pet_clair:4207:6904509,6906036:pet_clair:4207:6907044,6917033:pet_clair:4207:6917257,6921897:pet_clair:4207:6922719,6'}, {'unwanted_material': 'pet_clair', 'main_material': 'emr', 'pht_type': 4209, 'ratio': 0.00038788845724592604, 'nb_photo': 52, 'list_port_cont': '6613103,6648162,6655833,6657176,6658378,6660889,6666083,6666651,6666947,6668915,6669550,6669705,6669777,6671157,6700228,6704711,6706879,6709548,6712610,6720621,6722887,6723439,6744920,6748621,6748942,6761453,6774102,6776478,6837016,6841130,6846026,6853934', 'assoc_port': '6612572:6613103,6630822:6666083,6631385:6668915,6631618:6669777,6632901:6671157,6635653:6660889,6647202:6648162,6655088:6655833,6656505:6657176,6656506:6658378,6665067:6666947,6665718:6666651,6668654:6669705,6668657:6669550,6699726:6700228,6700555:6704711,6706262:6706879,6707499:6709548,6708643:6712610,6720202:6720621,6722573:6722887,6723094:6723439,6744086:6744920,6747584:6748621,6748313:6748942,6761126:6761453,6773386:6774102,6776077:6776478,6836050:6837016,6840554:6841130,6845438:6846026,6852534:6853934', 'assoc_mat': '6612572:pet_clair:4209:6613103,6630822:pet_clair:4209:6666083,6631385:pet_clair:4209:6668915,6631618:pet_clair:4209:6669777,6632901:pet_clair:4209:6671157,6635653:pet_clair:4209:6660889,6647202:pet_clair:4209:6648162,6655088:pet_clair:4209:6655833,6656505:pet_clair:4209:6657176,6656506:pet_clair:4209:6658378,6665067:pet_clair:4209:6666947,6665718:pet_clair:4209:6666651,6668654:pet_clair:4209:6669705,6668657:pet_clair:4209:6669550,6699726:pet_clair:4209:6700228,6700555:pet_clair:4209:6704711,6706262:pet_clair:4209:6706879,6707499:pet_clair:4209:6709548,6708643:pet_clair:4209:6712610,6720202:pet_clair:4209:6720621,6722573:pet_clair:4209:6722887,6723094:pet_clair:4209:6723439,6744086:pet_clair:4209:6744920,6747584:pet_clair:4209:6748621,6748313:pet_clair:4209:6748942,6761126:pet_clair:4209:6761453,6773386:pet_clair:4209:6774102,6776077:pet_clair:4209:6776478,6836050:pet_clair:4209:6837016,6840554:pet_clair:4209:6841130,6845438:pet_clair:4209:6846026,6852534:pet_clair:4209:6853934'}, {'unwanted_material': 'pet_clair', 'main_material': 'gm', 'pht_type': 4209, 'ratio': 0.00042088720046359597, 'nb_photo': 1, 'list_port_cont': '6862605', 'assoc_port': '6861515:6862605', 'assoc_mat': '6861515:pet_clair:4209:6862605'}, {'unwanted_material': 'pet_fonce', 'main_material': 'emr', 'pht_type': 4207, 'ratio': 0.0008578698895049885, 'nb_photo': 28, 'list_port_cont': '6860798,6861839,6862207,6868256,6868671,6869549,6877674,6877708,6877816,6877879,6878008,6886869,6888301,6889467,6898496,6904520,6915175,6922716', 'assoc_port': '6832753:6877879,6834821:6878008,6838973:6877674,6840554:6877708,6842390:6877816,6846972:6869549,6851003:6868671,6855642:6860798,6859123:6861839,6861516:6868256,6861524:6862207,6886258:6886869,6887695:6888301,6887698:6889467,6898175:6898496,6904057:6904520,6914259:6915175,6921897:6922716', 'assoc_mat': '6832753:pet_fonce:4207:6877879,6834821:pet_fonce:4207:6878008,6838973:pet_fonce:4207:6877674,6840554:pet_fonce:4207:6877708,6842390:pet_fonce:4207:6877816,6846972:pet_fonce:4207:6869549,6851003:pet_fonce:4207:6868671,6855642:pet_fonce:4207:6860798,6859123:pet_fonce:4207:6861839,6861516:pet_fonce:4207:6868256,6861524:pet_fonce:4207:6862207,6886258:pet_fonce:4207:6886869,6887695:pet_fonce:4207:6888301,6887698:pet_fonce:4207:6889467,6898175:pet_fonce:4207:6898496,6904057:pet_fonce:4207:6904520,6914259:pet_fonce:4207:6915175,6921897:pet_fonce:4207:6922716'}, {'unwanted_material': 'pet_fonce', 'main_material': 'emr', 'pht_type': 4209, 'ratio': 0.002001176734086916, 'nb_photo': 165, 'list_port_cont': '6613106,6614596,6626457,6628830,6629210,6635370,6641607,6642548,6644426,6646347,6647448,6648893,6654377,6659140,6659225,6660883,6661079,6664546,6664700,6665227,6666079,6666644,6666756,6666950,6668662,6669252,6669485,6669785,6671575,6674270,6678461,6683425,6683978,6702227,6704714,6706892,6708972,6709423,6709577,6711293,6712608,6718881,6719276,6719647,6720634,6722892,6723506,6744910,6748597,6762003,6774109,6776983,6841135,6842934,6847565,6859391', 'assoc_port': '6612572:6613106,6614336:6614596,6625827:6626457,6628455:6628830,6628736:6629210,6630577:6664546,6630578:6664700,6630581:6665227,6630822:6666079,6631384:6668662,6631618:6669785,6633545:6635370,6635651:6661079,6635653:6660883,6639123:6644426,6639695:6642548,6640928:6641607,6645791:6646347,6646682:6647448,6648217:6648893,6652800:6654377,6657819:6659140,6659025:6659225,6665067:6666950,6665718:6666644,6665719:6666756,6668655:6669252,6668656:6669485,6670886:6671575,6673850:6674270,6678032:6678461,6682633:6683425,6683289:6683978,6700555:6704714,6701501:6702227,6706262:6706892,6706760:6709423,6707163:6708972,6707499:6709577,6708643:6712608,6708644:6711293,6718520:6719276,6718521:6718881,6719441:6719647,6720202:6720634,6722573:6722892,6723192:6723506,6744086:6744910,6747584:6748597,6759349:6762003,6773386:6774109,6775574:6776983,6840554:6841135,6842390:6842934,6846972:6847565,6859123:6859391', 'assoc_mat': '6612572:pet_fonce:4209:6613106,6614336:pet_fonce:4209:6614596,6625827:pet_fonce:4209:6626457,6628455:pet_fonce:4209:6628830,6628736:pet_fonce:4209:6629210,6630577:pet_fonce:4209:6664546,6630578:pet_fonce:4209:6664700,6630581:pet_fonce:4209:6665227,6630822:pet_fonce:4209:6666079,6631384:pet_fonce:4209:6668662,6631618:pet_fonce:4209:6669785,6633545:pet_fonce:4209:6635370,6635651:pet_fonce:4209:6661079,6635653:pet_fonce:4209:6660883,6639123:pet_fonce:4209:6644426,6639695:pet_fonce:4209:6642548,6640928:pet_fonce:4209:6641607,6645791:pet_fonce:4209:6646347,6646682:pet_fonce:4209:6647448,6648217:pet_fonce:4209:6648893,6652800:pet_fonce:4209:6654377,6657819:pet_fonce:4209:6659140,6659025:pet_fonce:4209:6659225,6665067:pet_fonce:4209:6666950,6665718:pet_fonce:4209:6666644,6665719:pet_fonce:4209:6666756,6668655:pet_fonce:4209:6669252,6668656:pet_fonce:4209:6669485,6670886:pet_fonce:4209:6671575,6673850:pet_fonce:4209:6674270,6678032:pet_fonce:4209:6678461,6682633:pet_fonce:4209:6683425,6683289:pet_fonce:4209:6683978,6'}, {'unwanted_material': 'pet_fonce', 'main_material': 'gm', 'pht_type': 4209, 'ratio': 0.0009882492230258019, 'nb_photo': 2, 'list_port_cont': '6894805', 'assoc_port': '6894658:6894805', 'assoc_mat': '6894658:pet_fonce:4209:6894805'}, {'unwanted_material': 'pet_fonce', 'main_material': 'pet_fonce', 'pht_type': 4200, 'ratio': 0.9832720072705387, 'nb_photo': 21, 'list_port_cont': '6647700,6861697', 'assoc_port': '6647200:6647700,6861521:6861697', 'assoc_mat': '6647200:pet_fonce:4200:6647700,6861521:pet_fonce:4200:6861697'}, {'unwanted_material': 'pet_opaque', 'main_material': 'emr', 'pht_type': 4207, 'ratio': 0.0006428090611349251, 'nb_photo': 9, 'list_port_cont': '6866496,6868369,6869096,6869546,6878036,6904487,6905142,6905991,6922715', 'assoc_port': '6833565:6878036,6846972:6869546,6852533:6869096,6861517:6868369,6864855:6866496,6903710:6905991,6903712:6904487,6905102:6905142,6921897:6922715', 'assoc_mat': '6833565:pet_opaque:4207:6878036,6846972:pet_opaque:4207:6869546,6852533:pet_opaque:4207:6869096,6861517:pet_opaque:4207:6868369,6864855:pet_opaque:4207:6866496,6903710:pet_opaque:4207:6905991,6903712:pet_opaque:4207:6904487,6905102:pet_opaque:4207:6905142,6921897:pet_opaque:4207:6922715'}, {'unwanted_material': 'pet_opaque', 'main_material': 'emr', 'pht_type': 4209, 'ratio': 0.0005744915736568625, 'nb_photo': 214, 'list_port_cont': '6613105,6614118,6616031,6627858,6628408,6628839,6629216,6629282,6635308,6635367,6639706,6640660,6641595,6644422,6647441,6655823,6657172,6658373,6659149,6660897,6661077,6664543,6664634,6664804,6664940,6665229,6666078,6666656,6666757,6666952,6667994,6668664,6668914,6669254,6669547,6669695,6669784,6669814,6670110,6671566,6671848,6672292,6674152,6676774,6678456,6681180,6683428,6683979,6700223,6704719,6706884,6709575,6711305,6712607,6718352,6718715,6719280,6719890,6720396,6722151,6722589,6722891,6723435,6744915,6748617,6748952,6749035,6760254,6761440,6774110,6776978,6813183,6834135,6834365,6834702,6835809,6839582,6841141,6842938,6853225,6853523,6859402', 'assoc_port': '6612572:6613105,6613636:6614118,6614891:6616031,6627447:6627858,6627801:6628408,6627802:6629282,6628455:6628839,6628736:6629216,6630577:6664543,6630579:6664634,6630580:6664940,6630581:6665229,6630822:6666078,6631154:6667994,6631384:6668664,6631385:6668914,6631618:6669784,6631619:6669814,6631901:6670110,6633543:6635308,6633544:6671848,6633545:6635367,6633546:6672292,6635651:6661077,6635653:6660897,6639123:6644422,6639124:6639706,6640066:6640660,6640928:6641595,6646682:6647441,6655088:6655823,6656505:6657172,6656506:6658373,6657819:6659149,6663042:6664804,6665067:6666952,6665718:6666656,6665719:6666757,6668654:6669695,6668655:6669254,6668657:6669547,6670886:6671566,6671756:6676774,6673385:6674152,6678032:6678456,6680947:6681180,6682633:6683428,6683289:6683979,6699726:6700223,6700555:6704719,6706262:6706884,6707499:6709575,6708643:6712607,6708644:6711305,6715973:6718352,6716500:6718715,6717201:6719890,6718520:6719280,6719951:6720396,6721826:6722589,6721827:6722151,6722573:6722891,6723094:6723435,6744086:6744915,', 'assoc_mat': '6612572:pet_opaque:4209:6613105,6613636:pet_opaque:4209:6614118,6614891:pet_opaque:4209:6616031,6627447:pet_opaque:4209:6627858,6627801:pet_opaque:4209:6628408,6627802:pet_opaque:4209:6629282,6628455:pet_opaque:4209:6628839,6628736:pet_opaque:4209:6629216,6630577:pet_opaque:4209:6664543,6630579:pet_opaque:4209:6664634,6630580:pet_opaque:4209:6664940,6630581:pet_opaque:4209:6665229,6630822:pet_opaque:4209:6666078,6631154:pet_opaque:4209:6667994,6631384:pet_opaque:4209:6668664,6631385:pet_opaque:4209:6668914,6631618:pet_opaque:4209:6669784,6631619:pet_opaque:4209:6669814,6631901:pet_opaque:4209:6670110,6633543:pet_opaque:4209:6635308,6633544:pet_opaque:4209:6671848,6633545:pet_opaque:4209:6635367,6633546:pet_opaque:4209:6672292,6635651:pet_opaque:4209:6661077,6635653:pet_opaque:4209:6660897,6639123:pet_opaque:4209:6644422,6639124:pet_opaque:4209:6639706,6640066:pet_opaque:4209:6640660,6640928:pet_opaque:4209:6641595,6646682:pet_opaque:4209:6647441,6655088:pet_opaque:4209:6655823,6656505:pet_opaque:4209:6657172,'}) select count(distinct mtr_photo_id) from MTRUser.mtr_portfolio_photos where mtr_portfolio_id in (select mtr_portfolio_id from MTRPhoto.dashboard_results where dashboard_run_id in(448643,449568,454450,454465,454459,454472,456239,458795,461498,454567,457375,457649,459844,460382,461634,463066,472528,465865,469297,468129,475039,472453,474892,474538,475316,476524,479832,481665,479903)); after get_hostname_from_raspi hasthag : emr hasthag that could be used but not yet : _______carton hasthag : jrm hasthag that could be used but not yet : _______papier hasthag : aluminium hasthag that could be used but not yet : _______metal hasthag : pet_fonce hasthag that could be used but not yet : _______pet_fonce hasthag : gm hasthag that could be used but not yet : _______papier after impurety_average_per_hashtag VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier TODO : Insert select and so on # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier filepath : /home/admin/workarea/git/Velours/python/prod/memo/sla_mensuel/sla_mensuel_Romainville_Presse_2_mois_08_annee_2022.pdf # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! None was removed should we ? donnée sous forme de texte was removed should we ? [ptf_id0,ptf_id1...] was removed should we ? {'emr': {'barquette_opaque': ['barquette_opaque', '0.01%', 44], 'carton': ['carton', '0.78%', 1462], 'ela': ['ela', '0.01%', 3], 'etiquette': ['etiquette', '0.08%', 1049], 'film_plastique': ['film_plastique', '0.01%', 9], 'kraft': ['kraft', '0.11%', 1], 'metal': ['metal', '2.6%', 787], 'papier': ['papier', '96.86%', 148871], 'pehd': ['pehd', '0.0%', 2], 'pet_clair': ['pet_clair', '0.04%', 52], 'pet_fonce': ['pet_fonce', '0.2%', 165], 'pet_opaque': ['pet_opaque', '0.06%', 214]}, 'aluminium': {'carton': ['carton', '1.02%', 16], 'metal': ['metal', '98.97%', 54], 'papier': ['papier', '0.13%', 9]}, 'gm': {'carton': ['carton', '0.29%', 10], 'etiquette': ['etiquette', '0.08%', 16], 'metal': ['metal', '3.43%', 14], 'papier': ['papier', '99.03%', 2955], 'pet_clair': ['pet_clair', '0.04%', 1], 'pet_fonce': ['pet_fonce', '0.1%', 2]}, 'pet_fonce': {'carton': ['carton', '0.59%', 4], 'etiquette': ['etiquette', '0.11%', 5], 'papier': ['papier', '1.02%', 31], 'pet_fonce': ['pet_fonce', '98.33%', 21]}} filepath : /home/admin/workarea/git/Velours/python/prod/memo/sla_mensuel/sla_mensuel_Romainville_Presse_2_mois_08_annee_2022.pdf hash: 9b473a9b7e6f69a2b2147971a7bf4221 for path: /home/admin/workarea/git/Velours/python/prod/memo/sla_mensuel/sla_mensuel_Romainville_Presse_2_mois_08_annee_2022.pdf voici le hostname : marlene hash: 9b473a9b7e6f69a2b2147971a7bf4221 for path: /home/admin/workarea/git/Velours/python/prod/memo/sla_mensuel/sla_mensuel_Romainville_Presse_2_mois_08_annee_2022.pdf ############################### TEST one_day ################################ TODO and TOTEST Removing /home/admin/workarea/git/Velours/python/prod/memo/sla_one_day nb_day : (3, 30) nb deleted : 3 VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11978 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11987 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11986 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11982 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11982 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11985 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11985 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11990 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11990 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11981 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11980 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11980 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11989 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11981 doesn't seem to be define in the database( WARNING : type of input 3 of step 11980 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11978 doesn't seem to be define in the database( WARNING : type of input 2 of step 11982 doesn't seem to be define in the database( WARNING : output 1 of step 11978 have datatype=2 whereas input 1 of step 11985 have datatype=7 WARNING : type of output 2 of step 11985 doesn't seem to be define in the database( WARNING : type of input 1 of step 11979 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11981 have datatype=10 whereas input 3 of step 11988 have datatype=6 WARNING : type of input 2 of step 11990 doesn't seem to be define in the database( WARNING : output 1 of step 11979 have datatype=7 whereas input 2 of step 11990 have datatype=None WARNING : type of output 3 of step 11990 doesn't seem to be define in the database( WARNING : type of input 1 of step 11981 doesn't seem to be define in the database( WARNING : output 0 of step 11981 have datatype=10 whereas input 0 of step 11991 have datatype=18 WARNING : type of input 5 of step 11988 doesn't seem to be define in the database( WARNING : output 0 of step 11991 have datatype=11 whereas input 5 of step 11988 have datatype=None WARNING : type of output 1 of step 11987 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : type of output 1 of step 11986 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : output 0 of step 11985 have datatype=1 whereas input 0 of step 11979 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4461, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,pehd,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'film_plastique', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier Inconsistency in dashboard_places dashboard_places from input : romainville_petite_presse dashboard_name_from_port found from datou STS from crontab from raspi : Romainville_Presse_1 We force the correct camera_place_name ! TODO : Insert select and so on # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11978 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11987 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11986 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11982 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11982 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11985 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11985 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11990 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11990 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11981 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11980 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11980 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11989 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11981 doesn't seem to be define in the database( WARNING : type of input 3 of step 11980 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11978 doesn't seem to be define in the database( WARNING : type of input 2 of step 11982 doesn't seem to be define in the database( WARNING : output 1 of step 11978 have datatype=2 whereas input 1 of step 11985 have datatype=7 WARNING : type of output 2 of step 11985 doesn't seem to be define in the database( WARNING : type of input 1 of step 11979 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11981 have datatype=10 whereas input 3 of step 11988 have datatype=6 WARNING : type of input 2 of step 11990 doesn't seem to be define in the database( WARNING : output 1 of step 11979 have datatype=7 whereas input 2 of step 11990 have datatype=None WARNING : type of output 3 of step 11990 doesn't seem to be define in the database( WARNING : type of input 1 of step 11981 doesn't seem to be define in the database( WARNING : output 0 of step 11981 have datatype=10 whereas input 0 of step 11991 have datatype=18 WARNING : type of input 5 of step 11988 doesn't seem to be define in the database( WARNING : output 0 of step 11991 have datatype=11 whereas input 5 of step 11988 have datatype=None WARNING : type of output 1 of step 11987 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : type of output 1 of step 11986 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : output 0 of step 11985 have datatype=1 whereas input 0 of step 11979 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4461, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,pehd,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'film_plastique', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier TODO TODO : Insert select and so on ***** analysis of device with port 20001 for dashboard romainville_petite_presse ***** **** analysis of day 2022/09/01/ **** VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! WARNING: No hour configured for port 20001, from 00:00 to 24:00 used 0:00:00 apple pause between two photos 10 Unable to retrieve photo time from log, find in sqlite. Find filename in sqlite. Info from logs total number of images : 0 coverage for 10 seconds : 0:00:00 (0.00%) coverage for 20 seconds : 0:00:00 (0.00%) max time between two photos : 0:00:00 results of pre-diagnostic : light ok 5716, not duplicated 5865, two criteria ok 5716, nb forced upload 0 end of day status of photos as found in sqllite Unable to find info for dashboard number 181 for day 2022-09-01 00:00:00 Info from dashboard total number of uploaded images : 0 number of useful images : 5716 number of finished photos : 0 (0.00% of two criteria ok) number of finished photos for older algorithm : 0 (0.00% of two criteria ok) number of started photos : 0 (0.00% of two criteria ok) **** analysis of day 2022/09/02/ **** VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! WARNING: No hour configured for port 20001, from 00:00 to 24:00 used 0:00:00 apple pause between two photos 10 Unable to retrieve photo time from log, find in sqlite. Find filename in sqlite. Info from logs total number of images : 0 coverage for 10 seconds : 0:00:00 (0.00%) coverage for 20 seconds : 0:00:00 (0.00%) max time between two photos : 0:00:00 results of pre-diagnostic : light ok 5716, not duplicated 5865, two criteria ok 5716, nb forced upload 0 end of day status of photos as found in sqllite Unable to find info for dashboard number 181 for day 2022-09-02 00:00:00 Info from dashboard total number of uploaded images : 0 number of useful images : 5716 number of finished photos : 0 (0.00% of two criteria ok) number of finished photos for older algorithm : 0 (0.00% of two criteria ok) number of started photos : 0 (0.00% of two criteria ok) **** analysis of day 2022/09/03/ **** VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! WARNING: No hour configured for port 20001, from 00:00 to 24:00 used 0:00:00 apple pause between two photos 10 Unable to retrieve photo time from log, find in sqlite. Find filename in sqlite. Info from logs total number of images : 0 coverage for 10 seconds : 0:00:00 (0.00%) coverage for 20 seconds : 0:00:00 (0.00%) max time between two photos : 0:00:00 results of pre-diagnostic : light ok 5716, not duplicated 5865, two criteria ok 5716, nb forced upload 0 end of day status of photos as found in sqllite Unable to find info for dashboard number 181 for day 2022-09-03 00:00:00 Info from dashboard total number of uploaded images : 0 number of useful images : 5716 number of finished photos : 0 (0.00% of two criteria ok) number of finished photos for older algorithm : 0 (0.00% of two criteria ok) number of started photos : 0 (0.00% of two criteria ok) **** analysis for all days **** Info from logs total number of images : 0 coverage for 10 seconds : 0:00:00 (0.00%) coverage for 20 seconds : 0:00:00 (0.00%) max time between two photos : 0:00:00 results of pre-diagnostic : light ok 17148, not duplicated 17595, two criteria ok 17148, nb forced upload 0 end of day status of photos as found in sqllite Info from dashboard total number of uploaded images : 0 number of useful images : 17148 number of finished photos : 0 (0.00% of two criteria ok) number of finished photos for older algorithm : 0 (0.00% of two criteria ok) number of started photos : 0 (0.00% of two criteria ok) cvs resume : date,nb_photos,% time,nb ok,uploaded,to upload, % uploaded, nb useful, % completed photos, last_update, remark 2022/09/01,0,0.00%,5716,0,0,0.00%,0,0.00%,0000/00/00, 2022/09/02,0,0.00%,5716,0,0,0.00%,0,0.00%,0000/00/00, 2022/09/03,0,0.00%,5716,0,0,0.00%,0,0.00%,0000/00/00, coverage for this period for every 10 second 2022/09/01/ 0.0 2022/09/02/ 0.0 2022/09/03/ 0.0 mean value for this period : 0.0 coverage for this period for every 20 second 2022/09/01/ 0.0 2022/09/02/ 0.0 2022/09/03/ 0.0 mean value for this period : 0.0 ############################### TEST get_data ################################ TODO and TOTEST VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11978 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11987 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11986 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11982 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11982 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11985 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11985 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11990 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11990 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11981 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11980 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11980 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11989 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11981 doesn't seem to be define in the database( WARNING : type of input 3 of step 11980 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11978 doesn't seem to be define in the database( WARNING : type of input 2 of step 11982 doesn't seem to be define in the database( WARNING : output 1 of step 11978 have datatype=2 whereas input 1 of step 11985 have datatype=7 WARNING : type of output 2 of step 11985 doesn't seem to be define in the database( WARNING : type of input 1 of step 11979 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11981 have datatype=10 whereas input 3 of step 11988 have datatype=6 WARNING : type of input 2 of step 11990 doesn't seem to be define in the database( WARNING : output 1 of step 11979 have datatype=7 whereas input 2 of step 11990 have datatype=None WARNING : type of output 3 of step 11990 doesn't seem to be define in the database( WARNING : type of input 1 of step 11981 doesn't seem to be define in the database( WARNING : output 0 of step 11981 have datatype=10 whereas input 0 of step 11991 have datatype=18 WARNING : type of input 5 of step 11988 doesn't seem to be define in the database( WARNING : output 0 of step 11991 have datatype=11 whereas input 5 of step 11988 have datatype=None WARNING : type of output 1 of step 11987 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : type of output 1 of step 11986 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : output 0 of step 11985 have datatype=1 whereas input 0 of step 11979 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4461, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,pehd,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'film_plastique', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier TODO : Insert select and so on # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11978 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11987 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11986 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11982 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11982 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11985 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11985 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11990 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11990 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11981 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11980 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11980 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11989 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11981 doesn't seem to be define in the database( WARNING : type of input 3 of step 11980 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11978 doesn't seem to be define in the database( WARNING : type of input 2 of step 11982 doesn't seem to be define in the database( WARNING : output 1 of step 11978 have datatype=2 whereas input 1 of step 11985 have datatype=7 WARNING : type of output 2 of step 11985 doesn't seem to be define in the database( WARNING : type of input 1 of step 11979 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11981 have datatype=10 whereas input 3 of step 11988 have datatype=6 WARNING : type of input 2 of step 11990 doesn't seem to be define in the database( WARNING : output 1 of step 11979 have datatype=7 whereas input 2 of step 11990 have datatype=None WARNING : type of output 3 of step 11990 doesn't seem to be define in the database( WARNING : type of input 1 of step 11981 doesn't seem to be define in the database( WARNING : output 0 of step 11981 have datatype=10 whereas input 0 of step 11991 have datatype=18 WARNING : type of input 5 of step 11988 doesn't seem to be define in the database( WARNING : output 0 of step 11991 have datatype=11 whereas input 5 of step 11988 have datatype=None WARNING : type of output 1 of step 11987 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : type of output 1 of step 11986 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : output 0 of step 11985 have datatype=1 whereas input 0 of step 11979 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4461, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,pehd,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'film_plastique', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier nb_day : (0, 31) VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11978 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11987 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11986 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11982 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11982 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11985 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11985 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11990 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11990 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11981 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11980 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11980 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11989 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11981 doesn't seem to be define in the database( WARNING : type of input 3 of step 11980 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11978 doesn't seem to be define in the database( WARNING : type of input 2 of step 11982 doesn't seem to be define in the database( WARNING : output 1 of step 11978 have datatype=2 whereas input 1 of step 11985 have datatype=7 WARNING : type of output 2 of step 11985 doesn't seem to be define in the database( WARNING : type of input 1 of step 11979 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11981 have datatype=10 whereas input 3 of step 11988 have datatype=6 WARNING : type of input 2 of step 11990 doesn't seem to be define in the database( WARNING : output 1 of step 11979 have datatype=7 whereas input 2 of step 11990 have datatype=None WARNING : type of output 3 of step 11990 doesn't seem to be define in the database( WARNING : type of input 1 of step 11981 doesn't seem to be define in the database( WARNING : output 0 of step 11981 have datatype=10 whereas input 0 of step 11991 have datatype=18 WARNING : type of input 5 of step 11988 doesn't seem to be define in the database( WARNING : output 0 of step 11991 have datatype=11 whereas input 5 of step 11988 have datatype=None WARNING : type of output 1 of step 11987 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : type of output 1 of step 11986 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : output 0 of step 11985 have datatype=1 whereas input 0 of step 11979 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4461, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,pehd,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'film_plastique', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier TODO : Insert select and so on # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11978 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11987 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11986 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11982 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11982 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11985 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11985 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11990 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11990 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11981 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11980 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11980 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11989 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11981 doesn't seem to be define in the database( WARNING : type of input 3 of step 11980 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11978 doesn't seem to be define in the database( WARNING : type of input 2 of step 11982 doesn't seem to be define in the database( WARNING : output 1 of step 11978 have datatype=2 whereas input 1 of step 11985 have datatype=7 WARNING : type of output 2 of step 11985 doesn't seem to be define in the database( WARNING : type of input 1 of step 11979 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11981 have datatype=10 whereas input 3 of step 11988 have datatype=6 WARNING : type of input 2 of step 11990 doesn't seem to be define in the database( WARNING : output 1 of step 11979 have datatype=7 whereas input 2 of step 11990 have datatype=None WARNING : type of output 3 of step 11990 doesn't seem to be define in the database( WARNING : type of input 1 of step 11981 doesn't seem to be define in the database( WARNING : output 0 of step 11981 have datatype=10 whereas input 0 of step 11991 have datatype=18 WARNING : type of input 5 of step 11988 doesn't seem to be define in the database( WARNING : output 0 of step 11991 have datatype=11 whereas input 5 of step 11988 have datatype=None WARNING : type of output 1 of step 11987 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : type of output 1 of step 11986 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : output 0 of step 11985 have datatype=1 whereas input 0 of step 11979 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4461, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,pehd,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'film_plastique', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier select count(distinct mtr_photo_id) from MTRUser.mtr_portfolio_photos where mtr_portfolio_id in (select id from MTRUser.mtr_portfolios where id in (select mtr_portfolio_id from MTRPhoto.dashboard_results where dashboard_run_id in(select last_run_id from MTRPhoto.dashboard_entry_day where dashboard_place_id in (select id from MTRPhoto.dashboard_places where name = 'Romainville_Presse_1' and date like '%2022-08%') and created_at like '%2022-08%'))); nb_day : (0, 31) after unwanted_material_data nb_day : (0, 31) after coverage_data after number_of_batch date_start : 2022-08-01 : dt_date_just_month_year : 2022-08-01 00:00:00 : VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! after pl.get_datou_sts_from_crontab : verbose : False no sts found, try to find from database SELECT dri.id FROM MTRPhoto.dashboard_run_ids dri, MTRPhoto.dashboard_entry_day ded, MTRPhoto.dashboard_places dp WHERE dp.name= "Romainville_Presse_1" AND ded.dashboard_place_id=dp.id AND dri.dashboard_entry_day=ded.id AND dri.id=ded.last_run_id AND ded.date >= "2022-08-01" AND ded.date <= "2022-08-31" apple3 {'gm': {'mat': 'gm', 'pht': 4209, 'datou_carac_id': 3994, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'papier'}, 'emr': {'mat': 'emr', 'pht': 4207, 'datou_carac_id': 3993, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'carton'}, 'jrm': {'mat': 'jrm', 'pht': 3726, 'datou_carac_id': 3459, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'papier'}, 'ela': {'mat': 'ela', 'pht': 4203, 'datou_carac_id': 3991, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'ela'}, 'pet_clair': {'mat': 'pet_clair', 'pht': 3327, 'datou_carac_id': 3804, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'pet_clair,bouchon,etiquette,barquette_avec_film'}, 'film_pedb': {'mat': 'film_pedb', 'pht': 4461, 'datou_carac_id': 4322, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'film_plastique'}, 'pehd_pp': {'mat': 'pehd_pp', 'pht': 4211, 'datou_carac_id': 3995, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'pehd'}, 'pet_fonce': {'mat': 'pet_fonce', 'pht': 4200, 'datou_carac_id': 4153, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'pet_fonce'}, 'aluminium': {'mat': 'aluminium', 'pht': 4205, 'datou_carac_id': 3992, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'metal'}, 'refus': {'mat': 'refus', 'pht': 3594, 'datou_carac_id': 3318, 'unwanted_material': [], 'hashtag_majoritaire_from_carac': 'refus'}} SELECT h.hashtag as unwanted_material, substr(dr.hashtag,8) as main_material, ptp.type as pht_type, sum(pcr.value*dr.nombre_balle)/sum(dr.nombre_balle) as ratio, count(distinct mpp.mtr_photo_id) as nb_photo, group_concat(distinct ptp.mtr_portfolio_id_2) as list_port_cont, group_concat(distinct concat(cast(ptp.mtr_portfolio_id_1 as char), ":", cast(ptp.mtr_portfolio_id_2 as char))) as assoc_port, group_concat(distinct concat(cast(ptp.mtr_portfolio_id_1 as char), ":", h.hashtag, ":", cast(ptp.type as char), ":", cast(ptp.mtr_portfolio_id_2 as char))) as assoc_mat FROM MTRPhoto.dashboard_results dr, MTRPhoto.mtr_port_to_port_ids ptp, MTRUser.mtr_portfolio_photos mpp, MTRUser.portfolio_carac_ratio pcr, MTRBack.hashtags h WHERE dr.dashboard_run_id IN (449271,454376,454388,454411,454399,454424,451519,452689,468274,455185,456478,457640,459828,461074,462392,463490,464885,465870,469411,470781,897152,474755,474338,475306,477478,478927,479886) AND dr.mtr_portfolio_id=ptp.mtr_portfolio_id_1 AND dr.qualite >= 0 AND mpp.mtr_portfolio_id=ptp.mtr_portfolio_id_2 AND pcr.portfolio_id=ptp.mtr_portfolio_id_1 AND h.hashtag_id = pcr.hashtag_id AND ptp.type = pcr.hashtag_type AND mpp.hide_status = 0 AND ptp.hashtag_id=h.hashtag_id AND ptp.type IN (4209,4207,3726,4203,3327,4461,4211,4200,4205,3594) group by h.hashtag, dr.hashtag, ptp.type; VR TODO TO BETTER PARSE ! ({'unwanted_material': 'autre', 'main_material': 'pet_clair', 'pht_type': 3327, 'ratio': 0.025985557831013643, 'nb_photo': 16651, 'list_port_cont': '6601211,6601249,6601319,6601376,6601558,6601691,6601783,6601837,6602312,6603611,6603837,6603984,6604939,6606283,6606361,6607127,6607396,6607889,6608318,6608592,6608684,6608960,6609911,6610060,6610278,6610907,6611078,6613725,6614148,6615899,6616064,6616199,6616975,6617461,6617846,6618177,6618947,6620505,6620992,6621119,6621146,6621174,6621388,6621447,6621537,6622105,6622162,6622311,6622378,6622426,6622514,6622647,6622758,6626372,6626974,6626997,6627200,6627837,6628024,6628557,6628624,6629354,6629396,6635806,6635864,6635897,6635947,6635974,6636029,6636109,6636139,6636295,6636316,6636423,6636599,6636674,6636727,6636791,6637048,6637689,6637708,6637756,6637854,6637954,6637974,6638095,6638421,6638597,6638696,6638833,6638947,6638968,6639187,6639299,6639353,6639652,6639761,6639844,6639904,6639965,6640123,6640725,6640745,6640776,6640959,6641209,6641306,6641333,6641484,6641521,6641655,6641820,6641954,6642026,6642079,6642285,6643237,6643372,6643479,6643603,6643631,6643664,6643695,6643718,6643895,6644078,6644458,6644663,', 'assoc_port': '6600535:6601249,6600537:6601691,6600543:6601211,6600545:6601376,6600547:6601558,6600550:6601783,6600553:6601319,6601140:6602312,6601199:6601837,6602727:6603837,6602729:6603984,6602732:6603611,6604400:6604939,6604702:6606361,6605500:6606283,6605502:6607127,6606682:6608318,6606685:6607889,6606687:6607396,6607836:6608592,6607838:6608684,6608144:6608960,6609197:6610060,6609198:6609911,6609963:6610278,6610497:6611078,6610499:6610907,6612953:6613725,6613333:6614148,6614966:6616199,6614968:6616064,6615360:6615899,6616171:6616975,6616960:6618177,6616966:6617461,6616967:6617846,6618310:6618947,6620036:6620505,6620039:6621388,6620042:6620992,6620404:6621146,6620441:6621447,6620445:6621174,6620446:6621537,6620449:6621119,6621639:6622647,6621642:6622758,6621645:6622514,6621650:6622378,6621652:6622426,6621655:6622162,6621656:6622105,6621661:6622311,6625901:6626372,6626270:6626974,6626272:6626997,6626275:6627200,6627097:6627837,6627099:6628024,6627946:6628557,6627948:6628624,6628988:6629354,6628991:6629396,6630847:6635947,', 'assoc_mat': '6600535:autre:3327:6601249,6600537:autre:3327:6601691,6600543:autre:3327:6601211,6600545:autre:3327:6601376,6600547:autre:3327:6601558,6600550:autre:3327:6601783,6600553:autre:3327:6601319,6601140:autre:3327:6602312,6601199:autre:3327:6601837,6602727:autre:3327:6603837,6602729:autre:3327:6603984,6602732:autre:3327:6603611,6604400:autre:3327:6604939,6604702:autre:3327:6606361,6605500:autre:3327:6606283,6605502:autre:3327:6607127,6606682:autre:3327:6608318,6606685:autre:3327:6607889,6606687:autre:3327:6607396,6607836:autre:3327:6608592,6607838:autre:3327:6608684,6608144:autre:3327:6608960,6609197:autre:3327:6610060,6609198:autre:3327:6609911,6609963:autre:3327:6610278,6610497:autre:3327:6611078,6610499:autre:3327:6610907,6612953:autre:3327:6613725,6613333:autre:3327:6614148,6614966:autre:3327:6616199,6614968:autre:3327:6616064,6615360:autre:3327:6615899,6616171:autre:3327:6616975,6616960:autre:3327:6618177,6616966:autre:3327:6617461,6616967:autre:3327:6617846,6618310:autre:3327:6618947,6620036:autre:3327:662050'}, {'unwanted_material': 'barquette_avec_film', 'main_material': 'pet_clair', 'pht_type': 3327, 'ratio': 0.0050634087913797535, 'nb_photo': 1051, 'list_port_cont': '6601216,6601255,6601316,6601366,6601556,6601694,6601795,6601849,6602314,6603610,6603845,6603981,6604938,6606272,6606380,6607136,6607388,6607885,6608324,6608593,6608675,6608967,6609910,6610048,6610273,6611082,6613721,6614147,6615898,6616193,6616972,6617468,6618176,6618950,6620509,6620988,6621144,6621167,6621391,6621449,6622102,6622163,6622316,6622379,6622436,6622519,6622752,6626364,6626973,6627004,6627197,6627840,6628023,6628564,6628623,6629352,6629394,6635811,6635862,6635901,6635945,6635972,6636036,6636112,6636138,6636318,6636424,6636724,6637044,6637685,6637716,6637764,6637852,6637945,6637984,6638094,6638596,6638700,6638835,6638944,6638974,6639298,6639361,6639645,6639764,6639852,6639896,6639968,6640121,6640722,6640783,6640963,6641211,6641294,6641332,6641486,6641520,6641652,6641944,6642022,6642080,6642290,6643373,6643478,6643608,6643683,6643716,6643902,6644079,6644456,6644652,6645162,6645304,6645766,6647408,6648376,6648805,6649738,6651383,6651686,6654487,6654608,6655045,6655877,6656213,6656668,6659085,6660221,', 'assoc_port': '6600535:6601255,6600537:6601694,6600543:6601216,6600545:6601366,6600547:6601556,6600550:6601795,6600553:6601316,6601140:6602314,6601199:6601849,6602727:6603845,6602729:6603981,6602732:6603610,6604400:6604938,6604702:6606380,6605500:6606272,6605502:6607136,6606682:6608324,6606685:6607885,6606687:6607388,6607836:6608593,6607838:6608675,6608144:6608967,6609197:6610048,6609198:6609910,6609963:6610273,6610497:6611082,6612953:6613721,6613333:6614147,6614966:6616193,6615360:6615898,6616171:6616972,6616960:6618176,6616966:6617468,6618310:6618950,6620036:6620509,6620039:6621391,6620042:6620988,6620404:6621144,6620441:6621449,6620445:6621167,6621642:6622752,6621645:6622519,6621650:6622379,6621652:6622436,6621655:6622163,6621656:6622102,6621661:6622316,6625901:6626364,6626270:6626973,6626272:6627004,6626275:6627197,6627097:6627840,6627099:6628023,6627946:6628564,6627948:6628623,6628988:6629352,6628991:6629394,6630847:6635945,6630849:6636036,6630851:6635972,6630854:6637685,6630934:6637764,6630936:6637716,6630938:6638094,', 'assoc_mat': '6600535:barquette_avec_film:3327:6601255,6600537:barquette_avec_film:3327:6601694,6600543:barquette_avec_film:3327:6601216,6600545:barquette_avec_film:3327:6601366,6600547:barquette_avec_film:3327:6601556,6600550:barquette_avec_film:3327:6601795,6600553:barquette_avec_film:3327:6601316,6601140:barquette_avec_film:3327:6602314,6601199:barquette_avec_film:3327:6601849,6602727:barquette_avec_film:3327:6603845,6602729:barquette_avec_film:3327:6603981,6602732:barquette_avec_film:3327:6603610,6604400:barquette_avec_film:3327:6604938,6604702:barquette_avec_film:3327:6606380,6605500:barquette_avec_film:3327:6606272,6605502:barquette_avec_film:3327:6607136,6606682:barquette_avec_film:3327:6608324,6606685:barquette_avec_film:3327:6607885,6606687:barquette_avec_film:3327:6607388,6607836:barquette_avec_film:3327:6608593,6607838:barquette_avec_film:3327:6608675,6608144:barquette_avec_film:3327:6608967,6609197:barquette_avec_film:3327:6610048,6609198:barquette_avec_film:3327:6609910,6609963:barquette_avec_film:3327:6610273'}, {'unwanted_material': 'barquette_opaque', 'main_material': 'ela', 'pht_type': 4203, 'ratio': 0.0006065490165070008, 'nb_photo': 9, 'list_port_cont': '6603426,6627334,6634749,6723417,6780640,6834099,6852168', 'assoc_port': '6602731:6603426,6626721:6627334,6630937:6634749,6671808:6834099,6722813:6723417,6780026:6780640,6851650:6852168', 'assoc_mat': '6602731:barquette_opaque:4203:6603426,6626721:barquette_opaque:4203:6627334,6630937:barquette_opaque:4203:6634749,6671808:barquette_opaque:4203:6834099,6722813:barquette_opaque:4203:6723417,6780026:barquette_opaque:4203:6780640,6851650:barquette_opaque:4203:6852168'}, {'unwanted_material': 'barquette_opaque', 'main_material': 'emr', 'pht_type': 4209, 'ratio': 0.0005293780694215035, 'nb_photo': 1, 'list_port_cont': '6692906', 'assoc_port': '6691778:6692906', 'assoc_mat': '6691778:barquette_opaque:4209:6692906'}, {'unwanted_material': 'barquette_opaque', 'main_material': 'pehd_pp', 'pht_type': 4211, 'ratio': 0.008662761320534096, 'nb_photo': 659, 'list_port_cont': '6600860,6600903,6601023,6601433,6602273,6602593,6603403,6606082,6607689,6608069,6608289,6609462,6610653,6614532,6615427,6615792,6616525,6618779,6618922,6620328,6621053,6621664,6621960,6622002,6622135,6622199,6624057,6626607,6627268,6628481,6629183,6629252,6634382,6635139,6638289,6638441,6640989,6642058,6642706,6650155,6650276,6650959,6658495,6664041,6668175,6669610,6672035,6674014,6674549,6674630,6674772,6675081,6675105,6675139,6675482,6676524,6677132,6677217,6678042,6678216,6678577,6678660,6678688,6678769,6678960,6678988,6681252,6687138,6692292,6693194,6693681,6693891,6694045,6694217,6694420,6698421,6698805,6699377,6699427,6700669,6707231,6711232,6711409,6711495,6712142,6713437,6713607,6713753,6714397,6716562,6717498,6717555,6718025,6719023,6719736,6720660,6720723,6721143,6721925,6722677,6723045,6723102,6724740,6724912,6724973,6725830,6729866,6730263,6730718,6731855,6732324,6732440,6735375,6738136,6740197,6740602,6741090,6741939,6743256,6743597,6743876,6745278,6747827,6751581,6751678,6751683,6752336,6754140,', 'assoc_port': '10844008:10846065,10844009:10845784,10844011:10845552,10844012:10845981,10844014:10845176,10844016:10845161,10844017:10845129,10844018:10844946,10844019:10845048,10844020:10844679,12107427:12108055,12107429:12107821,6600536:6601433,6600544:6600860,6600546:6601023,6600551:6600903,6601138:6602593,6601649:6602273,6602733:6603403,6604399:6608069,6605499:6610653,6605688:6606082,6606683:6607689,6607839:6608289,6609199:6609462,6614199:6614532,6614969:6615427,6615362:6615792,6616173:6616525,6618307:6618779,6618311:6618922,6620040:6620328,6620422:6621664,6620444:6621053,6621638:6624057,6621647:6622199,6621651:6622135,6621654:6621960,6621659:6622002,6626268:6626607,6627098:6627268,6627945:6628481,6628987:6629183,6628989:6629252,6630852:6674014,6630932:6674630,6630935:6674772,6630939:6675105,6631065:6675081,6631069:6675482,6631193:6635139,6631477:6676524,6631489:6677132,6631492:6677217,6631967:6634382,6632585:6678216,6632660:6678577,6632663:6678660,6632714:6678769,6632787:6678688,6632877:6678960,6632881:6678988,6635669:', 'assoc_mat': '10844008:barquette_opaque:4211:10846065,10844009:barquette_opaque:4211:10845784,10844011:barquette_opaque:4211:10845552,10844012:barquette_opaque:4211:10845981,10844014:barquette_opaque:4211:10845176,10844016:barquette_opaque:4211:10845161,10844017:barquette_opaque:4211:10845129,10844018:barquette_opaque:4211:10844946,10844019:barquette_opaque:4211:10845048,10844020:barquette_opaque:4211:10844679,12107427:barquette_opaque:4211:12108055,12107429:barquette_opaque:4211:12107821,6600536:barquette_opaque:4211:6601433,6600544:barquette_opaque:4211:6600860,6600546:barquette_opaque:4211:6601023,6600551:barquette_opaque:4211:6600903,6601138:barquette_opaque:4211:6602593,6601649:barquette_opaque:4211:6602273,6602733:barquette_opaque:4211:6603403,6604399:barquette_opaque:4211:6608069,6605499:barquette_opaque:4211:6610653,6605688:barquette_opaque:4211:6606082,6606683:barquette_opaque:4211:6607689,6607839:barquette_opaque:4211:6608289,6609199:barquette_opaque:4211:6609462,6614199:barquette_opaque:4211:6614532,6614969:barq'}, {'unwanted_material': 'barquette_opaque', 'main_material': 'pet_fonce', 'pht_type': 4200, 'ratio': 0.0009915902324084817, 'nb_photo': 5, 'list_port_cont': '6649286,6687459,6784020,6813915,6920756', 'assoc_port': '6631070:6649286,6686295:6687459,6782249:6784020,6813389:6813915,6920100:6920756', 'assoc_mat': '6631070:barquette_opaque:4200:6649286,6686295:barquette_opaque:4200:6687459,6782249:barquette_opaque:4200:6784020,6813389:barquette_opaque:4200:6813915,6920100:barquette_opaque:4200:6920756'}, {'unwanted_material': 'bouchon', 'main_material': 'pet_clair', 'pht_type': 3327, 'ratio': 0.002148587132747826, 'nb_photo': 2481, 'list_port_cont': 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'assoc_port': 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{'unwanted_material': 'pet_opaque', 'main_material': 'ela', 'pht_type': 4203, 'ratio': 0.0009264502462378221, 'nb_photo': 9, 'list_port_cont': '6608814,6660097,6712722,6735145,6799275,6808109,6869931', 'assoc_port': '6608146:6608814,6632879:6660097,6685476:6799275,6690887:6735145,6712332:6712722,6786466:6808109,6869544:6869931', 'assoc_mat': '6608146:pet_opaque:4203:6608814,6632879:pet_opaque:4203:6660097,6685476:pet_opaque:4203:6799275,6690887:pet_opaque:4203:6735145,6712332:pet_opaque:4203:6712722,6786466:pet_opaque:4203:6808109,6869544:pet_opaque:4203:6869931'}, {'unwanted_material': 'pet_opaque', 'main_material': 'emr', 'pht_type': 4209, 'ratio': 0.007255625347838711, 'nb_photo': 19, 'list_port_cont': '6616740,6617521,6620419,6621938,6627043,6638500,6668139,6668209,6670564,6670896,6678093,6740485,6791207', 'assoc_port': 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'6600901,6602283,6603013,6606069,6608294,6610401,6610657,6611146,6614528,6615400,6621062,6621675,6621998,6622129,6622205,6626613,6629184,6629244,6634651,6635837,6638286,6639164,6650157,6668179,6669616,6672038,6674023,6674634,6674773,6675099,6675136,6677119,6677811,6678215,6678578,6678957,6679224,6681250,6691510,6691659,6693900,6694213,6694417,6698434,6698768,6698799,6699430,6711411,6711493,6712146,6712497,6712754,6713439,6716561,6717501,6717546,6718028,6719452,6720657,6720722,6724914,6725690,6725833,6728841,6729870,6730329,6730727,6731863,6732437,6735376,6738126,6740205,6740607,6741938,6743382,6745286,6751579,6751673,6754142,6754990,6755968,6756060,6756975,6762171,6763524,6767274,6768410,6773018,6774679,6775056,6778932,6780264,6780486,6783061,6791499,6793831,6794248,6794400,6795572,6796823,6799103,6799441,6799779,6800492,6800530,6801272,6801402,6806174,6808133,6808682,6808713,6808832,6808873,6809086,6810005,6815419,6822330,6839899,6842610,6853846,6855228,6855448,6863478,6866679,6869888,6870654,6875922,6890225,', 'assoc_port': '10844011:10845551,10844021:10844440,6600551:6600901,6601649:6602283,6602728:6603013,6605499:6610657,6605688:6606069,6607835:6610401,6607839:6608294,6610992:6611146,6614199:6614528,6614967:6615400,6620422:6621675,6620444:6621062,6621647:6622205,6621651:6622129,6621659:6621998,6626268:6626613,6628987:6629184,6628989:6629244,6630852:6674023,6630856:6634651,6630932:6674634,6630935:6674773,6630939:6675099,6631489:6677119,6631960:6677811,6632585:6678215,6632660:6678578,6632877:6678957,6632963:6679224,6633862:6635837,6635671:6693900,6635682:6694213,6637236:6698768,6637845:6638286,6638776:6639164,6640595:6806174,6647215:6717546,6648944:6650157,6653523:6725690,6654038:6724914,6654837:6725833,6655426:6728841,6656895:6729870,6657891:6731863,6666361:6668179,6668952:6751579,6668953:6669616,6671805:6756060,6671810:6672038,6672701:6755968,6674723:6675136,6681005:6681250,6683620:6691510,6685431:6799103,6685494:6799441,6685525:6799779,6686006:6855228,6686021:6855448,6686094:6800530,6686269:6800492,6686302:6801272,6686308:6801', 'assoc_mat': '10844011:pet_opaque:4211:10845551,10844021:pet_opaque:4211:10844440,6600551:pet_opaque:4211:6600901,6601649:pet_opaque:4211:6602283,6602728:pet_opaque:4211:6603013,6605499:pet_opaque:4211:6610657,6605688:pet_opaque:4211:6606069,6607835:pet_opaque:4211:6610401,6607839:pet_opaque:4211:6608294,6610992:pet_opaque:4211:6611146,6614199:pet_opaque:4211:6614528,6614967:pet_opaque:4211:6615400,6620422:pet_opaque:4211:6621675,6620444:pet_opaque:4211:6621062,6621647:pet_opaque:4211:6622205,6621651:pet_opaque:4211:6622129,6621659:pet_opaque:4211:6621998,6626268:pet_opaque:4211:6626613,6628987:pet_opaque:4211:6629184,6628989:pet_opaque:4211:6629244,6630852:pet_opaque:4211:6674023,6630856:pet_opaque:4211:6634651,6630932:pet_opaque:4211:6674634,6630935:pet_opaque:4211:6674773,6630939:pet_opaque:4211:6675099,6631489:pet_opaque:4211:6677119,6631960:pet_opaque:4211:6677811,6632585:pet_opaque:4211:6678215,6632660:pet_opaque:4211:6678578,6632877:pet_opaque:4211:6678957,6632963:pet_opaque:4211:6679224,6633862:pet_opaque:4211:6635'}, {'unwanted_material': 'pet_opaque', 'main_material': 'pet_fonce', 'pht_type': 4200, 'ratio': 0.006625372408584668, 'nb_photo': 447, 'list_port_cont': '6600927,6602060,6604867,6606114,6609165,6613073,6615618,6618507,6620186,6620865,6621897,6626785,6628362,6634254,6635389,6637069,6637443,6638357,6639233,6641563,6646016,6647330,6649289,6649475,6649908,6653440,6654682,6655700,6658472,6662384,6665186,6669577,6670052,6672606,6674518,6683671,6684478,6686802,6687225,6687464,6696442,6696817,6698458,6711562,6712277,6712786,6714508,6717607,6719819,6720158,6720206,6720247,6720358,6721243,6722532,6724146,6739282,6740800,6745521,6745789,6750245,6754191,6754564,6759415,6765265,6766702,6767358,6780406,6780528,6780714,6784016,6786843,6788645,6791330,6793704,6795548,6797668,6817665,6821371,6824096,6835190,6840200,6842443,6849228,6851781,6852374,6854530,6859022,6862735,6865768,6866326,6867982,6869259,6874403,6875763,6882730,6886804,6888096,6889498,6895283,6900338,6902503,6904834,6914452,6920753,6921628,6924247', 'assoc_port': '6600538:6600927,6601136:6602060,6604397:6604867,6605689:6606114,6608145:6609165,6612632:6613073,6615365:6615618,6618309:6618507,6620043:6620186,6620439:6620865,6621653:6621897,6626271:6626785,6627944:6628362,6630848:6646016,6631070:6649289,6631186:6634254,6631194:6649908,6631961:6655700,6632583:6662384,6632786:6635389,6632966:6670052,6635673:6637443,6635681:6637069,6637843:6638357,6638774:6639233,6641286:6641563,6646447:6647330,6648940:6649475,6650951:6653440,6654041:6654682,6657889:6658472,6664429:6665186,6668950:6669577,6671809:6672606,6673895:6674518,6681680:6683671,6683618:6684478,6685440:6720358,6685511:6720206,6686027:6719819,6686041:6720158,6686295:6687464,6686312:6687225,6686325:6686802,6688871:6714508,6690894:6698458,6693641:6696442,6696476:6696817,6710860:6711562,6711680:6712277,6712324:6712786,6716688:6717607,6718843:6720247,6720803:6721243,6722354:6722532,6723892:6724146,6738748:6739282,6740018:6740800,6740709:6745521,6744268:6745789,6748062:6750245,6753406:6754564,6753419:6754191,6759057:6759415,', 'assoc_mat': '6600538:pet_opaque:4200:6600927,6601136:pet_opaque:4200:6602060,6604397:pet_opaque:4200:6604867,6605689:pet_opaque:4200:6606114,6608145:pet_opaque:4200:6609165,6612632:pet_opaque:4200:6613073,6615365:pet_opaque:4200:6615618,6618309:pet_opaque:4200:6618507,6620043:pet_opaque:4200:6620186,6620439:pet_opaque:4200:6620865,6621653:pet_opaque:4200:6621897,6626271:pet_opaque:4200:6626785,6627944:pet_opaque:4200:6628362,6630848:pet_opaque:4200:6646016,6631070:pet_opaque:4200:6649289,6631186:pet_opaque:4200:6634254,6631194:pet_opaque:4200:6649908,6631961:pet_opaque:4200:6655700,6632583:pet_opaque:4200:6662384,6632786:pet_opaque:4200:6635389,6632966:pet_opaque:4200:6670052,6635673:pet_opaque:4200:6637443,6635681:pet_opaque:4200:6637069,6637843:pet_opaque:4200:6638357,6638774:pet_opaque:4200:6639233,6641286:pet_opaque:4200:6641563,6646447:pet_opaque:4200:6647330,6648940:pet_opaque:4200:6649475,6650951:pet_opaque:4200:6653440,6654041:pet_opaque:4200:6654682,6657889:pet_opaque:4200:6658472,6664429:pet_opaque:4200:6665186,'}, {'unwanted_material': 'textiles_sanitaires', 'main_material': 'ela', 'pht_type': 4203, 'ratio': 5.317677982697793e-05, 'nb_photo': 1, 'list_port_cont': '6754069', 'assoc_port': '6753416:6754069', 'assoc_mat': '6753416:textiles_sanitaires:4203:6754069'}, {'unwanted_material': 'textiles_sanitaires', 'main_material': 'pehd_pp', 'pht_type': 4211, 'ratio': 0.00014015295179752374, 'nb_photo': 14, 'list_port_cont': '6608063,6675111,6678967,6709734,6720656,6724749,6725824,6735649,6787860,6791503,6813248,6828520,6855445,10845973', 'assoc_port': '10844012:10845973,6604399:6608063,6630939:6675111,6632877:6678967,6654837:6725824,6663625:6735649,6686021:6855445,6709374:6709734,6720298:6720656,6724591:6724749,6787210:6787860,6790919:6791503,6812962:6813248,6814154:6828520', 'assoc_mat': '10844012:textiles_sanitaires:4211:10845973,6604399:textiles_sanitaires:4211:6608063,6630939:textiles_sanitaires:4211:6675111,6632877:textiles_sanitaires:4211:6678967,6654837:textiles_sanitaires:4211:6725824,6663625:textiles_sanitaires:4211:6735649,6686021:textiles_sanitaires:4211:6855445,6709374:textiles_sanitaires:4211:6709734,6720298:textiles_sanitaires:4211:6720656,6724591:textiles_sanitaires:4211:6724749,6787210:textiles_sanitaires:4211:6787860,6790919:textiles_sanitaires:4211:6791503,6812962:textiles_sanitaires:4211:6813248,6814154:textiles_sanitaires:4211:6828520'}) select count(distinct mtr_photo_id) from MTRUser.mtr_portfolio_photos where mtr_portfolio_id in (select mtr_portfolio_id from MTRPhoto.dashboard_results where dashboard_run_id in(449271,454376,454388,454411,454399,454424,451519,452689,468274,455185,456478,457640,459828,461074,462392,463490,464885,465870,469411,470781,897152,474755,474338,475306,477478,478927,479886)); after get_hostname_from_raspi hasthag : emr hasthag that could be used but not yet : _______carton hasthag : jrm hasthag that could be used but not yet : _______papier hasthag : aluminium hasthag that could be used but not yet : _______metal hasthag : pet_fonce hasthag that could be used but not yet : _______pet_fonce hasthag : gm hasthag that could be used but not yet : _______papier after impurety_average_per_hashtag ############################### TEST csv ################################ Removing /home/admin/workarea/git/Velours/python/prod/memo/sla_csv VR TODO TOCHECK : due to this bug it shouldn't have being able to work, or maybe it was due to a change directory not done ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11978 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11987 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11986 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11982 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11982 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11985 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11985 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11990 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11990 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11981 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11980 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11980 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11989 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11981 doesn't seem to be define in the database( WARNING : type of input 3 of step 11980 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11978 doesn't seem to be define in the database( WARNING : type of input 2 of step 11982 doesn't seem to be define in the database( WARNING : output 1 of step 11978 have datatype=2 whereas input 1 of step 11985 have datatype=7 WARNING : type of output 2 of step 11985 doesn't seem to be define in the database( WARNING : type of input 1 of step 11979 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11981 have datatype=10 whereas input 3 of step 11988 have datatype=6 WARNING : type of input 2 of step 11990 doesn't seem to be define in the database( WARNING : output 1 of step 11979 have datatype=7 whereas input 2 of step 11990 have datatype=None WARNING : type of output 3 of step 11990 doesn't seem to be define in the database( WARNING : type of input 1 of step 11981 doesn't seem to be define in the database( WARNING : output 0 of step 11981 have datatype=10 whereas input 0 of step 11991 have datatype=18 WARNING : type of input 5 of step 11988 doesn't seem to be define in the database( WARNING : output 0 of step 11991 have datatype=11 whereas input 5 of step 11988 have datatype=None WARNING : type of output 1 of step 11987 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : type of output 1 of step 11986 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : output 0 of step 11985 have datatype=1 whereas input 0 of step 11979 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4461, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,pehd,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'film_plastique', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier TODO : Insert select and so on # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11488 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11496 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11497 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11495 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11495 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11489 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11575 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11575 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11491 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11490 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11490 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11498 send_mail_cod have less outputs used (0) than in the step definition (1) : some outputs may be not used ! Step 11499 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11491 doesn't seem to be define in the database( WARNING : type of input 3 of step 11490 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11488 doesn't seem to be define in the database( WARNING : type of input 2 of step 11492 doesn't seem to be define in the database( WARNING : output 1 of step 11488 have datatype=2 whereas input 1 of step 11495 have datatype=7 WARNING : type of output 2 of step 11495 doesn't seem to be define in the database( WARNING : type of input 1 of step 11489 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11491 have datatype=10 whereas input 3 of step 11498 have datatype=6 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11575 doesn't seem to be define in the database( WARNING : output 1 of step 11489 have datatype=7 whereas input 2 of step 11575 have datatype=None WARNING : type of output 3 of step 11575 doesn't seem to be define in the database( WARNING : type of input 1 of step 11491 doesn't seem to be define in the database( WARNING : output 0 of step 11491 have datatype=10 whereas input 0 of step 11581 have datatype=18 WARNING : type of input 5 of step 11498 doesn't seem to be define in the database( WARNING : output 0 of step 11581 have datatype=11 whereas input 5 of step 11498 have datatype=None WARNING : type of output 1 of step 11496 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : type of output 1 of step 11497 doesn't seem to be define in the database( WARNING : type of input 3 of step 11492 doesn't seem to be define in the database( WARNING : output 0 of step 11495 have datatype=1 whereas input 0 of step 11489 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4209, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'papier', 'hashtag_weights': {'barquette_opaque': 0.7, 'carton': 0.7, 'ela': 0.7, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.7, 'metal': 1.5, 'pehd': 0.7, 'pet_clair': 0.7, 'pet_opaque': 0.7, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.7}, 'ETA': 600} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11500 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11508 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11509 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11504 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11504 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11507 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11507 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11501 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11576 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11576 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11503 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11502 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11502 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11511 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11503 doesn't seem to be define in the database( WARNING : type of input 3 of step 11502 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11500 doesn't seem to be define in the database( WARNING : type of input 2 of step 11504 doesn't seem to be define in the database( WARNING : output 1 of step 11500 have datatype=2 whereas input 1 of step 11507 have datatype=7 WARNING : type of output 2 of step 11507 doesn't seem to be define in the database( WARNING : type of input 1 of step 11501 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11503 have datatype=10 whereas input 3 of step 11510 have datatype=6 WARNING : type of input 2 of step 11576 doesn't seem to be define in the database( WARNING : output 1 of step 11501 have datatype=7 whereas input 2 of step 11576 have datatype=None WARNING : type of output 3 of step 11576 doesn't seem to be define in the database( WARNING : type of input 1 of step 11503 doesn't seem to be define in the database( WARNING : output 0 of step 11503 have datatype=10 whereas input 0 of step 11582 have datatype=18 WARNING : type of input 5 of step 11510 doesn't seem to be define in the database( WARNING : output 0 of step 11582 have datatype=11 whereas input 5 of step 11510 have datatype=None WARNING : type of output 1 of step 11508 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : type of output 1 of step 11509 doesn't seem to be define in the database( WARNING : type of input 3 of step 11504 doesn't seem to be define in the database( WARNING : output 0 of step 11507 have datatype=1 whereas input 0 of step 11501 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4207, 'hashtag_proportion': 'barquette_opaque,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'carton', 'hashtag_weights': {'barquette_opaque': 1, 'ela': 1, 'etiquette': 1.0, 'film_plastique': 0.5, 'kraft': 1, 'metal': 3.0, 'papier': 1, 'pehd': 2, 'pet_clair': 2, 'pet_opaque': 2, 'textiles_sanitaires': 1.0, 'pet_fonce': 2}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11449 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11452 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Step 11452 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11453 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11453 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11454 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11478 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11478 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11456 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11455 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11455 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11458 send_mail_cod have less inputs used (3) than in the step definition (5) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11449 doesn't seem to be define in the database( WARNING : type of input 2 of step 11452 doesn't seem to be define in the database( WARNING : output 1 of step 11449 have datatype=2 whereas input 1 of step 11453 have datatype=7 WARNING : type of output 2 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11454 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 11453 doesn't seem to be define in the database( WARNING : type of input 1 of step 11456 doesn't seem to be define in the database( WARNING : type of output 1 of step 11456 doesn't seem to be define in the database( WARNING : type of input 3 of step 11455 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11456 have datatype=10 whereas input 3 of step 11458 have datatype=6 WARNING : type of input 5 of step 11458 doesn't seem to be define in the database( WARNING : output 0 of step 11477 have datatype=11 whereas input 5 of step 11458 have datatype=None WARNING : output 0 of step 11456 have datatype=10 whereas input 0 of step 11477 have datatype=18 WARNING : type of input 2 of step 11478 doesn't seem to be define in the database( WARNING : output 1 of step 11454 have datatype=7 whereas input 2 of step 11478 have datatype=None WARNING : type of output 3 of step 11478 doesn't seem to be define in the database( WARNING : type of input 2 of step 11456 doesn't seem to be define in the database( WARNING : output 0 of step 11453 have datatype=1 whereas input 0 of step 11454 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3726, 'hashtag_proportion': 'Carton_brun,Carton_gris,Teint_Dans_La_Masse,autre_refus,cartonnette,kraft,metal,plastique', 'hashtag_parmi': 'papier', 'hashtag_weights': {'Carton_brun': 1.5, 'Carton_gris': 1.5, 'Teint_Dans_La_Masse': 1.0, 'autre_refus': 1.5, 'cartonnette': 1.0, 'kraft': 1.5, 'metal': 3, 'plastique': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11512 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11521 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11520 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11516 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11516 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11519 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11519 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11513 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11577 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11577 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11515 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11514 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11514 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11523 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11515 doesn't seem to be define in the database( WARNING : type of input 3 of step 11514 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11512 doesn't seem to be define in the database( WARNING : type of input 2 of step 11516 doesn't seem to be define in the database( WARNING : output 1 of step 11512 have datatype=2 whereas input 1 of step 11519 have datatype=7 WARNING : type of output 2 of step 11519 doesn't seem to be define in the database( WARNING : type of input 1 of step 11513 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11515 have datatype=10 whereas input 3 of step 11522 have datatype=6 WARNING : type of input 2 of step 11577 doesn't seem to be define in the database( WARNING : output 1 of step 11513 have datatype=7 whereas input 2 of step 11577 have datatype=None WARNING : type of output 3 of step 11577 doesn't seem to be define in the database( WARNING : type of input 1 of step 11515 doesn't seem to be define in the database( WARNING : output 0 of step 11515 have datatype=10 whereas input 0 of step 11583 have datatype=18 WARNING : type of input 5 of step 11522 doesn't seem to be define in the database( WARNING : output 0 of step 11583 have datatype=11 whereas input 5 of step 11522 have datatype=None WARNING : type of output 1 of step 11521 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : type of output 1 of step 11520 doesn't seem to be define in the database( WARNING : type of input 3 of step 11516 doesn't seem to be define in the database( WARNING : output 0 of step 11519 have datatype=1 whereas input 0 of step 11513 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4203, 'hashtag_proportion': 'barquette_opaque,carton,etiquette,film_plastique,kraft,metal,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'ela', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1, 'etiquette': 0.5, 'film_plastique': 0.5, 'kraft': 0.8, 'metal': 2, 'papier': 0.8, 'pehd': 0.8, 'pet_clair': 0.8, 'pet_opaque': 0.8, 'textiles_sanitaires': 0.5, 'pet_fonce': 0.8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11560 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 11567 mask_detect have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11567 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11563 crop_condition is not consistent : 4 used against 2 in the step definition ! Step 11563 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11564 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11564 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11565 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11573 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11573 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11568 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11566 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11566 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 1 of step 11560 have datatype=2 whereas input 1 of step 11564 have datatype=7 WARNING : type of output 2 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11565 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11567 doesn't seem to be define in the database( WARNING : type of input 3 of step 11563 doesn't seem to be define in the database( WARNING : type of output 3 of step 11564 doesn't seem to be define in the database( WARNING : type of input 1 of step 11568 doesn't seem to be define in the database( WARNING : type of output 1 of step 11568 doesn't seem to be define in the database( WARNING : type of input 3 of step 11566 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11570 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of input 2 of step 11563 doesn't seem to be define in the database( WARNING : output 0 of step 11569 have datatype=6 whereas input 2 of step 11563 have datatype=None WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11570 doesn't seem to be define in the database( WARNING : type of output 2 of step 11560 doesn't seem to be define in the database( WARNING : type of input 1 of step 11569 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11568 have datatype=10 whereas input 3 of step 11571 have datatype=6 WARNING : type of input 2 of step 11573 doesn't seem to be define in the database( WARNING : output 1 of step 11565 have datatype=7 whereas input 2 of step 11573 have datatype=None WARNING : type of output 3 of step 11573 doesn't seem to be define in the database( WARNING : type of input 3 of step 11568 doesn't seem to be define in the database( WARNING : output 0 of step 11568 have datatype=10 whereas input 0 of step 11587 have datatype=18 WARNING : type of input 5 of step 11571 doesn't seem to be define in the database( WARNING : output 0 of step 11587 have datatype=11 whereas input 5 of step 11571 have datatype=None WARNING : output 0 of step 11564 have datatype=1 whereas input 0 of step 11565 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3327, 'hashtag_proportion': 'autre,carton,metal,papier,pehd,pet_fonce', 'hashtag_parmi': 'pet_clair,bouchon,etiquette,barquette_avec_film', 'hashtag_weights': {'autre': 8.0, 'barquette_avec_film': 6, 'carton': 8.0, 'metal': 12, 'papier': 5, 'pehd': 8, 'pet_fonce': 8, 'bouchon': 8, 'etiquette': 8}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11978 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11987 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11986 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11982 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11982 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11985 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11985 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11979 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11990 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11990 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11981 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11980 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11980 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11989 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11981 doesn't seem to be define in the database( WARNING : type of input 3 of step 11980 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11978 doesn't seem to be define in the database( WARNING : type of input 2 of step 11982 doesn't seem to be define in the database( WARNING : output 1 of step 11978 have datatype=2 whereas input 1 of step 11985 have datatype=7 WARNING : type of output 2 of step 11985 doesn't seem to be define in the database( WARNING : type of input 1 of step 11979 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11981 have datatype=10 whereas input 3 of step 11988 have datatype=6 WARNING : type of input 2 of step 11990 doesn't seem to be define in the database( WARNING : output 1 of step 11979 have datatype=7 whereas input 2 of step 11990 have datatype=None WARNING : type of output 3 of step 11990 doesn't seem to be define in the database( WARNING : type of input 1 of step 11981 doesn't seem to be define in the database( WARNING : output 0 of step 11981 have datatype=10 whereas input 0 of step 11991 have datatype=18 WARNING : type of input 5 of step 11988 doesn't seem to be define in the database( WARNING : output 0 of step 11991 have datatype=11 whereas input 5 of step 11988 have datatype=None WARNING : type of output 1 of step 11987 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : type of output 1 of step 11986 doesn't seem to be define in the database( WARNING : type of input 3 of step 11982 doesn't seem to be define in the database( WARNING : output 0 of step 11985 have datatype=1 whereas input 0 of step 11979 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4461, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,pehd,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'film_plastique', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11524 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11533 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11532 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11528 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11528 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11531 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11531 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11525 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11578 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11578 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11527 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11526 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11526 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11535 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11527 doesn't seem to be define in the database( WARNING : type of input 3 of step 11526 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11524 doesn't seem to be define in the database( WARNING : type of input 2 of step 11528 doesn't seem to be define in the database( WARNING : output 1 of step 11524 have datatype=2 whereas input 1 of step 11531 have datatype=7 WARNING : type of output 2 of step 11531 doesn't seem to be define in the database( WARNING : type of input 1 of step 11525 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11527 have datatype=10 whereas input 3 of step 11534 have datatype=6 WARNING : type of input 2 of step 11578 doesn't seem to be define in the database( WARNING : output 1 of step 11525 have datatype=7 whereas input 2 of step 11578 have datatype=None WARNING : type of output 3 of step 11578 doesn't seem to be define in the database( WARNING : type of input 1 of step 11527 doesn't seem to be define in the database( WARNING : output 0 of step 11527 have datatype=10 whereas input 0 of step 11584 have datatype=18 WARNING : type of input 5 of step 11534 doesn't seem to be define in the database( WARNING : output 0 of step 11584 have datatype=11 whereas input 5 of step 11534 have datatype=None WARNING : type of output 1 of step 11533 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : type of output 1 of step 11532 doesn't seem to be define in the database( WARNING : type of input 3 of step 11528 doesn't seem to be define in the database( WARNING : output 0 of step 11531 have datatype=1 whereas input 0 of step 11525 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4211, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,metal,papier,pet_fonce,pet_clair,pet_opaque,textiles_sanitaires', 'hashtag_parmi': 'pehd', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 0.3, 'ela': 0.3, 'etiquette': 0.1, 'film_plastique': 0.1, 'kraft': 0.3, 'metal': 1.5, 'papier': 0.3, 'pet_clair': 0.3, 'pet_opaque': 0.3, 'textiles_sanitaires': 0.3, 'pet_fonce': 0.3}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11548 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11556 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11557 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11552 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11552 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11555 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11555 merge_mask_thcl_custom is not consistent : 3 used against 2 in the step definition ! WARNING : number of inputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11549 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11580 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11580 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11551 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11550 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11550 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11559 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11551 doesn't seem to be define in the database( WARNING : type of input 3 of step 11550 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11548 doesn't seem to be define in the database( WARNING : type of input 2 of step 11552 doesn't seem to be define in the database( WARNING : output 1 of step 11548 have datatype=2 whereas input 1 of step 11555 have datatype=7 WARNING : type of output 2 of step 11555 doesn't seem to be define in the database( WARNING : type of input 1 of step 11549 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11551 have datatype=10 whereas input 3 of step 11558 have datatype=6 WARNING : type of input 2 of step 11580 doesn't seem to be define in the database( WARNING : output 1 of step 11549 have datatype=7 whereas input 2 of step 11580 have datatype=None WARNING : type of output 3 of step 11580 doesn't seem to be define in the database( WARNING : type of input 1 of step 11551 doesn't seem to be define in the database( WARNING : output 0 of step 11551 have datatype=10 whereas input 0 of step 11586 have datatype=18 WARNING : type of input 5 of step 11558 doesn't seem to be define in the database( WARNING : output 0 of step 11586 have datatype=11 whereas input 5 of step 11558 have datatype=None WARNING : type of output 1 of step 11556 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : type of output 1 of step 11557 doesn't seem to be define in the database( WARNING : type of input 3 of step 11552 doesn't seem to be define in the database( WARNING : output 0 of step 11555 have datatype=1 whereas input 0 of step 11549 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4200, 'hashtag_proportion': 'carton,ela,etiquette,film_plastique,kraft,metal,papier,pehd,pet_opaque,textiles_sanitaires,barquette_opaque,pet_clair', 'hashtag_parmi': 'pet_fonce', 'hashtag_weights': {'barquette_opaque': 1.5, 'carton': 2.5, 'ela': 1.5, 'etiquette': 1.5, 'film_plastique': 1, 'kraft': 1.5, 'metal': 3.0, 'papier': 1.2, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 11536 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 11545 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 11544 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 11540 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 11540 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! Step 11543 merge_mask_thcl_custom have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11543 merge_mask_thcl_custom have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 11537 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 11579 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 11579 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of outputs for step 11539 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 11538 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 11538 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! Step 11547 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 11539 doesn't seem to be define in the database( WARNING : type of input 3 of step 11538 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 11536 doesn't seem to be define in the database( WARNING : type of input 2 of step 11540 doesn't seem to be define in the database( WARNING : output 1 of step 11536 have datatype=2 whereas input 1 of step 11543 have datatype=7 We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 11539 have datatype=10 whereas input 3 of step 11546 have datatype=6 WARNING : type of input 2 of step 11579 doesn't seem to be define in the database( WARNING : output 1 of step 11537 have datatype=7 whereas input 2 of step 11579 have datatype=None WARNING : type of output 3 of step 11579 doesn't seem to be define in the database( WARNING : type of input 1 of step 11539 doesn't seem to be define in the database( WARNING : output 0 of step 11539 have datatype=10 whereas input 0 of step 11585 have datatype=18 WARNING : type of input 5 of step 11546 doesn't seem to be define in the database( WARNING : output 0 of step 11585 have datatype=11 whereas input 5 of step 11546 have datatype=None WARNING : type of output 1 of step 11545 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : type of output 1 of step 11544 doesn't seem to be define in the database( WARNING : type of input 3 of step 11540 doesn't seem to be define in the database( WARNING : output 0 of step 11543 have datatype=1 whereas input 0 of step 11537 have datatype=2 DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 4205, 'hashtag_proportion': 'barquette_opaque,carton,ela,etiquette,film_plastique,kraft,papier,pehd,pet_clair,pet_opaque,textiles_sanitaires,pet_fonce', 'hashtag_parmi': 'metal', 'hashtag_weights': {'barquette_opaque': 1, 'carton': 1.5, 'ela': 1.5, 'etiquette': 1, 'film_plastique': 1, 'kraft': 1, 'papier': 1, 'pehd': 1.5, 'pet_clair': 1.5, 'pet_opaque': 1.5, 'textiles_sanitaires': 1.5, 'pet_fonce': 1.5}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected error treated as WARNING for now expected given param in final step {'name_pipeline': 'aggregate_carac_ratio', 'hashtag_type': 3594, 'hashtag_proportion': 'papier,carton,metal,pet_clair,autre,pehd,pet_fonce', 'hashtag_parmi': 'refus', 'hashtag_weights': {'papier': 1, 'carton': 1, 'metal': 1, 'pet_clair': 1, 'autre': 1, 'pehd': 1, 'pet_fonce': 1, 'refus': 1}} Found hashtag_parmi in final step, will be used and useful if different from matiere_majoritaire in classifier create_report_from_API() got an unexpected keyword argument 'outfolder' ERROR csv FAILED #&_#_#&_# TEST memo SUCCEEDED #&_#_#&_# #&_#_#&_# TEST one_day SUCCEEDED #&_#_#&_# #&_#_#&_# TEST get_data SUCCEEDED #&_#_#&_# #&_#_#&_# TEST csv FAILED #&_#_#&_# #&_# TEST FAILED #&_# : prod/memo/memo #&_# #&_# END OF TEST #&_# : prod/memo/memo #&_# /home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python/../../tools/../lib/rpn/proposal_layer.py:28: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. layer_params = yaml.load(self.param_str_) /usr/lib/python3/dist-packages/paramiko/transport.py:220: CryptographyDeprecationWarning: Blowfish has been deprecated "class": algorithms.Blowfish, #######all_test_python_finish###### insert result in bdd : Test are not running on charlot, the path should be tested ! /data_2/data_log/job/2025/February/15022025/python_test3/output_tests_python-0537.html new path : /proc/3820514/ /home/admin/workarea/git/Velours/python/dev/generate_new_image.py:720: SyntaxWarning: "is not" with a literal. Did you mean "!="? list_origin_portfolio_ids = [int(item) for item in options.list_origin_portfolio_ids.split(",")] if options.list_origin_portfolio_ids is not "" else [] /home/admin/workarea/git/Velours/python/dev/generate_new_image.py:721: SyntaxWarning: "is not" with a literal. Did you mean "!="? list_photo_ids = [int(item) for item in options.list_photo_ids.split(",")] if options.list_photo_ids is not "" else [] /home/admin/workarea/git/Velours/python/dev/generate_new_image.py:722: SyntaxWarning: "is not" with a literal. Did you mean "!="? rotate_angle_interval = [int(item) for item in options.interval_rotation.split(",")] if options.interval_rotation is not "" else [] /home/admin/workarea/git/Velours/python/dev/generate_new_image.py:723: SyntaxWarning: "is not" with a literal. Did you mean "!="? resize_interval = [float(item) for item in options.interval_resize.split(",")] if options.interval_resize is not "" else None /home/admin/workarea/git/Velours/python/dev/generate_new_image.py:750: SyntaxWarning: "is not" with a literal. Did you mean "!="? mother_crop_portfolio_multi = [float(item) for item in options.mother_crop_portfolio_multi.split(",")] if options.mother_crop_portfolio_multi is not "" else None /home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py:1505: SyntaxWarning: "is not" with a literal. Did you mean "!="? elif new_context_file is not "": /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:1950: SyntaxWarning: "is not" with a literal. Did you mean "!="? rotate_angle_interval_value = [int(item) for item in interval_rotation.split(",")] if interval_rotation is not "" else [] /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:1951: SyntaxWarning: "is not" with a literal. Did you mean "!="? resize_interval_value = [float(item) for item in interval_resize.split(",")] if interval_resize is not "" else None /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:1957: SyntaxWarning: "is not" with a literal. Did you mean "!="? mother_crop_portfolio_multi_value = [float(item) for item in mother_crop_portfolio_multi.split(",")] if mother_crop_portfolio_multi is not "" else None /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:2141: SyntaxWarning: "is not" with a literal. Did you mean "!="? rotate_angle_interval_value = [int(item) for item in interval_rotation.split(",")] if interval_rotation is not "" else [] /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:2142: SyntaxWarning: "is not" with a literal. Did you mean "!="? resize_interval_value = [float(item) for item in interval_resize.split(",")] if interval_resize is not "" else None /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:2148: SyntaxWarning: "is not" with a literal. Did you mean "!="? mother_crop_portfolio_multi_value = [float(item) for item in mother_crop_portfolio_multi.split(",")] if mother_crop_portfolio_multi is not "" else None Name Stmts Miss Cover Missing ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ /home/admin/.local/lib/python3.8/site-packages/Crypto/Hash/SHA256.py 46 29 37% 72-80, 89-93, 104-112, 122, 135-140, 145, 158, 171-185 /home/admin/.local/lib/python3.8/site-packages/Crypto/Hash/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/Crypto/Math/Numbers.py 11 7 36% 36-42 /home/admin/.local/lib/python3.8/site-packages/Crypto/Math/Primality.py 154 141 8% 65-116, 134-213, 244-277, 314-335, 354-369 /home/admin/.local/lib/python3.8/site-packages/Crypto/Math/_IntegerBase.py 226 121 46% 43, 47, 51, 55, 60, 65, 69, 73, 77, 81, 85, 89, 94, 99, 103, 107, 111, 115, 119, 123, 127, 131, 135, 139, 143, 147, 152, 156, 160, 164, 168, 172, 176, 181, 185, 189, 193, 197, 201, 205, 209, 213, 217, 221, 225, 230, 249-295, 322-343, 364-391 /home/admin/.local/lib/python3.8/site-packages/Crypto/Math/_IntegerGMP.py 407 329 19% 98, 104, 110-118, 134-137, 155-191, 196-212, 215, 218, 222, 226, 248-276, 292-308, 312-314, 317-319, 322-324, 327, 330, 333, 336, 339, 343, 347-356, 359-368, 371-380, 383-392, 395-407, 411-446, 449-450, 453-455, 461-473, 476-491, 494-509, 512-528, 531-542, 546-552, 555-561, 564-575, 578-588, 591-597, 600-605, 611-617, 622, 625, 630-632, 636, 639, 644-653, 658-675, 680-684, 693-708, 711-713, 719-728, 734-738, 744-750, 755-762 /home/admin/.local/lib/python3.8/site-packages/Crypto/Math/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/Crypto/PublicKey/RSA.py 325 267 18% 96-105, 109, 113, 117-119, 123-125, 129-131, 135-137, 141, 145, 148-150, 153-174, 179, 182, 185, 193, 196-202, 205, 209-210, 213-218, 221-225, 304-368, 376, 379, 382, 385, 388, 391, 394, 426-475, 518-618, 635-638, 646-647, 652-655, 660-661, 665-670, 676-688, 693-712, 756-791 /home/admin/.local/lib/python3.8/site-packages/Crypto/PublicKey/__init__.py 33 29 12% 46-60, 65-73, 79-94 /home/admin/.local/lib/python3.8/site-packages/Crypto/Random/__init__.py 16 6 62% 31, 35, 39, 43, 48, 52 /home/admin/.local/lib/python3.8/site-packages/Crypto/Signature/PKCS1_v1_5.py 14 9 36% 42-46, 49-52 /home/admin/.local/lib/python3.8/site-packages/Crypto/Signature/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/Crypto/Signature/pkcs1_15.py 49 39 20% 49, 53, 73-84, 106-138, 191-207, 221 /home/admin/.local/lib/python3.8/site-packages/Crypto/Util/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/Crypto/Util/_file_system.py 8 1 88% 46 /home/admin/.local/lib/python3.8/site-packages/Crypto/Util/_raw_api.py 164 105 36% 42-46, 61, 66, 77, 99, 113, 118-126, 130, 134, 137-143, 149, 152, 155, 158, 162-261, 268-269, 272, 275-276, 279-284, 304-305, 307-309, 314, 318 /home/admin/.local/lib/python3.8/site-packages/Crypto/Util/asn1.py 316 251 21% 34-39, 47-49, 52, 55-56, 59, 62-68, 71, 107-141, 147-153, 160-163, 171-180, 187-197, 210-220, 225-246, 289-291, 297-306, 319, 325-341, 400-404, 409, 412, 415, 418, 421, 424, 427, 430-431, 434-435, 446-447, 460, 470-478, 501-507, 512-543, 589, 598, 643-644, 650-664, 680, 686-698, 743-749, 756-757, 772, 778-787, 827-836, 839, 842, 845, 856-869, 887, 892-919, 928-939 /home/admin/.local/lib/python3.8/site-packages/Crypto/Util/number.py 223 199 11% 40-47, 53-59, 72-81, 93-98, 111-114, 120-123, 128-136, 147-157, 173-206, 246-339, 359-374, 407-447, 464-483, 489-490, 492-493 /home/admin/.local/lib/python3.8/site-packages/Crypto/Util/py3compat.py 82 59 28% 66-110, 114, 116, 118-121, 123, 125-134, 136, 138, 147, 150, 153, 166-171 /home/admin/.local/lib/python3.8/site-packages/Crypto/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/PIL/BmpImagePlugin.py 218 179 18% 76-264, 276-284, 291-355, 366, 384, 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/home/admin/.local/lib/python3.8/site-packages/PIL/_version.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/apiclient/__init__.py 10 2 80% 7-10 /home/admin/.local/lib/python3.8/site-packages/av/__init__.py 21 1 95% 12 /home/admin/.local/lib/python3.8/site-packages/av/about.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/av/audio/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/av/codec/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/av/container/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/av/deprecation.py 36 17 53% 33-34, 37-42, 45-55, 58-68, 77-81 /home/admin/.local/lib/python3.8/site-packages/av/filter/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/av/sidedata/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/av/video/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/boto3/__init__.py 31 17 45% 35, 61-70, 80-84, 93, 102, 109 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1866-1882, 1885, 1895, 1911-1915, 1931-1932, 1941-1947, 1959, 1962-1965, 1973-1985, 1994-2000, 2009-2021, 2025-2027, 2031-2057, 2075-2083, 2086-2111, 2114-2128 /home/admin/.local/lib/python3.8/site-packages/botocore/discovery.py 183 139 24% 40-42, 47, 51-52, 56-60, 63-67, 70-75, 78, 83-90, 95-107, 110-115, 118-121, 124-125, 128, 131-133, 138-142, 145-148, 151-160, 163-168, 171, 174-214, 219, 222-228, 231-236, 239-251, 254-274 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/__init__.py 11 8 27% 28-38 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/bcdoc/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/botocore/docs/bcdoc/docstringparser.py 119 83 30% 24-26, 29-30, 34-36, 39-42, 45, 48, 51, 61-64, 67-79, 82-87, 90, 93, 98, 101, 106-107, 110-111, 114, 117-118, 126-128, 131-133, 136-138, 141-143, 148, 151-152, 160-170, 178-181, 184, 187-200 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/bcdoc/restdoc.py 112 74 34% 25-33, 36-37, 43, 49, 56, 62, 68, 74-78, 81, 84-85, 88-97, 101-103, 120-128, 133, 141, 145, 149, 153, 156-157, 175-183, 187, 191, 201-209, 212, 215, 218 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/bcdoc/style.py 288 206 28% 22-25, 29, 33, 36, 39, 42-43, 46, 49, 52, 55, 58, 61, 64, 70-73, 76, 79, 82, 91-101, 104, 107, 110-111, 114-115, 118-121, 124-126, 129-132, 135, 138, 141, 144, 147, 150-153, 156-157, 160-161, 164-165, 168-169, 172-175, 178-181, 184-185, 188-191, 194-195, 198-201, 204-205, 208-219, 222, 225-230, 233-254, 257-258, 261-262, 265-267, 270-271, 274-277, 280-283, 286-289, 293-296, 299-302, 305, 308, 311, 314, 317-319, 322-323, 332-334, 337-342, 345-351, 354-357, 360-361, 364-368, 371-374, 377-378, 381-387, 390-391, 394-397, 400-401, 404-406, 409-412, 415-418 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/client.py 170 130 24% 28-32, 39-43, 46, 49-67, 71, 75-81, 84-86, 90-94, 97, 100, 103-110, 113-132, 167-168, 171-174, 177, 180-192, 195-196, 199-210, 213-214, 217-223, 226-229, 232-246, 249-254, 257-264, 267-276, 281-290 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/docstring.py 38 19 50% 33-36, 40, 43, 58-60, 63, 70-72, 75-81, 86, 91, 96 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/example.py 127 107 16% 36-41, 46, 50-56, 60-66, 70-81, 85-110, 114-125, 128-132, 135-139, 142-146, 152-158, 166-169, 177-208 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/method.py 97 86 11% 33-39, 60-78, 99-105, 117-123, 169-281 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/paginator.py 49 39 20% 22-24, 31-43, 46-65, 94-167 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/params.py 132 108 18% 33-34, 39, 43, 47-56, 60-77, 82-95, 98, 101-105, 108-117, 120-121, 124-125, 134-145, 149, 159-177, 182-212, 215-216, 219-220 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/service.py 53 36 32% 24-32, 46-55, 58-59, 66, 69-75, 78, 81-88, 91-96, 99-102 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/shape.py 39 31 21% 27-32, 61-89, 92-98, 101-107, 110-117 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/sharedexample.py 143 123 14% 33-38, 41-55, 58-72, 88-97, 101-125, 128-147, 150-164, 169-170, 173, 176-180, 183-187, 190-192, 195-198, 213-218 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/utils.py 75 33 56% 27, 50, 69-77, 117-128, 160-166, 176-180, 197 /home/admin/.local/lib/python3.8/site-packages/botocore/docs/waiter.py 35 25 29% 22-24, 31-38, 41-56, 83-119 /home/admin/.local/lib/python3.8/site-packages/botocore/endpoint.py 153 117 24% 54-70, 85-94, 97, 100-102, 105-118, 122-124, 127-128, 131-158, 166-183, 186-230, 236-245, 249-266, 269, 274, 285-303, 314, 323-327 /home/admin/.local/lib/python3.8/site-packages/botocore/errorfactory.py 32 21 34% 28, 44, 47-51, 58, 70-74, 77-88 /home/admin/.local/lib/python3.8/site-packages/botocore/eventstream.py 246 149 39% 33-34, 40-43, 49-52, 58-61, 71-72, 110, 123, 135-136, 148-149, 161-162, 175-176, 189-190, 203-204, 225-229, 251-253, 265, 279, 285-287, 293-295, 306, 318, 328, 334-337, 340-343, 384, 396-397, 400-406, 409-411, 414-416, 419-421, 424-428, 431, 442-444, 452, 455-459, 462-468, 471-472, 475-477, 480-483, 487-488, 491-494, 497-502, 506-507, 515-524, 527, 530, 577-581, 584-587, 590-594, 597-602, 605-612, 616 /home/admin/.local/lib/python3.8/site-packages/botocore/exceptions.py 200 32 84% 24-28, 40-42, 45, 82-84, 87, 369-370, 410-420, 423-430, 436, 620-622 /home/admin/.local/lib/python3.8/site-packages/botocore/handlers.py 434 313 28% 80, 90-106, 125-134, 138-152, 163-185, 189-198, 202-205, 210-214, 218-224, 228-236, 246, 256, 260-272, 276, 285, 289-297, 305-312, 316-330, 365-374, 378-392, 396-401, 414-420, 427-429, 434-443, 450-465, 475-477, 483-496, 505-514, 518-522, 544-562, 573-584, 588-593, 597-598, 603-605, 620-637, 658-668, 672, 676-690, 696-699, 703-707, 719, 732, 745, 763-773, 777-781, 822-835, 838-855, 858-862, 875, 885, 894-900, 903-905, 911-923, 927-929, 934-935 /home/admin/.local/lib/python3.8/site-packages/botocore/history.py 27 10 63% 22, 31, 34, 37, 40-47 /home/admin/.local/lib/python3.8/site-packages/botocore/hooks.py 249 196 21% 31-35, 60-63, 82, 99, 112, 124, 130-132, 143, 146-147, 158-163, 171-175, 195-215, 228, 243-247, 251, 256, 261, 266-302, 306-336, 339-344, 349-352, 355-356, 359-360, 364-365, 371-372, 378-379, 385-386, 391-420, 423-427, 430, 464, 472-483, 493-497, 500-528, 538-540, 543-564, 572-575, 581-589 /home/admin/.local/lib/python3.8/site-packages/botocore/httpsession.py 210 158 25% 39-41, 45-51, 61-88, 99-105, 109-113, 117-122, 126, 129-134, 137-139, 142-146, 169-195, 199-206, 209-219, 222, 225-234, 237-243, 246-251, 254-274, 277-281, 284-301, 304, 307-359 /home/admin/.local/lib/python3.8/site-packages/botocore/loaders.py 139 98 29% 127-134, 154, 166-175, 192-199, 222-238, 242, 246, 267-287, 310, 327-340, 374-389, 393-400, 419-424, 430-441, 455-456, 460-461 /home/admin/.local/lib/python3.8/site-packages/botocore/model.py 398 242 39% 42, 81-93, 118-126, 145-150, 161, 164, 167, 172, 178-188, 192-195, 199-206, 212, 218, 222, 228, 259-266, 269, 273, 277-281, 284, 288, 292-297, 301-305, 309, 313, 327-330, 334-337, 348-351, 355, 359, 363, 367-370, 374-379, 382-385, 394-397, 401, 404, 437-444, 448-451, 465, 469, 473, 477, 483, 487, 491-495, 500-505, 510-514, 520, 524-525, 529, 533, 537, 541, 544, 547, 551-556, 560, 564, 567, 570, 574-581, 584, 599-600, 603-616, 624-636, 643, 647, 688-691, 702-703, 712-719, 724-734, 737-745, 748-752, 755-762, 765-773, 776, 779-782, 793, 821-823 /home/admin/.local/lib/python3.8/site-packages/botocore/monitoring.py 221 149 33% 42-43, 47-48, 56-61, 73, 89, 92, 97, 104-110, 114-124, 127-129, 136-138, 141, 145-147, 150, 153, 171-173, 176, 179-181, 214-220, 229-235, 287-296, 342-343, 346-347, 362-370, 374, 380, 383, 386, 389-391, 394-408, 412-415, 419, 422, 426-433, 438, 442-444, 448-451, 456-460, 464-467, 470-472, 475-481, 484, 490, 493, 496-500, 503-508, 531-533, 542-550 /home/admin/.local/lib/python3.8/site-packages/botocore/paginate.py 369 304 18% 52-68, 72-79, 83-90, 94-101, 105, 127-136, 140-144, 158-161, 172-173, 178, 181-186, 193-207, 211, 216, 220-232, 236, 239-303, 321-329, 332, 335, 338-344, 349-357, 360-364, 370-397, 401-424, 427-440, 443-444, 448-490, 493-506, 513-534, 541-550, 557-566, 570, 573-576, 579-585, 588-591, 594-596, 599-604, 607, 617-618, 629-646, 668-669, 672-677 /home/admin/.local/lib/python3.8/site-packages/botocore/parsers.py 528 407 23% 135, 147, 150-151, 155, 165-174, 199-207, 214, 233-262, 265, 279-284, 289-291, 299, 302, 306, 310-312, 317-321, 324, 327-329, 334-336, 339-357, 360, 368-370, 373-399, 402-406, 413-421, 427-444, 447-458, 461-467, 471-474, 478, 482, 486, 490, 494, 504-517, 520, 523, 526-538, 541-542, 545-551, 557-560, 575-580, 583-588, 594-609, 612-619, 622, 625, 628-652, 655-656, 660-669, 675-685, 688-706, 709-726, 730-740, 747, 753, 759-761, 770-778, 781, 784-793, 799-800, 806-810, 813-818, 821-823, 826-836, 839-860, 864-879, 885-893, 900, 903-907, 915, 918-920, 925-933, 942-944, 960-970, 973, 986-1006, 1010-1011 /home/admin/.local/lib/python3.8/site-packages/botocore/regions.py 90 69 23% 58, 65, 85, 94-96, 99-102, 106-116, 119-136, 141-165, 169-173, 176-190, 193-195, 199 /home/admin/.local/lib/python3.8/site-packages/botocore/response.py 67 45 33% 44-46, 60-69, 76-87, 92, 97-100, 110-117, 124-127, 133-135, 141, 145-162 /home/admin/.local/lib/python3.8/site-packages/botocore/retries/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/botocore/retries/adaptive.py 70 50 29% 14-35, 44-50, 53-54, 58-77, 90-96, 99-113, 117 /home/admin/.local/lib/python3.8/site-packages/botocore/retries/base.py 6 2 67% 9, 27 /home/admin/.local/lib/python3.8/site-packages/botocore/retries/bucket.py 70 48 31% 10, 13, 16, 24-32, 36, 40-56, 60, 64, 76-77, 80-100, 103, 106-114 /home/admin/.local/lib/python3.8/site-packages/botocore/retries/quota.py 24 16 33% 12-16, 28-32, 46-53, 57 /home/admin/.local/lib/python3.8/site-packages/botocore/retries/special.py 28 17 39% 23-27, 36-48 /home/admin/.local/lib/python3.8/site-packages/botocore/retries/standard.py 200 132 34% 40-61, 71-73, 77-93, 108-129, 136-138, 172-189, 199-204, 215, 218, 223-224, 227, 230, 239-241, 257, 265, 268-272, 290-298, 301-310, 334-336, 341, 348, 351-354, 376-391, 396-398, 402-406, 421-422, 433, 439, 442, 458-460, 463-475, 478, 490-498 /home/admin/.local/lib/python3.8/site-packages/botocore/retries/throttling.py 25 15 40% 13-17, 20-21, 24-28, 35-38, 50 /home/admin/.local/lib/python3.8/site-packages/botocore/retryhandler.py 158 118 25% 52-58, 68, 73-77, 85-87, 93-118, 124-128, 132-144, 148-155, 173-174, 183-187, 219-225, 228, 231, 245-247, 250-263, 266-277, 282, 285-291, 296-297, 300-307, 312, 315-320, 326, 329-340, 359 /home/admin/.local/lib/python3.8/site-packages/botocore/serialize.py 357 275 23% 65-69, 117, 122-130, 135-139, 142, 145-147, 150-157, 162, 168-170, 174-186, 190-192, 200-222, 232-234, 237-243, 246-262, 265-278, 282, 285, 289-292, 295, 298, 314-322, 325-328, 335-357, 360-362, 365-379, 382-385, 388-397, 400, 403, 407, 428-476, 485-493, 502-519, 523-525, 533-569, 572-574, 577, 580-591, 597-599, 606-610, 613-615, 618-641, 644-652, 663-671, 677-682, 685-686, 689-690, 694-695 /home/admin/.local/lib/python3.8/site-packages/botocore/session.py 384 276 28% 102-131, 134-141, 144, 147, 151, 156, 161-165, 169, 173, 177-186, 189-192, 196, 200-215, 218-226, 230, 236-238, 242-245, 248-251, 261-282, 308-313, 316, 340-353, 365-388, 398, 408, 427, 440-443, 468-480, 489, 505-506, 509-512, 515-518, 524-534, 540, 548, 573-588, 602-616, 652, 685, 690, 693-694, 697-707, 713, 719, 722, 725, 800-855, 860-877, 880-884, 892-893, 915-925, 931-932, 935-945, 948-952, 955-959, 964-965, 968, 971-972, 975, 978, 981, 992-995, 1017-1018, 1032-1038, 1051 /home/admin/.local/lib/python3.8/site-packages/botocore/signers.py 216 174 19% 64-71, 75, 79, 83, 90, 120-162, 174-199, 221-242, 271-276, 315-316, 333-351, 354-355, 385-396, 401, 406, 427-457, 462, 506-533, 537, 561-598, 604, 671-719, 725-734 /home/admin/.local/lib/python3.8/site-packages/botocore/translate.py 21 16 24% 21-38, 42-55, 70-76 /home/admin/.local/lib/python3.8/site-packages/botocore/utils.py 1126 888 21% 181-184, 196, 207-214, 218-220, 226-229, 236-256, 262-267, 276-300, 310, 322-331, 337, 340-364, 367-395, 413-432, 435-436, 439-441, 444, 450-453, 456-459, 462-472, 482-513, 516, 523-528, 531-536, 539, 545, 552-558, 569-587, 592-595, 599-604, 611-619, 642-655, 671-676, 681-695, 710-716, 747-762, 775-783, 804-810, 827-843, 855-860, 875-880, 910, 922-923, 926-949, 952-958, 963-966, 971-974, 980-981, 993-1004, 1007, 1011-1016, 1030-1039, 1053-1060, 1077-1124, 1128, 1150-1159, 1170-1179, 1184-1187, 1191-1193, 1197-1212, 1222-1230, 1238, 1243-1250, 1253-1256, 1266-1343, 1358-1376, 1379-1381, 1388-1395, 1398, 1407-1413, 1435-1437, 1440, 1443-1451, 1454-1462, 1465-1470, 1480-1481, 1490-1499, 1515-1523, 1526-1527, 1533-1553, 1556-1567, 1570, 1573-1600, 1608-1615, 1618-1619, 1622-1633, 1636-1662, 1669-1671, 1674-1679, 1682-1688, 1691-1697, 1705-1732, 1738-1744, 1750-1766, 1777-1785, 1788, 1791-1802, 1805, 1808, 1811-1835, 1838-1839, 1847-1853, 1856-1858, 1861-1862, 1865-1876, 1879-1883, 1886, 1889-1891, 1894-1906, 1909-1918, 1921, 1924-1925, 1928-1933, 1936-1942, 1945-1951, 1954-1957, 1960, 1967-1969, 1972, 1978-1985, 1988-1997, 2000, 2003-2013, 2016-2018, 2022-2031, 2037-2043, 2046-2051, 2054-2063, 2069-2075, 2078-2083, 2095-2100, 2111-2112, 2115-2119, 2125-2127, 2138-2139, 2142-2156, 2159-2180, 2183, 2187-2190, 2205-2211, 2221-2232, 2236-2240, 2244-2245, 2249-2254, 2259-2263, 2268-2269, 2272-2273, 2278-2280, 2283, 2286-2296 /home/admin/.local/lib/python3.8/site-packages/botocore/validate.py 164 114 30% 46-49, 55-56, 59-64, 71-84, 89, 92-94, 97-100, 103-128, 132-137, 140, 160-162, 165-166, 169-173, 179-182, 187-202, 215, 219-222, 226-231, 235, 238-244, 250, 254, 260, 266-269, 273-279, 284-285, 288-294 /home/admin/.local/lib/python3.8/site-packages/botocore/vendored/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/botocore/vendored/requests/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/botocore/vendored/requests/exceptions.py 26 6 77% 21-27 /home/admin/.local/lib/python3.8/site-packages/botocore/vendored/requests/packages/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/botocore/vendored/requests/packages/urllib3/__init__.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/botocore/vendored/requests/packages/urllib3/exceptions.py 67 15 78% 17-18, 22, 28-29, 33, 73-78, 85-87, 135-138 /home/admin/.local/lib/python3.8/site-packages/botocore/vendored/six.py 444 211 52% 49-72, 98-99, 112, 118-121, 131-133, 145, 154-157, 192-193, 203, 222-223, 304, 480, 488, 493-499, 511-517, 522-524, 530-532, 537, 542, 546-560, 575, 578, 581, 584, 592-608, 620, 623, 636-637, 642-661, 667, 671, 675, 682-701, 707, 717-718, 723-775, 777-784, 789-795, 805-809, 814-825, 836-843, 864-865 /home/admin/.local/lib/python3.8/site-packages/botocore/waiter.py 175 140 20% 44-73, 79-82, 87, 90-93, 113-121, 124-125, 132-136, 147-154, 158-162, 167-171, 175-186, 197-208, 212-219, 222-239, 242-259, 262-271, 274-284, 303-307, 310-367 /home/admin/.local/lib/python3.8/site-packages/cached_property.py 93 61 34% 14-15, 30-37, 40-47, 57-59, 62-74, 85-91, 94-95, 98-115, 118, 121, 124-128, 143-144, 147-148 /home/admin/.local/lib/python3.8/site-packages/cffi/__init__.py 7 0 100% /home/admin/.local/lib/python3.8/site-packages/cffi/api.py 544 341 37% 8-11, 52-59, 82, 97-98, 115-117, 121-123, 129-130, 133-135, 147, 160, 166, 169, 174, 190, 200, 203-211, 217-221, 227-229, 238-240, 284-291, 299, 318, 335, 361-365, 382, 392-403, 411-419, 431, 454-473, 476, 478, 483, 486-487, 495-508, 511-515, 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/home/admin/.local/lib/python3.8/site-packages/cffi/error.py 19 8 58% 8-15 /home/admin/.local/lib/python3.8/site-packages/cffi/lock.py 10 6 40% 4-7, 11-12 /home/admin/.local/lib/python3.8/site-packages/cffi/model.py 389 160 59% 16, 21, 30-45, 51, 54, 66, 79, 99, 166, 168, 170, 172, 182-183, 186, 189, 196-197, 200, 215, 219, 232, 249-253, 258, 269, 288-290, 304, 314, 318, 359-362, 365-376, 382-394, 400, 405-408, 414, 422-425, 430-462, 467, 471, 495-499, 502-505, 508-509, 512-514, 520-557, 562, 569-572, 584-587, 598-599, 610, 613, 616-617 /home/admin/.local/lib/python3.8/site-packages/charset_normalizer/__init__.py 9 0 100% /home/admin/.local/lib/python3.8/site-packages/charset_normalizer/api.py 195 181 7% 62-497, 515, 543-544 /home/admin/.local/lib/python3.8/site-packages/charset_normalizer/assets/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/charset_normalizer/cd.py 189 164 13% 24-50, 63-71, 80-91, 100-112, 120-129, 138-164, 175-244, 253-283, 291-311, 319-338, 350-388 /home/admin/.local/lib/python3.8/site-packages/charset_normalizer/constant.py 21 0 100% /home/admin/.local/lib/python3.8/site-packages/charset_normalizer/legacy.py 19 14 26% 22-50 /home/admin/.local/lib/python3.8/site-packages/charset_normalizer/models.py 174 110 37% 20-34, 37-43, 49-62, 66, 70-72, 75, 78-86, 90, 97-103, 107, 111, 119, 127-147, 151, 155-157, 161, 165, 172, 176, 180, 184-192, 201, 208-212, 219, 229, 232, 239-246, 249, 252, 259-272, 278-280, 286, 308-318, 322, 337 /home/admin/.local/lib/python3.8/site-packages/charset_normalizer/utils.py 214 158 26% 24-28, 40-46, 54-60, 65-69, 74-78, 83-93, 98-108, 113-118, 123-128, 133, 137-139, 144-149, 154-159, 164-169, 174-179, 184-189, 194, 199, 212-237, 245, 266-276, 280, 284-296, 300-310, 314-334, 342, 353-358, 372-414 /home/admin/.local/lib/python3.8/site-packages/charset_normalizer/version.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/colorama/__init__.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/colorama/ansi.py 74 8 89% 16, 19, 22, 38, 40, 42, 44, 46 /home/admin/.local/lib/python3.8/site-packages/colorama/ansitowin32.py 131 100 24% 13, 25-26, 29, 35, 38, 41, 44-53, 57-61, 75-104, 114, 117-158, 161-167, 171-174, 183-190, 194-196, 200-202, 206-220, 224-242, 246-257 /home/admin/.local/lib/python3.8/site-packages/colorama/initialise.py 48 32 33% 19-20, 25-48, 52-55, 60-64, 68-71, 75-80 /home/admin/.local/lib/python3.8/site-packages/colorama/win32.py 78 68 13% 11, 17-152 /home/admin/.local/lib/python3.8/site-packages/colorama/winterm.py 119 90 24% 25-34, 37, 40-42, 45-47, 50-58, 61-69, 72-75, 78-83, 86-91, 94-101, 104-109, 115-141, 147-166, 169 /home/admin/.local/lib/python3.8/site-packages/cryptography/__about__.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/cryptography/__init__.py 7 1 86% 18 /home/admin/.local/lib/python3.8/site-packages/cryptography/exceptions.py 37 5 86% 11, 33-34, 61-62 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/_oid.py 122 0 100% /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/__init__.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/aead.py 143 127 11% 10-19, 28-46, 50-62, 70-85, 97-137, 141-145, 149-158, 162-166, 170-175, 179-187, 199-245, 257-310 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/backend.py 1215 945 22% 189, 200, 219, 229-231, 234-244, 250-264, 269-276, 279-285, 294, 299, 304, 308, 323-327, 334-336, 339-342, 346-349, 357-368, 372, 458, 468-482, 506-514, 519-535, 542, 553-582, 592-602, 605-608, 611-614, 633-638, 644-649, 671-721, 729-780, 783-786, 798-814, 817-820, 823-844, 849-857, 862-863, 868-871, 876-892, 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/home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/cmac.py 46 35 24% 16-17, 27-59, 62-63, 66-73, 76-82, 85-87 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/dh.py 173 143 17% 12, 16-30, 34-35, 40-41, 44-55, 62, 69-104, 108-111, 116-119, 123, 126-141, 154-187, 190-192, 198-212, 215, 223-241, 253-256, 260, 263-278, 288, 295-315 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/dsa.py 119 87 27% 17, 23-35, 46-52, 57-58, 61-68, 75, 82-91, 95, 98-110, 123-139, 142-147, 155, 169-170, 177-185, 189, 192-204, 214-218, 225, 235-236 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/ec.py 145 111 23% 20, 26-27, 34-60, 70, 76-81, 87-90, 99-108, 117-122, 127-134, 138, 142, 147-162, 165-179, 182-184, 195, 209-214, 219-226, 230, 234, 237-255, 258-279, 286-302, 312-317 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/ed25519.py 70 54 23% 17, 22-23, 30-44, 49-56, 59-77, 82-83, 86-94, 97-117, 125-143, 148-155 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/ed448.py 72 54 25% 15, 23-24, 31-45, 50-57, 60-78, 83-84, 87-95, 98-118, 126-144, 149-156 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/hashes.py 45 12 73% 11, 29, 47-53, 65, 79-86 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/hmac.py 46 34 26% 15, 26-48, 52, 55-62, 67-69, 72-79, 82-84 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/poly1305.py 34 23 32% 15, 20-47, 50-54, 57-62, 65-67 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/rsa.py 257 136 47% 37, 46-59, 68-95, 107-162, 172, 180-201, 226-227, 233-234, 242-243, 250-261, 288-289, 306-322, 332-358, 383-384, 395-396, 436, 439-444, 447-451, 494, 520-532, 536, 539, 542-549, 559, 570-571, 581-586 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/utils.py 34 22 35% 11, 15-41, 53, 56 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/backends/openssl/x448.py 53 37 30% 15, 22-23, 30-44, 49-56, 61-62, 65-73, 76-79, 87-105, 110-117 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/bindings/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/bindings/openssl/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/bindings/openssl/_conditional.py 74 34 54% 9, 25, 32, 38, 46, 52, 58, 65, 72, 79, 92, 98, 106, 118, 126, 132, 146, 155, 175, 181, 189, 199, 205, 211, 218, 227, 239, 247, 253, 257, 261, 265, 271, 275 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/bindings/openssl/binding.py 84 16 81% 25-28, 42, 88-99, 110-111, 161, 185, 200 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/_asymmetric.py 5 0 100% /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/_cipheralgorithm.py 17 0 100% /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/_serialization.py 79 35 56% 37-42, 64-67, 83-87, 90-99, 109-116, 126-133, 141-144, 163-168 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/asymmetric/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/asymmetric/dh.py 112 47 58% 17-19, 24-39, 42-45, 50-54, 58, 62, 66, 71-80, 83-86, 92-96, 100, 104, 109-118, 121-124, 130-134, 138, 142 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/asymmetric/dsa.py 127 57 55% 128-139, 143, 147, 151, 154-158, 161-164, 167, 175-184, 188, 192, 195-199, 202-205, 211, 219-227, 231, 235, 238-242, 245-248, 256-258, 264-266, 270-278, 282-288 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/asymmetric/ec.py 216 56 74% 171-184, 315, 321, 327-329, 337-348, 353-361, 364-368, 372, 376, 380, 383-386, 394, 397, 407-417, 422-426, 430, 434, 437-440, 446, 477-480 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/asymmetric/ed25519.py 39 14 64% 18-26, 43, 57-65, 69-77, 101 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/asymmetric/ed448.py 37 14 62% 15-23, 40, 54-61, 65-73, 103 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/asymmetric/padding.py 46 20 57% 44-57, 69-74, 85-88, 95-101 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/asymmetric/rsa.py 181 91 50% 129-132, 136-143, 156-190, 194-201, 208-214, 221, 229, 237, 254-288, 310, 316, 331, 335, 339, 343, 347, 351, 363-367, 372-375, 386, 402, 416-420, 423, 426-429, 432 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/home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/serialization/base.py 21 10 52% 22-24, 32-34, 40-42, 62-64, 70-72 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/serialization/pkcs12.py 81 49 40% 44-49, 53, 57, 60-63, 69, 72, 84-110, 114, 118, 122, 125-128, 135, 138-141, 153-155, 163-165, 181-225 /home/admin/.local/lib/python3.8/site-packages/cryptography/hazmat/primitives/serialization/ssh.py 723 580 20% 39-49, 105-120, 125-130, 138, 143-144, 149-150, 160-165, 170-172, 177-179, 184-187, 192-195, 200-205, 216-218, 222, 226, 230, 234-239, 243, 247, 251-255, 259-261, 275-277, 283-286, 292-308, 314-316, 322-331, 347-351, 357-362, 368-378, 384-391, 397-398, 401-403, 426-432, 438-442, 448-454, 460-464, 470-474, 491-492, 498-502, 508-516, 522-525, 531-541, 556-560, 577-653, 662-730, 773-792, 796, 801, 805, 809, 813, 817, 821, 825, 829, 833, 836-839, 842, 849-873, 882-888, 895-983, 989, 993-1005, 1011-1025, 1030-1045, 1074-1083, 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/home/admin/.local/lib/python3.8/site-packages/cryptography/x509/extensions.py 989 542 45% 52-70, 75, 78, 81, 88-89, 94-95, 105, 116, 121-125, 130-141, 148, 155-158, 161-164, 167, 170, 174, 177, 189-214, 225-226, 236, 243, 251-254, 262-266, 272, 278, 282, 285, 292, 298, 302, 306, 309, 312-315, 318, 321, 330-337, 342, 345-348, 351, 354, 363-370, 375, 378-381, 384, 387, 394-401, 404, 410-413, 419, 423, 427, 434-448, 452, 456, 459, 464-467, 470, 473, 480-483, 487, 490-493, 496, 499, 502, 511-520, 527, 530-533, 536, 539, 548-557, 564, 567-570, 573, 576, 587-636, 639, 646-649, 657-671, 675, 679, 683, 687, 746-768, 771, 778-781, 787, 793, 797, 800, 807-814, 819, 822-825, 828, 831, 842-857, 860, 866-869, 875-882, 886, 892, 901-909, 912, 918-921, 927, 931, 935, 944-949, 952, 958-961, 967, 971, 975, 982-988, 993, 996-999, 1002, 1005, 1012-1015, 1018, 1021, 1024, 1031-1034, 1037, 1040, 1043, 1050-1060, 1065, 1068-1071, 1074, 1077, 1098-1104, 1107, 1110-1113, 1116, 1120, 1123, 1141-1155, 1159, 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82-94, 98, 102-104, 107, 110-113, 116, 121-133, 137, 143-145, 148, 151-154, 157, 162-165, 169, 172, 175-178, 181, 186-189, 193, 196, 199-202, 205, 210-225, 229, 232-237, 242, 245-248, 251, 256-262, 266, 270, 273, 278-281, 284 /home/admin/.local/lib/python3.8/site-packages/cryptography/x509/name.py 232 142 39% 64-87, 91-106, 118-164, 168, 172, 180, 191-197, 200-203, 206, 209, 214-225, 230, 241, 247-250, 253, 256, 259, 262, 268, 274, 282-293, 304, 319, 327, 331, 334, 337-340, 345, 348-350, 353, 356-357, 388-391, 394, 397-399, 402-404, 407-412, 423-429, 432-437, 440-460 /home/admin/.local/lib/python3.8/site-packages/cryptography/x509/oid.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/cv2/__init__.py 16 2 88% 18-19 /home/admin/.local/lib/python3.8/site-packages/cv2/data/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/cv2/version.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/dateutil/__init__.py 13 4 69% 6-7, 17, 24 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76, 91-143 /home/admin/.local/lib/python3.8/site-packages/fontTools/colorLib/table_builder.py 118 99 16% 49, 53, 57-72, 84-86, 89-119, 122-181, 186-188, 191-223 /home/admin/.local/lib/python3.8/site-packages/fontTools/colorLib/unbuilder.py 41 32 22% 6-10, 17-21, 26-34, 37-38, 41-58, 62-81 /home/admin/.local/lib/python3.8/site-packages/fontTools/config/__init__.py 8 0 100% /home/admin/.local/lib/python3.8/site-packages/fontTools/designspaceLib/__init__.py 1422 1195 16% 49-56, 64, 68-70, 77-78, 81, 86-95, 105-109, 118-120, 185-296, 311, 315, 322, 329, 339-345, 379-390, 402, 411-421, 431-446, 525-650, 661, 665, 669, 672, 675, 678, 681, 684, 687, 690, 720-732, 744-752, 774-785, 794, 799-812, 830-869, 925-945, 953, 968-972, 976-982, 1031-1052, 1064, 1074-1076, 1116-1137, 1152-1156, 1161, 1187-1208, 1215, 1223, 1249-1271, 1286-1299, 1315-1320, 1338, 1342, 1346, 1350, 1353-1356, 1359-1409, 1421-1439, 1443-1460, 1463-1465, 1469-1497, 1500-1527, 1532-1548, 1551-1555, 1560-1568, 1577-1596, 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7 4 43% 69-72 /home/admin/.local/lib/python3.8/site-packages/fontTools/misc/etree.py 263 257 2% 47-478 /home/admin/.local/lib/python3.8/site-packages/fontTools/misc/filenames.py 76 64 16% 99-134, 168-191, 221-239, 243-246 /home/admin/.local/lib/python3.8/site-packages/fontTools/misc/fixedTools.py 35 20 43% 81, 109-110, 137-138, 157-158, 188-190, 212-213, 231-239, 251-253 /home/admin/.local/lib/python3.8/site-packages/fontTools/misc/intTools.py 9 2 78% 9, 25 /home/admin/.local/lib/python3.8/site-packages/fontTools/misc/loggingTools.py 240 173 28% 57-76, 79-86, 134-185, 192-226, 294-296, 306, 312, 316-319, 327-336, 340-342, 348-357, 370, 374-375, 384, 387, 390, 421-423, 426-434, 439-444, 447-456, 459-464, 467, 470-478, 511-514, 519, 528-533, 541-543 /home/admin/.local/lib/python3.8/site-packages/fontTools/misc/plistlib/__init__.py 259 182 30% 66-78, 82, 103-105, 109, 112, 117-122, 125, 131-142, 188-201, 204-207, 210-212, 215, 218-220, 225-238, 241-243, 250-252, 256-258, 262-264, 268-270, 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/home/admin/.local/lib/python3.8/site-packages/google/auth/crypt/base.py 32 10 69% 44, 53, 67, 87, 104-109, 124-127 /home/admin/.local/lib/python3.8/site-packages/google/auth/crypt/es256.py 67 34 49% 48, 53-73, 90-101, 117-118, 123, 127-132, 156-160, 164-170, 174-175 /home/admin/.local/lib/python3.8/site-packages/google/auth/crypt/rsa.py 5 0 100% /home/admin/.local/lib/python3.8/site-packages/google/auth/environment_vars.py 16 0 100% /home/admin/.local/lib/python3.8/site-packages/google/auth/exceptions.py 31 6 81% 22-24, 28, 58, 70 /home/admin/.local/lib/python3.8/site-packages/google/auth/iam.py 42 21 50% 84-86, 90-116, 126, 130-131 /home/admin/.local/lib/python3.8/site-packages/google/auth/jwt.py 237 160 32% 89-115, 120-127, 143-168, 184-185, 201-228, 257-316, 395-406, 424-426, 443-444, 458-461, 491-493, 514-517, 528, 543-560, 570, 574, 579, 584, 589, 637-648, 666-668, 685-686, 700-703, 729-731, 748-751, 763, 779, 790-806, 821-827, 841, 858-864, 868, 873, 878 /home/admin/.local/lib/python3.8/site-packages/google/auth/metrics.py 48 20 58% 46, 54, 62, 70, 80, 89, 98, 106, 114, 120, 126, 132-135, 149-154 /home/admin/.local/lib/python3.8/site-packages/google/auth/transport/__init__.py 20 4 80% 55, 60, 65, 103 /home/admin/.local/lib/python3.8/site-packages/google/auth/transport/_http_client.py 42 24 43% 36-38, 42, 46, 50, 80-113 /home/admin/.local/lib/python3.8/site-packages/google/auth/transport/_mtls_helper.py 134 107 20% 61-65, 81-88, 109-114, 134-144, 148-186, 190-193, 197-207, 211-222, 241-276, 310-337, 360-365, 401-407 /home/admin/.local/lib/python3.8/site-packages/google/auth/transport/mtls.py 35 29 17% 27-39, 53-67, 89-112 /home/admin/.local/lib/python3.8/site-packages/google/auth/version.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/google/oauth2/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/google/oauth2/_client.py 126 100 21% 57-69, 85-110, 123-133, 174-217, 259-271, 297-319, 344-367, 396-419, 439-450, 494-508 /home/admin/.local/lib/python3.8/site-packages/google/oauth2/service_account.py 249 165 34% 174-197, 215, 243-246, 260-263, 268, 273, 282, 285-299, 303-306, 321-330, 334-338, 350-352, 366-370, 374-376, 380-382, 393-415, 420, 423-425, 429-452, 461-490, 496, 501, 506, 510-516, 599-621, 639-643, 661-664, 678-681, 684-695, 709-711, 730-739, 743-745, 749-751, 762-782, 803-809, 820-828, 833, 837, 842, 847 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/google/protobuf/any_pb2.py 16 4 75% 31-34 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/descriptor.py 404 261 35% 66-73, 80-82, 85, 88, 95-97, 138-143, 151-155, 163-181, 209-220, 232-238, 327-369, 376-379, 397, 406, 558, 575-607, 616-618, 635-638, 684-697, 706, 742-750, 781-790, 827-828, 833-845, 856, 865, 892-893, 903-913, 925-931, 977-980, 984, 991-1011, 1019, 1028-1029, 1034-1050, 1055-1058, 1063-1075, 1096-1179 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/descriptor_database.py 57 42 26% 50-51, 63-85, 104, 128-141, 145, 149, 152-158, 171-177 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/descriptor_pool.py 465 393 15% 75-80, 99, 104-107, 111, 140-155, 165-193, 202, 216-221, 227, 240-246, 252, 264-287, 293, 303-308, 314, 329-356, 361, 374-379, 392-394, 409-423, 439-450, 465-499, 514-517, 532-535, 549-552, 566-569, 583-599, 618-622, 637-646, 655-674, 688-691, 705-708, 722-731, 745-826, 843-920, 939-972, 995-1005, 1037-1056, 1067-1132, 1145, 1169-1188, 1204-1209, 1229-1234, 1246-1250, 1263-1272, 1276, 1285 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/internal/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/google/protobuf/internal/api_implementation.py 31 9 71% 44-45, 48, 65-67, 86, 102, 107, 112 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/internal/containers.py 328 229 30% 62-63, 67, 71, 76, 79, 82, 88-90, 93, 114-115, 119-121, 125-127, 132-146, 152-153, 157-158, 162-164, 168-174, 178, 182-186, 190-191, 195-196, 200-206, 231-232, 238-243, 247-252, 256-261, 268-276, 282, 286-287, 291-293, 297, 301-302, 306-307, 311-316, 340-344, 347-353, 358-359, 365-368, 371-374, 377-378, 381, 384, 387, 390-391, 396-398, 402-403, 406, 430-434, 437-446, 460, 466-469, 472-473, 476, 479-481, 484, 487, 490, 494-499, 506-508, 512-513, 516, 527-530, 534, 537-540, 548-550, 553-557, 562-564, 568-570, 574-576, 587, 590-599, 602, 605-608, 611-613, 616-617, 620-623, 626-636, 639-643 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/internal/decoder.py 499 420 16% 108-120, 131-144, 173-179, 196-243, 257-258, 281-283, 309-328, 353-368, 375-508, 547-593, 600-634, 640-681, 687-731, 752-832, 839-876, 887-892, 897-900, 905-906, 912-916, 923-927, 933-944, 950-967, 973, 979-982, 988-989, 995, 1024-1025 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/internal/encoder.py 475 391 18% 82-91, 96-106, 113, 129-148, 158-177, 187-203, 231-247, 253-269, 275-287, 293-308, 326-334, 346-364, 379-381, 394-402, 442-466, 476-500, 516-538, 559-566, 569-578, 582-615, 650-681, 687-705, 711-727, 733-748, 754-769, 787-801, 820-829 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/internal/enum_type_wrapper.py 33 19 42% 53-64, 69-73, 83, 103, 108-114 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/internal/type_checkers.py 121 59 51% 61, 71-76, 80, 92-101, 123-132, 142, 153-155, 157, 164, 172, 175-181, 184, 195-217, 220, 261-272, 275 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/internal/well_known_types.py 447 337 25% 68-72, 76-80, 85, 89, 108-126, 139-190, 194, 198, 202, 207, 212, 216-217, 221-222, 226-227, 231-232, 236, 249-250, 267-288, 301-321, 326, 330-331, 335-336, 340, 344, 349, 355, 361-362, 366, 372, 378-382, 386-395, 406-411, 421-424, 428-433, 437-440, 444-446, 458-459, 463-467, 471-477, 492-493, 499-508, 513-516, 522-546, 551-561, 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191, 198-199, 215, 230, 261, 279, 293, 309, 327, 335, 343, 350, 360, 364, 368, 389, 393, 397-403, 406-413, 419-421 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/message_factory.py 56 39 30% 49, 78-85, 100-121, 137-157, 176-185 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/pyext/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/google/protobuf/pyext/cpp_message.py 5 0 100% /home/admin/.local/lib/python3.8/site-packages/google/protobuf/reflection.py 13 5 62% 75-78, 95 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/symbol_database.py 44 21 52% 95, 108, 118-120, 130, 148, 169-186 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/text_encoding.py 32 13 59% 73-80, 96-107 /home/admin/.local/lib/python3.8/site-packages/google/protobuf/text_format.py 722 458 37% 79-89, 92, 95, 101, 104, 107, 110, 171-192, 198-202, 226-239, 257-263, 281-287, 302-312, 375-391, 395-407, 410-418, 426-457, 461-512, 516-541, 545-548, 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/home/admin/.local/lib/python3.8/site-packages/googleapiclient/http.py 672 543 19% 43-44, 90-147, 170-229, 243-244, 253-256, 269-270, 279-282, 318, 326, 334, 342, 355, 367, 376, 389-396, 405, 419-425, 469-478, 486, 494, 502, 510, 523-524, 536, 545, 549, 592-601, 606-607, 616, 620-621, 658-659, 695-713, 734-780, 801-804, 816-820, 852-874, 896-939, 951, 992-1093, 1109-1126, 1133-1141, 1146-1149, 1162, 1210-1247, 1259-1277, 1290-1296, 1313-1319, 1331-1367, 1379-1395, 1405-1408, 1440-1453, 1468-1525, 1544-1606, 1624-1630, 1638, 1681-1682, 1700-1720, 1732-1744, 1755-1759, 1762, 1794-1796, 1808-1826, 1848-1877, 1898-1930, 1944-1962 /home/admin/.local/lib/python3.8/site-packages/googleapiclient/mimeparse.py 56 41 27% 45-56, 73-83, 95-120, 133, 147-149, 166-177, 181-183 /home/admin/.local/lib/python3.8/site-packages/googleapiclient/model.py 170 103 39% 38, 51, 79, 94, 118-130, 152-182, 193-205, 209-215, 230-241, 252, 264, 284, 287-293, 296-307, 311, 327, 331, 347, 351, 375, 378, 381, 385, 409-429 /home/admin/.local/lib/python3.8/site-packages/googleapiclient/sample_tools.py 31 22 29% 58-108 /home/admin/.local/lib/python3.8/site-packages/googleapiclient/schema.py 110 86 22% 81-84, 99-114, 127, 142-145, 158, 167, 184-200, 208, 216, 225-232, 236, 240, 251-302, 316-317 /home/admin/.local/lib/python3.8/site-packages/googleapiclient/version.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/httplib2/__init__.py 914 737 19% 59-61, 151-188, 192-194, 202-217, 228-229, 233-245, 258-274, 281, 290-292, 296-304, 342-386, 390-412, 416-429, 433-471, 475-478, 482, 498-502, 505-506, 510-511, 516, 526, 529, 532, 535, 538, 541, 544, 547, 552, 557, 567-579, 583-615, 618-630, 639-678, 682-689, 705-708, 721, 726-730, 740-765, 770, 791-794, 797-805, 808-811, 814-816, 824, 827, 830-832, 840, 843-845, 877-881, 900, 911, 914, 918-929, 932, 942-949, 955-979, 994-998, 1002-1066, 1093-1114, 1118-1202, 1272, 1313-1317, 1320-1327, 1330-1331, 1337-1341, 1346, 1351, 1356-1357, 1360-1431, 1439-1510, 1513, 1542-1751, 1775-1793, 1796-1799 /home/admin/.local/lib/python3.8/site-packages/httplib2/auth.py 40 17 58% 40-49, 54-69 /home/admin/.local/lib/python3.8/site-packages/httplib2/certs.py 29 9 69% 10-11, 17, 30-33, 35, 38, 42 /home/admin/.local/lib/python3.8/site-packages/httplib2/error.py 25 3 88% 10-12 /home/admin/.local/lib/python3.8/site-packages/httplib2/iri2uri.py 41 30 27% 49-57, 64-72, 76-124 /home/admin/.local/lib/python3.8/site-packages/httplib2/socks.py 244 201 18% 44, 127, 139-142, 155-162, 169-175, 181-183, 190-206, 209-210, 241, 256-352, 358, 364, 371, 378-422, 429-467, 477-518 /home/admin/.local/lib/python3.8/site-packages/imgaug/__init__.py 8 0 100% /home/admin/.local/lib/python3.8/site-packages/imgaug/augmentables/__init__.py 8 0 100% /home/admin/.local/lib/python3.8/site-packages/imgaug/augmentables/base.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/imgaug/augmentables/batches.py 266 116 56% 24, 168, 285-311, 374, 380, 386, 392, 398, 415, 431, 583-610, 624, 630, 717, 751, 771-785, 803-816, 853-888, 943-954, 979-981, 997, 1018-1029, 1051-1068, 1081-1088 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmentables/bbs.py 484 365 25% 49-58, 73-76, 91, 106, 121, 136, 148, 160, 172, 184, 196, 214-218, 249-253, 282, 318-322, 355, 381-387, 406, 433-437, 459-464, 493-501, 521-523, 548-552, 581-585, 592, 614-628, 647, 673-677, 721-723, 784-795, 843-895, 946-957, 1003-1085, 1101-1103, 1122-1124, 1158-1173, 1201-1203, 1228-1244, 1277, 1319, 1332, 1345, 1348, 1351, 1382-1383, 1397, 1411, 1425, 1439, 1451, 1473-1481, 1500, 1529-1544, 1574-1580, 1601-1606, 1620, 1652-1670, 1694-1695, 1735-1748, 1773-1778, 1800, 1825, 1847, 1854, 1870-1876, 1887, 1913-1915, 1958-1960, 1974-1989, 2015-2028, 2042-2045, 2066-2072, 2094-2100, 2113, 2128, 2141, 2144, 2147, 2158-2165, 2169-2187, 2190, 2194-2195, 2203-2227, 2230-2246, 2251-2258, 2261-2271 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmentables/heatmaps.py 143 116 19% 45-96, 113-125, 156-187, 221-254, 280-286, 323-333, 381-396, 413-414, 435-436, 446, 467-475, 494-496, 536-537, 580-584, 614-659, 671, 682 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmentables/kps.py 364 260 29% 37-67, 100-102, 114, 126, 140, 154, 184-186, 213, 235-239, 265, 287-289, 308, 347-408, 456-487, 512-526, 554, 575, 601, 604, 647, 661, 673, 685, 718-726, 744, 785-790, 819, 845, 863, 879, 901-903, 922, 936, 975, 996-1006, 1077-1097, 1139-1184, 1214-1228, 1280-1334, 1351, 1374-1384, 1405-1411, 1452, 1467, 1480, 1483, 1486 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmentables/lines.py 517 418 19% 48-67, 80-82, 94, 106, 122, 138, 153-155, 170-172, 192-198, 211-213, 240-262, 285-288, 313, 343-344, 371, 400-409, 431-433, 456-463, 495-502, 520-614, 634-671, 697-699, 742-744, 772-778, 812-823, 854-864, 907-923, 967-1052, 1097-1104, 1176-1210, 1266-1305, 1325-1327, 1356-1360, 1372-1373, 1385-1390, 1405-1406, 1443-1444, 1483-1484, 1520-1539, 1563-1565, 1587, 1609, 1624, 1637, 1640, 1643-1645, 1690-1698, 1712, 1726, 1738, 1760-1768, 1787, 1815-1818, 1837-1838, 1913-1923, 1948-1951, 1973, 1998, 2018, 2046-2050, 2076, 2102-2104, 2147-2149, 2163-2165, 2191-2216, 2232-2238, 2262-2277, 2302-2308, 2334-2340, 2353, 2368, 2381, 2384, 2387, 2392-2397, 2401-2414, 2418-2442 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmentables/normalization.py 574 394 31% 14, 16-19, 29-32, 37-46, 64-65, 77-87, 98-99, 111-121, 132, 134-138, 149, 153, 171-187, 203-230, 245, 247-250, 256-257, 260-261, 264-301, 319-384, 433-516, 527-530, 532-565, 570-575, 583, 597-626, 638-669, 675-679, 681-686, 690-700, 703-713, 720-762, 773-861, 898-1040, 1193-1202, 1223-1252, 1262, 1265, 1273-1281, 1286-1288 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmentables/polys.py 731 611 16% 49-70, 104-142, 157, 169, 181, 197, 213, 231-233, 245-248, 263-264, 279-280, 310-311, 338, 369-380, 402-405, 435-438, 459, 480, 511-536, 543, 575-650, 676-678, 721-723, 818-902, 928-957, 993-1008, 1031-1041, 1062-1069, 1089, 1101-1103, 1125, 1138-1142, 1157-1159, 1178-1181, 1208-1223, 1250, 1297-1306, 1340-1342, 1364, 1385, 1400, 1413, 1416, 1419-1423, 1455-1456, 1470, 1484, 1496, 1517-1525, 1543, 1637-1653, 1678-1682, 1702, 1725, 1747, 1777-1781, 1806, 1831-1833, 1876-1878, 1896-1898, 1916, 1930-1932, 1964-1988, 2003-2009, 2032-2047, 2072-2078, 2104-2110, 2123, 2138, 2151, 2154, 2157, 2164-2182, 2188-2230, 2233-2281, 2284-2299, 2303-2317, 2321-2328, 2331-2392, 2397-2407, 2413-2526, 2531-2573, 2579-2589, 2592-2760, 2777-2782, 2806-2829 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmentables/segmaps.py 124 101 19% 21, 103-167, 195-205, 211, 236-255, 312-381, 418-421, 466-476, 482, 505-507, 536-540, 568-572 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmentables/utils.py 114 88 23% 12, 25-37, 57-59, 90-111, 139-142, 167-173, 204-218, 252-270, 290-296, 323-334, 339-342, 348-361 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/__init__.py 21 0 100% /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/arithmetic.py 791 668 16% 101-118, 130-161, 165-204, 247-261, 274-283, 298-325, 383-400, 411-442, 448-492, 548-565, 571-583, 587-628, 686, 754-781, 816-847, 877-893, 943-1004, 1038, 1132-1186, 1190-1193, 1199-1202, 1207-1211, 1236-1252, 1259-1261, 1268-1281, 1287-1309, 1335, 1369, 1407-1470, 1552-1559, 1564-1607, 1611, 1698-1705, 1710-1729, 1733, 1836-1845, 1959-1968, 2075-2081, 2167-2174, 2179-2221, 2225, 2311-2318, 2323-2353, 2357, 2365-2373, 2554-2570, 2576-2587, 2591-2627, 2631-2663, 2680-2698, 2703, 2792-2794, 2803-2834, 2993-3010, 3113-3128, 3132-3165, 3171-3209, 3214, 3301-3315, 3319-3353, 3357-3359, 3364-3366, 3371, 3483-3491, 3496-3537, 3541, 3612, 3675, 3816-3831, 3905-3913, 4035-4055, 4132-4139, 4259-4279, 4414-4431, 4436-4460, 4464-4485, 4496, 4505-4510, 4579, 4664-4665, 4742-4748, 4754-4765, 4769 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/artistic.py 105 84 20% 99-157, 164-170, 175-189, 194-198, 203-206, 211-221, 226-239, 244-246, 365-381, 385-396, 400-401, 413 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/base.py 14 7 50% 21-27, 43, 49 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/blend.py 584 447 23% 38-43, 111-211, 216-242, 247-258, 403-422, 426-472, 476, 481, 486, 491-498, 616-648, 652-695, 704-718, 724-785, 789, 794, 799, 804-810, 958-962, 970, 1160-1190, 1411-1442, 1581, 1704, 1833, 1962, 2064, 2196, 2325, 2407-2409, 2418-2423, 2429-2451, 2562-2578, 2586-2592, 2598, 2607-2626, 2667-2684, 2690-2694, 2701-2703, 2708-2735, 2740-2744, 2752-2762, 2773-2777, 2783, 2792-2801, 2842-2881, 2942, 2982, 3041, 3081, 3134-3142, 3153-3158, 3164-3175, 3205-3242, 3275, 3291, 3305, 3315-3320, 3348-3359, 3434-3450, 3462-3469, 3475-3490, 3518-3528, 3598-3614, 3626-3637, 3643-3658, 3686-3699, 3724-3725, 3734-3740, 3758, 3782, 3809, 3842 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/blur.py 259 182 30% 174-181, 186-215, 219, 221, 223, 225, 242, 263, 265, 329-367, 372, 376, 461, 473, 570-616, 622-686, 690, 768-781, 787-815, 819, 932-942, 949-975, 979, 1075-1088, 1098-1101, 1106-1134, 1213-1220, 1227-1236, 1240-1241, 1251 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/collections.py 50 33 34% 192-218, 233, 254-293, 340-341 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/color.py 642 462 28% 69-72, 240-310, 374-395, 405-407, 414, 436-454, 459-853, 888-950, 983, 994, 1063-1069, 1073-1093, 1096-1100, 1104, 1108, 1111, 1226-1234, 1238-1266, 1270-1277, 1282-1285, 1289-1293, 1298, 1303, 1307, 1396-1402, 1414, 1497, 1571, 1666-1675, 1679-1688, 1692-1712, 1716-1744, 1747-1751, 1755, 1759, 1762, 1891-1974, 2048, 2117, 2196-2204, 2380-2398, 2401-2438, 2442-2483, 2501-2511, 2516-2521, 2525, 2530-2543, 2547-2554, 2558-2564, 2572-2582, 2653, 2726, 2858-2905, 2908-2913, 2917-2939, 2943, 3021, 3076-3083, 3087-3095, 3100, 3115-3126, 3129-3139, 3143-3153, 3157-3210, 3218, 3228-3238, 3380, 3396, 3399, 3409, 3484-3526, 3663, 3679, 3682, 3824, 3836, 3858, 3889, 3957-3974, 3993-3995, 4015-4017, 4023, 4031, 4039-4053, 4081, 4133-4136, 4165 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/contrast.py 303 239 21% 37-45, 49-90, 94, 149-172, 233-258, 318-340, 388-421, 489-493, 589-599, 676-681, 754-761, 788-803, 806-898, 902, 1001-1012, 1017-1082, 1086, 1265-1275, 1280-1309, 1313-1315, 1388, 1394-1420, 1424, 1541-1549, 1554-1583, 1587-1588 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/convolutional.py 149 115 23% 126-143, 150-234, 238, 313-322, 330-331, 334-353, 424-433, 441-442, 445-464, 521-527, 535, 538-556, 654-664, 672-673, 676-717 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/debug.py 470 319 32% 42-77, 138-140, 145, 150, 154-159, 171, 176, 181-184, 188-191, 203-205, 210, 215, 219-250, 255-256, 271-272, 277, 282, 286-294, 305, 314, 323, 332, 340-341, 358-359, 367-373, 470-496, 502, 509, 515-527, 533-558, 564-593, 599-611, 617-671, 677-690, 696-708, 714-756, 762-825, 832-843, 849-850, 863, 868, 873, 878-882, 887, 892-894, 899-901, 906-908, 913-915, 920, 925-926, 931-932, 937, 942-943, 948-949, 953-957, 961-965, 970, 975, 980, 985-987, 992, 997, 1002, 1007-1010, 1051, 1055-1056, 1060-1061, 1071-1075, 1079-1080, 1086, 1123-1124, 1128-1130, 1170-1174, 1178-1193, 1256-1266, 1273-1274 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/edges.py 94 68 28% 93-101, 110-114, 117-159, 162, 327-375, 382-415, 419-468, 472, 476 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/flip.py 114 92 19% 722-724, 728, 734-761, 805, 811, 817, 872-875, 879-925, 929, 984-987, 991-1039, 1043 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/geometric.py 1751 1369 22% 92-96, 102, 106-120, 129, 139, 143-150, 158, 162, 169, 185-188, 215-244, 267, 269, 298-312, 315, 317, 323-351, 399-443, 475-508, 543-582, 607, 611, 639, 672, 681, 1178-1181, 1224-1229, 1253-1268, 1279-1284, 1309-1314, 1340, 1345, 1366-1371, 1392, 1414, 1417, 1422-1424, 1427, 1434-1473, 1479, 1489, 1503, 1513-1515, 1536, 1607, 1684, 1771-1774, 1862-1865, 1941, 2016, 2091, 2405-2571, 2576-2583, 2591-2676, 2679-2691, 2694-2707, 2711-2774, 2778, 2783, 2788, 2793, 2797-2841, 2849-2854, 2857-2860, 3009-3043, 3047-3081, 3085-3128, 3133-3169, 3174-3242, 3245-3271, 3287-3354, 3358, 3365-3369, 3551-3586, 3592-3621, 3632-3681, 3685-3753, 3758-3817, 3821-3847, 3852-3962, 3972-3988, 3993-4011, 4015, 4021-4026, 4239-4269, 4273-4275, 4281-4293, 4298-4304, 4310-4358, 4363-4379, 4385-4433, 4438-4496, 4501-4503, 4509-4511, 4516-4518, 4522, 4527-4554, 4672-4793, 4901-4911, 4914, 4919-4943, 4948-4966, 4971-4991, 4996-5029, 5033, 5165-5168, 5172-5204, 5209-5238, 5243-5278, 5283, 5288, 5293, 5298, 5304, 5310, 5316, 5321, 5326-5328, 5333-5335, 5340, 5345, 5350, 5355, 5360-5413, 5419-5476, 5481-5505, 5511-5532, 5537-5560, 5566-5589, 5594-5608, 5613-5629, 5635-5654, 5667-5707, 5712, 5717, 5721-5725, 5729-5733, 5849-5862, 5866-5935, 5939-5955, 5961-5970, 5976-5986, 5991-5996, 6001-6007, 6011, 6018-6021 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/imgcorruptlike.py 197 121 39% 96-112, 144-212, 243-257, 297, 329, 361, 393, 425, 457, 470-515, 550, 582, 614, 646, 678, 710, 742, 774, 806, 838, 870, 902, 934, 1009-1014, 1020-1029, 1033-1037, 1042, 1098, 1157, 1216, 1275, 1334, 1393, 1452, 1511, 1570, 1629, 1688, 1747, 1806, 1865, 1924, 1983, 2042, 2101, 2164, 2171-2177 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/meta.py 1062 774 27% 47, 53, 59-61, 68-72, 77-100, 108-117, 122-125, 130-142, 147-149, 153-157, 166-173, 207-210, 215, 219, 296, 299-304, 313-314, 320, 370-528, 550, 598-602, 610-616, 622-624, 626-632, 649, 654-659, 668-670, 713-737, 762-771, 821-822, 874, 901, 940, 966, 1010, 1071, 1116, 1180, 1246, 1315, 1364, 1406, 1449, 1479, 1524-1529, 1558, 1592-1596, 1631-1656, 1682-1687, 1933-1934, 1945-1957, 1984, 1995-2000, 2003, 2081-2082, 2139-2186, 2213-2214, 2252-2256, 2272-2287, 2296, 2357-2373, 2393-2397, 2443-2449, 2479-2487, 2552-2613, 2627, 2664, 2686-2696, 2740-2757, 2780, 2805-2813, 2871-2888, 2897, 2935-2947, 2958, 2975, 2978, 2981-2983, 3094, 3100, 3107, 3119, 3132-3137, 3141, 3152, 3156, 3159-3164, 3287-3315, 3319-3343, 3346-3355, 3358-3362, 3366-3374, 3378-3411, 3414-3419, 3423, 3434, 3438, 3441-3446, 3512, 3599-3607, 3612-3641, 3644-3653, 3657, 3661-3666, 3669-3673, 3746-3766, 3770-3811, 3816, 3824-3831, 3841-3849, 3859-3861, 3865-3869, 3873-3878, 3882-3898, 3901-3905, 3909, 3913, 3916-3920, 3980, 3986, 3991, 4035, 4222-4231, 4234-4236, 4239-4252, 4255-4269, 4273-4287, 4291-4311, 4316-4333, 4338-4363, 4367, 4497-4504, 4521-4522, 4526-4529, 4669-4677, 4697-4718, 4725-4733, 4741, 4746-4748, 4754, 4757-4759, 4765, 4768-4770, 4776, 4779-4781, 4787, 4791-4794, 4800, 4803-4805, 4811, 4815-4818, 4892-4906, 4910-4922, 4926, 4972-4992, 5088-5092, 5096-5103, 5108, 5176, 5182-5188, 5193 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/pillike.py 343 243 29% 80-90, 122, 151, 182, 211, 244-249, 294-313, 320-347, 352-362, 415-426, 432, 446-531, 536-554, 597, 641, 684, 727, 732-750, 787, 824, 861, 898, 936, 973, 1010, 1047, 1084, 1121, 1132-1189, 1278-1316, 1373, 1444, 1451-1454, 1459, 1533-1540, 1558-1562, 1568-1574, 1578, 1583, 1643, 1709, 1775, 1841, 1855-1858, 1862-1865, 1870, 1917, 1967, 2018, 2070, 2122, 2173, 2224, 2274, 2324, 2375, 2489-2503, 2507-2513, 2520-2544, 2549-2567, 2572 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/pooling.py 113 76 33% 26-36, 49-59, 66-76, 83-92, 96-111, 115, 120, 126-150, 154-168, 172-174, 179-181, 186-188, 193, 312, 318, 433, 441, 556, 564, 679, 687 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/segmentation.py 353 269 24% 56-66, 212-222, 226-283, 287-319, 323, 357-378, 383-388, 392-393, 398-416, 421-441, 598-611, 615-634, 637-654, 658, 776, 940, 1122, 1174-1187, 1245-1248, 1253-1257, 1260-1263, 1267-1279, 1283-1286, 1290-1313, 1316, 1319, 1377-1381, 1387-1391, 1396-1410, 1413, 1417, 1463-1468, 1474-1495, 1498-1505, 1508-1512, 1515-1518, 1522-1538, 1541, 1545, 1580, 1585-1596, 1600-1603, 1608-1620, 1623, 1626, 1664-1671, 1676-1682, 1688-1692, 1695, 1699 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/size.py 1205 1047 13% 48-66, 70-72, 77-90, 95, 102, 110-147, 154-166, 170-174, 179-219, 225-253, 257, 262-279, 285-330, 348-350, 425-553, 607-621, 680-695, 734-766, 807-838, 874-902, 937-965, 1007-1037, 1084-1115, 1123, 1267-1272, 1276-1359, 1363-1378, 1382-1410, 1414-1434, 1438-1461, 1465-1475, 1478-1490, 1494-1529, 1533, 1539-1548, 1553, 1558, 1804-1828, 1833-1847, 1852-1902, 1906-1964, 1968-1997, 2001-2019, 2024-2043, 2047-2056, 2059-2169, 2173, 2377-2399, 2563-2585, 2731-2756, 2764-2790, 2794-2812, 2816-2831, 2836-2860, 2863-2884, 2889-2904, 2908, 2972, 3109-3121, 3129-3153, 3157-3171, 3175-3189, 3193-3204, 3210-3223, 3226-3245, 3249, 3310, 3381-3386, 3390-3412, 3417, 3477, 3551-3557, 3561-3583, 3588, 3657, 3739-3744, 3748-3770, 3775, 3835, 3914-3920, 3924-3946, 3951, 4019, 4085-4089, 4093-4118, 4123, 4180, 4248-4253, 4257-4279, 4284, 4340, 4399, 4461, 4523, 4579, 4701-4737, 4742-4781, 4787-4807, 4813-4825, 4830-4838, 4843-4855, 4858-4901, 4904-4908, 4912, 4916, 4919-4927 /home/admin/.local/lib/python3.8/site-packages/imgaug/augmenters/weather.py 226 166 27% 140-150, 153-159, 163-186, 190, 353-366, 371-379, 383, 394-414, 422-451, 457-466, 471-478, 484-495, 563-594, 666, 855-876, 880-888, 892, 903-953, 957-958, 965-969, 975, 979-988, 997-1004, 1012-1017, 1022-1023, 1028-1029, 1204-1217, 1301, 1311, 1317-1319, 1328-1339, 1428-1441 /home/admin/.local/lib/python3.8/site-packages/imgaug/dtypes.py 148 109 26% 20, 35-49, 54-97, 104, 108-112, 116-135, 150-172, 177-183, 187-189, 196-197, 201-207, 217-253, 258-282, 319-345 /home/admin/.local/lib/python3.8/site-packages/imgaug/external/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/imgaug/external/opensimplex.py 1412 1385 2% 14-15, 85, 100-113, 116-120, 123-129, 132-140, 148-244, 252-740, 748-1934 /home/admin/.local/lib/python3.8/site-packages/imgaug/imgaug.py 599 461 23% 14-15, 86-87, 106, 147, 165-187, 192, 365, 382, 400-402, 419, 440-448, 462, 491-506, 525-526, 541-542, 567-572, 586-587, 610-613, 632-633, 656-657, 670-671, 703-726, 761-802, 839-846, 866, 889-906, 928-957, 983-1003, 1029-1056, 1083-1106, 1142-1146, 1200-1216, 1273-1306, 1403-1572, 1576-1578, 1608-1619, 1691-1744, 1791, 1838, 1882, 1926, 1976-2034, 2061-2062, 2095-2123, 2142-2143, 2150-2151, 2153, 2180, 2227-2273, 2352-2355, 2369-2371, 2389-2391, 2402-2404, 2415-2417, 2455-2461 /home/admin/.local/lib/python3.8/site-packages/imgaug/parameters.py 1056 827 22% 37, 40-43, 51-62, 74-99, 112-153, 161-187, 197-247, 254-293, 299-301, 306-314, 320-336, 342, 387, 420, 423-425, 431-433, 439-441, 447-453, 459-461, 467-469, 475-477, 483-485, 491-493, 499-501, 507-513, 519-521, 527-529, 535-537, 551, 562, 594-628, 659, 663, 675, 678-682, 706-727, 731-739, 743, 747-750, 787-799, 802-856, 859, 862, 899-900, 903-907, 910, 913, 955-958, 962-968, 971, 974, 1014-1016, 1019-1022, 1025, 1028, 1068-1071, 1075-1080, 1083, 1086, 1143-1149, 1153-1170, 1173, 1176, 1220-1223, 1227-1232, 1235, 1238, 1273-1275, 1279-1281, 1284, 1287, 1323-1325, 1329-1331, 1334, 1337, 1379-1382, 1386-1392, 1395, 1398, 1438-1445, 1448-1452, 1455, 1458, 1538-1589, 1592-1653, 1656, 1659-1670, 1703-1715, 1718-1723, 1726, 1729-1737, 1766-1769, 1772-1791, 1794, 1797-1798, 1846-1850, 1853-1867, 1870, 1873, 1926-1930, 1934-1958, 1961, 1964, 2018-2022, 2025-2038, 2041, 2044, 2093-2097, 2100-2113, 2116, 2119, 2169-2173, 2176-2202, 2205, 2208, 2229-2233, 2236-2237, 2240, 2243-2244, 2269-2280, 2283-2300, 2303, 2306-2307, 2347-2364, 2367-2404, 2407, 2410-2411, 2449, 2491, 2570-2622, 2628-2659, 2662, 2665-2666, 2731-2746, 2771, 2774-2789, 2792, 2795-2796, 2870-2890, 2895-2906, 2909-2934, 2937-2977, 2980, 2983, 3072-3093, 3103-3114, 3117-3177, 3181-3188, 3191, 3194, 3201 /home/admin/.local/lib/python3.8/site-packages/imgaug/random.py 378 202 47% 67, 172, 185, 202-203, 224, 241, 256, 272, 293, 304-305, 318, 336, 348-352, 384, 396-398, 438, 455, 476, 489, 496, 500, 507, 512, 517, 521, 526, 530, 534, 538, 542, 546, 550, 554, 559, 563, 567, 571, 575, 580, 585, 590, 594, 599, 604, 608, 613, 617, 621, 633-643, 654-665, 676-686, 691, 695, 700, 705, 709, 714, 719, 738, 756, 770, 783-785, 798, 811-814, 831, 880-883, 891, 895, 940, 961, 970, 975-978, 985-992, 996-1003, 1022, 1032, 1065-1066, 1080-1082, 1087, 1091, 1154-1156, 1163-1166, 1170-1173, 1196-1198, 1219, 1237-1240, 1260, 1284-1286, 1314-1319, 1324-1325, 1346-1348, 1356, 1373-1376, 1384, 1405-1407, 1411-1431, 1435-1444, 1466, 1477-1478, 1515-1519, 1521, 1550-1561, 1586-1587, 1590-1592, 1595-1596 /home/admin/.local/lib/python3.8/site-packages/importlib_resources/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/importlib_resources/_common.py 101 56 45% 35-46, 56, 68-72, 77, 82, 87, 95-104, 112-114, 129-141, 145, 156-158, 167, 176, 184-185, 194-196, 200-207 /home/admin/.local/lib/python3.8/site-packages/importlib_resources/_compat.py 58 36 38% 13, 20-23, 28-29, 42, 46, 49-75, 101-103, 107, 117-126 /home/admin/.local/lib/python3.8/site-packages/importlib_resources/abc.py 65 23 65% 26, 39, 47, 52, 79-80, 86-87, 109-124, 130, 161, 164, 167, 170 /home/admin/.local/lib/python3.8/site-packages/jmespath/__init__.py 12 4 67% 10-12, 19, 23 /home/admin/.local/lib/python3.8/site-packages/jmespath/ast.py 44 22 50% 6, 10, 14, 18, 22, 26, 30, 34, 38, 42, 46, 50, 54, 58, 62, 66, 70, 74, 78, 82, 86, 90 /home/admin/.local/lib/python3.8/site-packages/jmespath/compat.py 40 21 48% 16-48 /home/admin/.local/lib/python3.8/site-packages/jmespath/exceptions.py 68 36 47% 13-19, 23-24, 34-37, 41-42, 50-57, 60-61, 68-71, 74, 82-85, 91, 103-106, 109, 117 /home/admin/.local/lib/python3.8/site-packages/jmespath/functions.py 228 141 38% 73-81, 84-91, 94-97, 104-120, 124-134, 137-161, 166, 170-173, 177-179, 183-186, 190-193, 198-211, 215, 219, 223, 227, 231-234, 238, 242, 246, 250-253, 257-260, 264-267, 271-274, 278, 282, 288, 292, 296-307, 311-327, 331-337, 341-347, 350-359, 362 /home/admin/.local/lib/python3.8/site-packages/jmespath/lexer.py 139 120 14% 27-110, 114-118, 121-127, 130-135, 140-156, 159-176, 180-188, 193-196, 200-207 /home/admin/.local/lib/python3.8/site-packages/jmespath/parser.py 313 244 22% 79-82, 85-92, 95-105, 108-116, 119-135, 138, 141, 144-152, 155-160, 163, 166, 169-171, 174-177, 180-181, 184-198, 205-213, 219-237, 240, 243-244, 247-259, 262-263, 266-267, 270-271, 274-291, 295-301, 304, 307, 310, 313, 316, 319, 322-325, 328-344, 347-353, 356-357, 360-369, 372-389, 393-406, 417-434, 437-440, 443, 447-451, 455-458, 461, 464, 467, 470, 473-476, 480-488, 492-493, 498, 504-505, 508-510, 522-524, 527 /home/admin/.local/lib/python3.8/site-packages/jmespath/visitor.py 212 161 24% 9-12, 32-35, 43, 54-56, 70-71, 76-77, 80, 85, 88-94, 97, 113-123, 126, 129-132, 135-138, 142-158, 161, 164, 167-171, 174-184, 187-197, 200, 205-210, 213-216, 219-222, 225, 228, 231-236, 239-244, 247-250, 253-256, 259-264, 267-270, 273-281, 284-294, 300, 304, 309-311, 314-319, 322-328 /home/admin/.local/lib/python3.8/site-packages/lxml/__init__.py 11 9 18% 12-22 /home/admin/.local/lib/python3.8/site-packages/matplotlib/__init__.py 517 265 49% 165-178, 190-191, 223, 240-243, 276-277, 356-460, 465-480, 505, 511, 514-515, 521-537, 608-609, 617, 702-706, 708-709, 711-714, 717-718, 721-722, 724-725, 731-734, 737-740, 745-748, 758-764, 767, 775, 788-789, 803, 808-814, 821-828, 863-865, 872, 875-878, 889-902, 927-945, 977, 1033-1052, 1074-1077, 1090-1092, 1115-1119, 1168-1177, 1233-1240, 1252, 1263, 1270, 1288-1293, 1308-1316, 1320-1325, 1348, 1366, 1368, 1448-1472 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_afm.py 242 190 21% 54, 61-65, 69, 73-74, 78, 82-85, 105-168, 206-237, 252-269, 306-323, 339-355, 362-364, 367-369, 376-394, 398-424, 428, 432-434, 440-442, 446, 450-452, 458-459, 466, 470, 474, 478-481, 485-493, 498, 502, 506, 510, 514, 518, 525, 532 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_api/__init__.py 126 30 76% 47, 58, 83, 89-93, 124, 128-131, 158-168, 187, 191-192, 256, 270, 281, 336, 341, 357-359, 382 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_api/deprecation.py 173 33 81% 28-29, 142-143, 156-159, 162-164, 167-169, 292-296, 310, 370-373, 387, 392, 400-403, 449, 486-503 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_blocking_input.py 8 7 12% 21-30 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_cm.py 141 12 91% 59-64, 145-152 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_cm_listed.py 11 0 100% /home/admin/.local/lib/python3.8/site-packages/matplotlib/_color_data.py 5 0 100% /home/admin/.local/lib/python3.8/site-packages/matplotlib/_constrained_layout.py 373 352 6% 102-149, 162-194, 202-240, 247-260, 264-297, 303-335, 347-440, 447-479, 507-576, 583-596, 615-624, 632-665, 689-751, 761-768, 772-783 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_docstring.py 39 4 90% 35, 53, 59-60 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_enums.py 57 36 37% 24, 89-111, 161-177 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_fontconfig_pattern.py 46 7 85% 89-91, 97, 101-105, 114-118 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_layoutgrid.py 208 174 16% 40-103, 106-118, 126-128, 132-137, 144-162, 166, 173-206, 213-245, 266-267, 287-288, 303-304, 322-323, 339-347, 352, 359-367, 374-391, 398-411, 418-429, 436-448, 455-466, 473-484, 490, 497, 502-547 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_mathtext.py 1244 988 21% 57-66, 100-102, 105-111, 116-147, 170-171, 180, 218-219, 227-228, 234, 240, 247, 255, 264, 274-282, 285-295, 298-300, 304-323, 334-343, 349, 353-358, 380-387, 392-405, 464, 489-519, 524, 527-586, 589-592, 599-617, 621-632, 699-704, 709-753, 757-773, 912-919, 926, 929, 932, 939, 949-952, 955-959, 962, 969, 976, 993-1002, 1005, 1008-1015, 1018, 1027-1034, 1037, 1042-1047, 1057-1061, 1064-1065, 1068, 1077-1083, 1086, 1093-1104, 1108-1113, 1120-1123, 1133-1148, 1187-1226, 1233-1234, 1258-1305, 1320-1321, 1324, 1331-1334, 1341-1342, 1368-1375, 1378-1381, 1391, 1401, 1419-1420, 1423, 1426-1428, 1441-1467, 1480-1495, 1508-1637, 1646-1649, 1664-1668, 1671, 1675, 1679-1681, 1685, 1701-1711, 1800-1955, 1964-1977, 1981, 1985, 1989, 1992, 1995, 1998-2000, 2003-2009, 2019-2028, 2046-2048, 2051, 2054-2096, 2099, 2127-2141, 2148-2150, 2153-2185, 2188-2192, 2195-2196, 2199, 2204-2205, 2208-2209, 2212-2216, 2219-2221, 2224-2226, 2229, 2232-2391, 2394-2429, 2432, 2435, 2441, 2446, 2451, 2456-2483, 2488-2525, 2528-2544, 2547-2566, 2569 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_mathtext_data.py 6 0 100% /home/admin/.local/lib/python3.8/site-packages/matplotlib/_pylab_helpers.py 67 27 60% 41, 55-67, 72-75, 80-83, 88, 93, 98, 115, 130-132 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_text_helpers.py 23 1 96% 34 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_tight_bbox.py 47 44 6% 18-70, 80-84 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_tight_layout.py 133 125 6% 48-157, 170-191, 226-301 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_type1font.py 396 320 19% 56-58, 61, 65, 69, 73, 77, 81, 84, 91, 94, 101, 108, 115, 118, 137-141, 145-151, 158, 165, 168-171, 190-270, 294-315, 364-373, 377-402, 415-441, 457-463, 482-489, 498-592, 595-626, 630-653, 660-680, 684-692, 714-770 /home/admin/.local/lib/python3.8/site-packages/matplotlib/_version.py 11 2 82% 5-6 /home/admin/.local/lib/python3.8/site-packages/matplotlib/artist.py 664 260 61% 36-37, 58-61, 66-67, 70, 75, 77, 81-82, 97-98, 113, 145, 217-221, 241-259, 304, 317, 327, 350, 367-376, 405, 415, 457, 462, 483-485, 504-508, 518, 531-555, 590, 602, 616, 630, 641, 713-717, 727-728, 754, 813-814, 816, 822-823, 825-826, 828-829, 832, 864, 879-881, 892, 896, 908-910, 959-964, 985-986, 1003-1005, 1017, 1020, 1036, 1040-1046, 1076-1078, 1127, 1178, 1193, 1197, 1271-1286, 1317, 1337-1373, 1397-1403, 1414-1417, 1435-1437, 1441, 1485, 1493, 1515-1519, 1596-1600, 1614, 1616-1617, 1635-1666, 1683-1700, 1704-1715, 1746-1751, 1816-1838 /home/admin/.local/lib/python3.8/site-packages/matplotlib/axes/__init__.py 9 1 89% 10 /home/admin/.local/lib/python3.8/site-packages/matplotlib/axes/_axes.py 2254 1885 16% 98-102, 158, 172, 179, 193-195, 317, 323, 381-398, 461-511, 547-550, 585-591, 617-623, 704, 761-776, 829-844, 849-851, 904-926, 966-974, 1022-1031, 1072-1111, 1152-1191, 1304-1437, 1772-1776, 1821-1829, 1872-1876, 1919-1923, 1996, 2073-2105, 2174-2176, 2190-2228, 2340-2525, 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254-257, 285-293, 341-343, 364-371, 415-425, 464, 469-472, 475, 479-483, 486-495, 509-518, 527, 531, 537, 561, 563, 573, 587, 598-606, 610, 615, 620, 643-647, 654-658, 665-666, 719 /home/admin/.local/lib/python3.8/site-packages/matplotlib/collections.py 835 494 41% 182, 187, 195, 205, 208, 216, 219, 232, 257, 263, 266, 277-280, 300, 305, 328-330, 332-334, 346, 358-359, 362, 365-366, 384-391, 394, 397, 400-405, 434, 443-471, 494, 535, 545-553, 612-617, 635, 638, 649, 652, 677, 680-684, 722-723, 727, 731, 749, 758, 764, 769-775, 777-779, 799, 822, 825, 847-853, 869, 873-887, 890, 894, 901, 906-925, 943, 958-959, 1069-1144, 1170-1173, 1189-1215, 1221-1226, 1238-1244, 1264-1271, 1315-1320, 1323, 1326, 1330-1337, 1408-1412, 1415-1421, 1434-1448, 1451, 1454, 1457, 1460, 1473, 1478, 1541-1549, 1555-1556, 1560-1571, 1575-1580, 1585, 1591, 1598-1603, 1613-1618, 1622, 1626-1635, 1639, 1643-1652, 1656, 1659, 1663, 1680-1683, 1711-1718, 1723-1760, 1764-1765, 1807-1821, 1824-1826, 1836-1846, 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78-84, 91-97, 102-121, 126-129, 136-137, 144-145, 153-154, 162-168, 185-189, 205-225 /home/admin/.local/lib/python3.8/site-packages/matplotlib/image.py 760 617 19% 83-110, 134-157, 171-213, 221-227, 259-274, 277-281, 285, 289-292, 302-306, 318, 325-326, 358-587, 607, 615, 620-646, 650-677, 681-683, 695-731, 743, 754, 771-776, 788-792, 796-797, 811-814, 818, 830-831, 835, 846-850, 854, 920-922, 936-938, 942-949, 954, 977-1002, 1006-1014, 1025-1041, 1058-1059, 1063, 1067-1133, 1148-1165, 1168, 1177-1180, 1183-1185, 1188, 1191, 1194-1196, 1199-1201, 1245-1248, 1252-1281, 1284, 1304-1338, 1341, 1345-1354, 1379-1389, 1393-1394, 1399-1410, 1416-1417, 1440-1451, 1454-1462, 1466-1476, 1480-1486, 1538, 1541-1553, 1558, 1621, 1627-1633, 1641, 1648, 1657, 1665-1666, 1679-1686, 1711-1724, 1734-1754, 1796-1818 /home/admin/.local/lib/python3.8/site-packages/matplotlib/layout_engine.py 69 39 43% 63-64, 70, 78-80, 88-90, 96, 103, 122-124, 130, 158-162, 181-189, 207-209, 249-259, 269-274, 303-305 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397, 400-403, 406, 421-423, 427-442, 446, 454-456, 460-473, 477, 483-488, 492-493, 496, 502 /home/admin/.local/lib/python3.8/site-packages/matplotlib/projections/polar.py 719 577 20% 50-54, 63, 68-77, 81-131, 135, 165-169, 175-184, 207-210, 219-231, 235, 246-253, 259, 262, 265, 268, 271, 274, 277, 290-291, 294-295, 298-302, 305-306, 324-332, 337-344, 347-352, 355-396, 413-416, 420-422, 425-433, 437-445, 458-459, 462, 466-471, 478-479, 483-487, 490-494, 514-518, 523-544, 559-561, 566-615, 618-695, 710-711, 714-716, 720-722, 725-726, 735, 744, 761-765, 771-800, 815-821, 825-844, 848-849, 857-951, 955-956, 959, 962, 965-970, 973-982, 985-991, 994-1037, 1040, 1043-1053, 1057, 1061, 1065, 1069, 1087-1098, 1104-1106, 1112, 1129-1138, 1150-1159, 1171, 1181, 1190, 1200, 1209, 1219, 1227, 1230, 1244-1256, 1266, 1277, 1280-1281, 1285, 1288, 1340-1349, 1402-1415, 1419-1441, 1453, 1463, 1473, 1476-1486, 1496, 1499-1523 /home/admin/.local/lib/python3.8/site-packages/matplotlib/pyplot.py 860 424 51% 119-120, 136, 145-157, 163-167, 175, 180-182, 188-191, 208, 234-267, 276-279, 304-322, 337, 352, 362-373, 375, 445-446, 476, 512-516, 552-556, 576-584, 589, 594, 599-601, 609, 614, 619, 658-686, 804-807, 814-825, 831, 846, 849-853, 867, 889-890, 906, 911, 921-923, 940, 945, 950, 969-991, 1017, 1022-1025, 1032, 1118-1126, 1133-1135, 1142-1143, 1149, 1290-1352, 1613-1621, 1664-1683, 1696-1699, 1712-1715, 1726-1734, 1753-1756, 1791-1795, 1830, 1881-1883, 1893, 1944-1946, 1954-1956, 2020-2029, 2088-2097, 2105-2108, 2116-2118, 2130-2138, 2155-2159, 2165, 2184-2190, 2195, 2242-2252, 2267-2274, 2284, 2295, 2303, 2315, 2324, 2335, 2343, 2349, 2355, 2361, 2370, 2380, 2389, 2395, 2401, 2407, 2419, 2425, 2431, 2439, 2447, 2457, 2467, 2483, 2500, 2508, 2517, 2527-2531, 2537-2541, 2550, 2564, 2578, 2588, 2598, 2608, 2627-2635, 2645, 2658, 2669-2674, 2682, 2695-2704, 2716, 2722, 2730, 2739, 2745, 2751, 2759-2764, 2773-2778, 2786, 2822, 2833, 2843-2847, 2853, 2874, 2880, 2890-2897, 2905-2909, 2917, 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274 146 47% 69, 76, 111, 145-150, 153, 156, 180-182, 186, 190-198, 205-209, 213, 218-236, 239, 246-247, 250, 253, 256, 281-282, 288-291, 297, 301-304, 333-335, 339, 343, 350-361, 364-371, 374, 382-388, 391-398, 401, 440-441, 449-453, 457, 465-469, 472, 475, 483-484, 487, 490, 551-557, 562, 565-574, 581-584, 588-593, 596, 599, 606-607, 611, 614, 617, 646-648, 652, 657-665, 677-679, 726 /home/admin/.local/lib/python3.8/site-packages/matplotlib/spines.py 315 142 55% 33, 90-99, 103-109, 113-114, 126-131, 137-138, 156, 171-176, 189-194, 231, 234, 240, 243-270, 282, 314, 317, 319, 329-330, 338-341, 351, 357-386, 408-419, 423, 438, 448-451, 456-460, 476-477, 491, 494-505, 508-512, 546, 549, 554-555, 560-563, 566, 568-571, 578, 582 /home/admin/.local/lib/python3.8/site-packages/matplotlib/stackplot.py 42 37 12% 71-127 /home/admin/.local/lib/python3.8/site-packages/matplotlib/streamplot.py 370 328 11% 91-241, 247-248, 274-284, 288, 291, 294, 297, 300-301, 304-305, 308-311, 314, 321-362, 366, 372, 386-396, 399, 403-404, 408-409, 417-426, 443-502, 535-602, 607-624, 633-667, 678-707 /home/admin/.local/lib/python3.8/site-packages/matplotlib/style/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/matplotlib/style/core.py 92 45 51% 22, 127-180, 220-224, 242, 256, 262-266 /home/admin/.local/lib/python3.8/site-packages/matplotlib/table.py 335 92 73% 101, 118, 143, 161, 188-189, 202, 207, 211-217, 302, 354-355, 365, 402, 404, 407, 431-444, 448, 452-457, 500-508, 512-516, 520-521, 526, 532, 543-545, 568-570, 585, 598-605, 614, 616, 618, 620, 627, 629, 631, 633, 650, 738, 744-746, 752, 757, 760, 774-777, 780-781, 787-790, 796, 821-827 /home/admin/.local/lib/python3.8/site-packages/matplotlib/texmanager.py 151 103 32% 48-49, 105-106, 110-115, 120-130, 134-171, 178-187, 194-195, 200, 205-207, 246-249, 253-275, 284-305, 314-329, 334-344, 357-361, 366-373 /home/admin/.local/lib/python3.8/site-packages/matplotlib/text.py 812 357 56% 41-49, 67-90, 130, 228, 233, 236-239, 246-268, 279, 292-313, 318, 390, 479, 486-489, 492, 494, 496, 498, 531-552, 559, 571-582, 589, 633-652, 659-675, 681-685, 697-736, 761-762, 768-769, 785, 789-790, 796, 814, 824, 834, 844, 864, 874, 884, 916, 941, 952, 954, 977-983, 1026-1028, 1065-1066, 1080-1081, 1095-1096, 1126, 1148, 1181-1182, 1234, 1246-1247, 1297-1299, 1301, 1303, 1332, 1371, 1395-1397, 1407-1408, 1412, 1415-1419, 1436-1454, 1470-1478, 1483-1488, 1490-1496, 1498-1499, 1501, 1503, 1505, 1508, 1510-1513, 1517, 1524, 1526, 1537-1538, 1545-1546, 1548, 1550-1552, 1557, 1562, 1569, 1606-1607, 1612, 1616-1617, 1639-1654, 1673, 1856, 1872-1880, 1888-1895, 1908, 1918, 1922, 1938, 1946, 1960-2016, 2024, 2030-2032, 2041-2058, 2062-2064 /home/admin/.local/lib/python3.8/site-packages/matplotlib/textpath.py 192 152 21% 34-37, 40, 46, 49-70, 112-134, 142-164, 173-215, 221-223, 230-280, 287-298, 354-369, 373-374, 378, 385-386, 393, 402-408 /home/admin/.local/lib/python3.8/site-packages/matplotlib/ticker.py 1228 803 35% 165-167, 170, 173, 176, 179, 182, 186, 196-197, 213, 225, 233, 269, 283-284, 294-297, 300, 303, 316-317, 325, 328, 331, 346, 354, 365, 374, 452, 485-486, 498, 512, 531, 555-556, 559-564, 573, 588, 620-622, 626-650, 654-666, 676-692, 712-713, 736, 749-750, 753-754, 761-762, 764, 768, 772, 774, 782, 789, 792, 795, 805, 809, 874-883, 893, 902, 914, 925, 933-984, 987-993, 997-1016, 1019-1020, 1024, 1028-1046, 1054-1062, 1072, 1076-1110, 1120-1125, 1167-1172, 1184, 1193, 1205, 1218, 1221-1260, 1263-1286, 1289-1292, 1295-1313, 1318-1322, 1388-1392, 1395, 1398-1401, 1406, 1409-1412, 1417-1421, 1438-1473, 1503-1506, 1510-1512, 1536-1556, 1559, 1570-1579, 1583, 1616, 1623, 1631, 1645, 1685-1686, 1690-1693, 1697-1698, 1701, 1723-1724, 1741-1747, 1791-1795, 1800, 1804, 1808-1811, 1815-1816, 1819-1830, 1835-1850, 1860, 1864-1865, 1869-1870, 1873-1879, 1886-1896, 1905, 1928, 1935-1937, 1946, 1953, 2013, 2017, 2020, 2022, 2053, 2065, 2072, 2086-2088, 2097-2098, 2104-2109, 2117, 2140-2141, 2148, 2150, 2152, 2157-2158, 2164, 2171-2176, 2181-2189, 2198, 2209, 2220-2225, 2234-2239, 2244, 2248, 2284-2292, 2296-2303, 2308, 2315, 2321-2334, 2340-2341, 2344-2429, 2433-2441, 2444-2462, 2489-2502, 2506-2509, 2514-2515, 2518-2604, 2608-2620, 2659-2664, 2669-2676, 2679-2685, 2690-2732, 2752-2753, 2757-2759, 2763, 2767, 2771-2844, 2847-2880, 2895-2896, 2916, 2920-2957, 2960 /home/admin/.local/lib/python3.8/site-packages/matplotlib/transforms.py 1162 372 68% 127-129, 146-155, 219, 238-244, 251, 336, 341, 391, 397-398, 404-405, 411, 421-431, 437-438, 444-445, 451, 462-472, 512, 517, 530-531, 545, 547, 551, 563-566, 574-577, 589-593, 604, 612-617, 635-636, 643-647, 653, 666-670, 764, 774-782, 828, 832, 837, 840, 878, 908-909, 928-929, 952, 980-981, 1000-1004, 1054-1055, 1067, 1095, 1098, 1125, 1129, 1140-1145, 1149, 1153, 1183-1192, 1198-1204, 1207-1212, 1219-1222, 1226-1228, 1235-1238, 1242-1244, 1251-1254, 1258-1260, 1267-1270, 1274-1276, 1401, 1415, 1452, 1458-1462, 1467, 1473, 1502-1503, 1508, 1536, 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/home/admin/.local/lib/python3.8/site-packages/matplotlib/tri/_trifinder.py 26 15 42% 20-21, 38-42, 55-63, 79, 86, 93 /home/admin/.local/lib/python3.8/site-packages/matplotlib/tri/_triinterpolate.py 535 450 16% 34-56, 157-207, 228, 258-261, 265, 270, 275-283, 381-418, 421, 426, 431-446, 466-476, 497-515, 539-543, 561-571, 689-706, 727-762, 783-787, 803-828, 846-879, 896-909, 935-978, 996-1004, 1007, 1013-1017, 1043-1058, 1065-1068, 1084-1105, 1112-1127, 1135-1153, 1163-1164, 1172-1210, 1224-1227, 1234-1235, 1243-1248, 1254-1259, 1265-1269, 1272, 1277-1280, 1312-1350, 1406-1426, 1440-1472, 1479, 1486, 1494-1514, 1531-1544, 1556-1574 /home/admin/.local/lib/python3.8/site-packages/matplotlib/tri/_tripcolor.py 62 56 10% 61-154 /home/admin/.local/lib/python3.8/site-packages/matplotlib/tri/_triplot.py 28 23 18% 38-86 /home/admin/.local/lib/python3.8/site-packages/matplotlib/tri/_trirefine.py 93 81 13% 43-44, 62, 94-131, 157-169, 191-307 /home/admin/.local/lib/python3.8/site-packages/matplotlib/tri/_tritools.py 77 65 16% 29-30, 44-47, 79-115, 165-190, 220-238, 260-263 /home/admin/.local/lib/python3.8/site-packages/matplotlib/units.py 61 10 84% 66, 117, 122, 132, 150-156, 176 /home/admin/.local/lib/python3.8/site-packages/matplotlib/widgets.py 1888 1585 16% 43-45, 49-51, 55, 59, 63, 76, 80, 91, 107, 133-135, 144-145, 149-150, 194-215, 218-221, 224-228, 231-241, 249, 253, 265-301, 305-315, 326, 330-331, 430-503, 507-527, 531-552, 556-561, 571-586, 603, 703-803, 814-824, 828-835, 839-846, 850, 854-865, 869-906, 910-920, 930, 940, 950-969, 986, 990-991, 1053-1107, 1111-1118, 1121-1143, 1156-1159, 1173-1176, 1190-1196, 1214-1246, 1256-1260, 1268, 1277, 1281, 1287-1305, 1311-1335, 1383-1420, 1424, 1435-1458, 1461-1465, 1468-1501, 1504-1511, 1515-1532, 1536-1548, 1551-1563, 1566, 1569-1575, 1583, 1592, 1596, 1659-1721, 1725-1731, 1734-1753, 1766-1769, 1783-1791, 1797, 1801-1808, 1816-1841, 1849, 1853, 1859-1870, 1888-1919, 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/home/admin/.local/lib/python3.8/site-packages/numpy/lib/mixins.py 59 12 80% 10-13, 19-21, 29-31, 39, 54 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/nanfunctions.py 279 219 22% 61-66, 96-110, 135-139, 164-180, 209-221, 225, 313-336, 340, 428-451, 455, 494-500, 504, 544-550, 554, 647-648, 652, 717-718, 722, 787-788, 792, 854-855, 859, 937-957, 965-974, 984-1000, 1010-1020, 1025, 1113-1124, 1129, 1245-1249, 1255, 1358-1362, 1371-1381, 1391-1405, 1413-1418, 1424, 1518-1567, 1572, 1670-1676 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/npyio.py 854 664 22% 34-37, 83, 86-89, 97, 108-112, 189-202, 205, 208, 215-221, 224, 228, 231, 242-260, 269-273, 277-281, 408, 414-415, 431-434, 438, 444-450, 455, 519-529, 534-535, 618, 622-623, 689, 695-726, 733-736, 740, 742, 744, 747-758, 768, 904, 927-944, 950, 954, 990, 992, 994-995, 1005-1006, 1016, 1028, 1039-1054, 1065, 1072-1075, 1081, 1085-1086, 1091, 1100-1104, 1113, 1122-1138, 1152-1156, 1162, 1167, 1176-1179, 1182-1186, 1199, 1326-1447, 1510-1541, 1557, 1751-2284, 2311-2317, 2339-2345, 2369-2377, 2403-2415 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/polynomial.py 438 319 27% 41, 138-165, 231, 238, 248, 257, 265, 342-366, 370, 432-446, 450, 620-689, 693, 764-772, 776, 830-844, 884-898, 956-961, 965, 1020-1038, 1042-1065, 1180, 1185-1186, 1191, 1197, 1202, 1208, 1220-1231, 1233, 1236, 1239, 1246-1249, 1252-1254, 1257, 1260-1314, 1317, 1320, 1323, 1326-1330, 1333-1337, 1340-1341, 1344-1345, 1348-1353, 1356-1357, 1360-1361, 1364-1368, 1373-1377, 1382-1386, 1389-1391, 1395-1400, 1403-1411, 1414, 1427, 1440 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/scimath.py 70 38 46% 106-110, 135-138, 162-165, 189-192, 196, 239-240, 287-288, 337-338, 342, 376-378, 425-426, 430, 473-475, 519-520, 565-566, 616-617 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/shape_base.py 263 148 44% 31-49, 53, 161-170, 174, 251-260, 264, 359-414, 418, 487-505, 509, 588-602, 648, 718, 722, 727-732, 778, 868-872, 878, 937-942, 989-991, 1034-1036, 1043-1048, 1055-1060, 1064, 1136-1164, 1252 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/stride_tricks.py 91 46 49% 21-22, 29-34, 97-114, 119, 301-335, 343, 345, 363, 411, 426-427, 470-471 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/twodim_base.py 177 100 44% 34-40, 95-98, 153, 158, 211, 216, 220, 295, 300-303, 346-363, 367, 412-424, 433, 469-472, 498-501, 505, 582-597, 602-615, 741-752, 821-823, 904-906, 911, 938-940, 1023-1025, 1057-1059 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/type_check.py 138 78 43% 70-77, 81, 112-114, 159-160, 202-203, 240-244, 339-340, 390, 395-397, 401, 498-521, 526, 574-583, 588-590, 618, 696, 713, 753-769 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/ufunclike.py 57 30 47% 24-36, 50-53, 65, 70, 117-124, 188-196, 260-268 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/utils.py 454 363 20% 38-46, 83-84, 96-97, 116, 123-124, 221, 260-277, 329-379, 391-407, 415-431, 452-482, 537-628, 672-677, 737-812, 835-947, 950-956, 1028-1043, 1056-1070 /home/admin/.local/lib/python3.8/site-packages/numpy/linalg/__init__.py 6 0 100% /home/admin/.local/lib/python3.8/site-packages/numpy/linalg/linalg.py 678 507 25% 88, 91, 94, 97, 100, 129, 133, 142, 146-149, 153-154, 165-174, 177-185, 188-190, 196, 203, 208, 212, 230, 235, 286-306, 310, 378-395, 399, 456-467, 550, 618-666, 756-764, 770, 890-982, 1075, 1081, 1159-1176, 1179-1181, 1314-1333, 1453-1473, 1624-1639, 1652-1657, 1666-1674, 1678, 1761-1797, 1801, 1898-1906, 1912, 1995-2011, 2092-2101, 2153-2160, 2166, 2266-2328, 2354-2356, 2360, 2514-2611, 2617-2618, 2707-2739, 2750-2760, 2780-2801, 2806-2812 /home/admin/.local/lib/python3.8/site-packages/numpy/ma/__init__.py 10 0 100% /home/admin/.local/lib/python3.8/site-packages/numpy/ma/core.py 2405 1672 30% 102-113, 122, 124, 204-212, 217-222, 270-277, 282-291, 342, 393, 414-425, 441, 443-451, 456-457, 463-468, 532-534, 543-547, 575-579, 628, 633-636, 646-663, 713, 768-776, 804, 812-813, 831-832, 848-853, 868-869, 884-885, 895, 928-969, 1011-1050, 1057-1080, 1087-1105, 1112-1116, 1155-1192, 1284-1291, 1295-1297, 1305, 1534-1537, 1547, 1621-1636, 1683, 1726-1753, 1788-1809, 1814-1817, 1924-1943, 1969, 1995, 2021, 2047, 2073, 2101-2103, 2139-2143, 2179-2183, 2244-2251, 2323-2331, 2370, 2400, 2407, 2414, 2421, 2424, 2439-2447, 2489-2495, 2525-2550, 2581-2590, 2647-2653, 2656, 2659-2670, 2674-2676, 2696-2703, 2834, 2840, 2845-2847, 2857-2861, 2869-2871, 2874-2875, 2879-2882, 2887, 2889, 2895-2896, 2900-2909, 2915-2932, 2938, 2943, 2956, 3012, 3033, 3037-3040, 3047, 3054-3058, 3062, 3065, 3074-3121, 3180-3183, 3190-3194, 3204-3210, 3236-3251, 3261-3267, 3276, 3283-3286, 3291, 3301-3330, 3347-3402, 3411-3419, 3427-3431, 3438-3500, 3516, 3532-3535, 3539, 3554-3555, 3570-3571, 3576, 3591-3594, 3599, 3635, 3660, 3664-3665, 3697-3706, 3710-3725, 3778, 3781, 3786, 3789-3790, 3794-3809, 3833-3836, 3898-3908, 3915-3939, 3942, 3949-4026, 4031-4040, 4053-4104, 4117, 4130, 4137-4139, 4148, 4155-4157, 4164, 4168-4170, 4179, 4186-4188, 4195-4197, 4204, 4211-4213, 4220, 4227-4229, 4236, 4243-4253, 4260-4269, 4276-4285, 4292-4303, 4310-4321, 4328-4339, 4346-4360, 4367-4373, 4380-4385, 4407-4409, 4434-4436, 4497-4538, 4588, 4652-4658, 4673-4676, 4739-4761, 4785-4787, 4815, 4841-4855, 4871-4885, 4983, 4990-4997, 5037, 5078-5099, 5133-5140, 5160-5181, 5206-5213, 5241-5260, 5293-5300, 5317-5363, 5380-5388, 5401-5413, 5479-5493, 5535-5538, 5572-5575, 5648-5658, 5692-5724, 5788-5792, 5826-5859, 5936-5947, 5950-5953, 5956-5959, 5964-5985, 6024-6046, 6057-6061, 6101, 6116, 6163-6175, 6184-6186, 6200-6203, 6209, 6214-6221, 6229-6231, 6241-6257, 6262, 6269-6284, 6287-6291, 6294-6302, 6308-6316, 6319, 6343, 6356-6366, 6462-6469, 6472, 6475, 6478, 6481-6485, 6491-6500, 6505, 6510, 6524, 6527, 6530, 6536-6542, 6559, 6614-6616, 6640-6647, 6651-6679, 6683-6695, 6698-6705, 6710-6717, 6723-6729, 6767-6768, 6775, 6812-6813, 6833-6865, 6872-6882, 6898-6908, 6923, 6967-6983, 6998-7001, 7016-7022, 7037-7043, 7059-7062, 7083-7101, 7136-7139, 7156-7158, 7216-7222, 7230, 7237, 7243, 7308-7340, 7388-7415, 7442-7448, 7527-7540, 7605-7625, 7636-7642, 7650-7660, 7670-7682, 7710, 7738, 7783-7796, 7871-7904, 8001, 8011, 8017, 8082, 8116-8127, 8186 /home/admin/.local/lib/python3.8/site-packages/numpy/ma/extras.py 560 464 17% 48, 101-102, 152-154, 207-209, 259, 262, 272-280, 306-318, 333-341, 364-369, 376-451, 459-477, 587-631, 700-714, 719-799, 823-842, 894-896, 911-914, 928-931, 975-981, 1024-1030, 1049-1063, 1078-1087, 1113-1119, 1133-1146, 1168-1188, 1209-1210, 1225, 1248-1253, 1267-1301, 1358-1374, 1425-1461, 1486-1487, 1491-1494, 1569-1576, 1621-1626, 1674-1684, 1744-1760, 1769-1789, 1825-1828, 1864-1867, 1880-1884, 1894-1921 /home/admin/.local/lib/python3.8/site-packages/numpy/matrixlib/__init__.py 5 0 100% /home/admin/.local/lib/python3.8/site-packages/numpy/matrixlib/defmatrix.py 238 158 34% 15-33, 69, 123-128, 131-139, 142, 149, 151, 153, 157, 160, 173-187, 190-213, 216-221, 224, 227-228, 231, 234-235, 238, 244-251, 257-260, 284, 319, 372, 411, 445, 479, 513, 546, 569, 609, 644, 683, 718, 757, 790, 830-835, 865, 894, 933, 966, 998-1001, 1011-1032, 1089-1111 /home/admin/.local/lib/python3.8/site-packages/numpy/polynomial/__init__.py 18 7 61% 171-180 /home/admin/.local/lib/python3.8/site-packages/numpy/polynomial/_polybase.py 419 296 29% 105, 110, 115, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 193-198, 216, 234, 252, 280-288, 291-304, 307-311, 314-324, 327-329, 337-367, 375-380, 389-394, 398-403, 409, 413-462, 469-473, 476, 481-483, 486, 489, 494, 497, 500-505, 508-513, 516-521, 527-532, 535-538, 541-544, 547-556, 559-561, 564-568, 571-575, 578-582, 586, 591, 594-597, 600-603, 606-614, 617-622, 625, 640, 653, 678, 700-701, 723-730, 761-767, 796, 823-829, 849-851, 865-866, 894-898, 971-986, 1014-1027, 1054-1060, 1091-1099, 1137-1141 /home/admin/.local/lib/python3.8/site-packages/numpy/polynomial/chebyshev.py 357 294 18% 152-155, 177-180, 207, 243-274, 302-306, 333-340, 389-394, 441-455, 508-511, 566, 608, 652, 686-698, 742-747, 797-814, 855-872, 935-964, 1052-1091, 1153-1175, 1224, 1277, 1328, 1384, 1422-1437, 1490, 1544, 1670, 1700-1715, 1766-1776, 1827-1843, 1881-1888, 1915-1916, 1946-1953, 1979-1986, 2065-2069 /home/admin/.local/lib/python3.8/site-packages/numpy/polynomial/hermite.py 267 214 20% 134-139, 180-197, 251-254, 310, 350, 390, 432-443, 485-509, 557, 594, 652-677, 763-799, 871-895, 944, 997, 1048, 1104, 1151-1165, 1218, 1272, 1403, 1433-1448, 1502-1512, 1544-1555, 1594-1622, 1649-1650 /home/admin/.local/lib/python3.8/site-packages/numpy/polynomial/hermite_e.py 264 211 20% 135-140, 181-197, 250-253, 309, 349, 389, 427-438, 480-504, 550, 587, 645-670, 756-792, 864-887, 936, 989, 1040, 1096, 1143-1156, 1209, 1263, 1395, 1426-1441, 1495-1505, 1537-1548, 1587-1615, 1641-1642 /home/admin/.local/lib/python3.8/site-packages/numpy/polynomial/laguerre.py 252 200 21% 134-138, 179-193, 245-248, 304, 345, 385, 427-439, 481-505, 551, 588, 646-674, 761-798, 870-893, 942, 995, 1046, 1102, 1149-1162, 1215, 1269, 1400, 1429-1444, 1498-1508, 1547-1572, 1598-1599 /home/admin/.local/lib/python3.8/site-packages/numpy/polynomial/legendre.py 261 209 20% 140-145, 193-207, 261-264, 319, 361, 405, 447-461, 505-529, 578, 609, 672-701, 789-829, 891-914, 963, 1016, 1067, 1123, 1161-1176, 1229, 1283, 1411, 1441-1455, 1506-1516, 1555-1584, 1611-1612 /home/admin/.local/lib/python3.8/site-packages/numpy/polynomial/polynomial.py 221 166 25% 145-148, 212, 248, 285, 317-325, 361-363, 400-421, 460, 515-542, 623-661, 745-757, 835-845, 895, 948, 999, 1055, 1096-1109, 1157, 1211, 1361, 1390-1401, 1454-1464, 1514, 1518, 1522-1529 /home/admin/.local/lib/python3.8/site-packages/numpy/polynomial/polyutils.py 229 204 11% 71-77, 130-153, 200-208, 248-254, 297-301, 366-368, 372-374, 422-443, 452-453, 469-483, 497-513, 527-529, 547-565, 571-578, 584-592, 606-680, 697-713, 732-750 /home/admin/.local/lib/python3.8/site-packages/numpy/random/__init__.py 17 1 94% 210 /home/admin/.local/lib/python3.8/site-packages/numpy/random/_pickle.py 22 12 45% 31-37, 54-60, 77-83 /home/admin/.local/lib/python3.8/site-packages/numpy/testing/__init__.py 8 0 100% /home/admin/.local/lib/python3.8/site-packages/numpy/testing/_private/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/numpy/testing/_private/decorators.py 74 61 18% 61-65, 100-105, 143-186, 226-251, 282-304, 323-329 /home/admin/.local/lib/python3.8/site-packages/numpy/testing/_private/nosetester.py 174 157 10% 36-58, 96-109, 164-193, 212-230, 233-250, 259-260, 276-324, 397-463, 523-536, 540-544 /home/admin/.local/lib/python3.8/site-packages/numpy/testing/_private/utils.py 873 732 16% 59-75, 89-95, 109-113, 127-132, 146-151, 156-186, 196-208, 220-244, 249-272, 325-432, 463-473, 545-599, 660-698, 716, 741-745, 749, 753, 758-763, 778-781, 784-787, 790, 795-796, 806-852, 933-934, 1015-1046, 1127-1128, 1135, 1165-1206, 1231-1252, 1289-1290, 1300, 1329-1330, 1353-1354, 1380-1401, 1437-1447, 1455-1473, 1583-1594, 1639-1646, 1681-1709, 1717-1724, 1730-1738, 1743-1749, 1797-1803, 1808-1814, 1844-1850, 1878-1918, 1935-1939, 1956-1961, 2009-2011, 2014-2019, 2022-2027, 2105-2112, 2115-2124, 2127-2149, 2171, 2201, 2205-2234, 2237-2242, 2246-2293, 2300-2305, 2310-2342, 2386-2392, 2403-2409, 2414-2431, 2439-2460, 2465-2476, 2481-2500, 2509-2520 /home/admin/.local/lib/python3.8/site-packages/numpy/version.py 9 0 100% /home/admin/.local/lib/python3.8/site-packages/oauth2client/__init__.py 7 0 100% /home/admin/.local/lib/python3.8/site-packages/oauth2client/_helpers.py 98 60 39% 119-133, 139-140, 156-159, 174-179, 194-202, 222-227, 243-246, 250-255, 272-274, 278, 302-307, 323-328, 333-334, 339-341 /home/admin/.local/lib/python3.8/site-packages/oauth2client/_openssl_crypt.py 40 38 5% 18-135 /home/admin/.local/lib/python3.8/site-packages/oauth2client/_pkce.py 14 8 43% 41-49, 66-67 /home/admin/.local/lib/python3.8/site-packages/oauth2client/_pure_python_crypt.py 63 39 38% 55-62, 73, 88-92, 113-125, 136, 147-148, 166-184 /home/admin/.local/lib/python3.8/site-packages/oauth2client/_pycrypto_crypt.py 38 22 42% 34, 48-49, 64-75, 87, 98-99, 116-124 /home/admin/.local/lib/python3.8/site-packages/oauth2client/client.py 708 520 27% 147-148, 184-187, 213, 222, 231, 239, 255-274, 283, 298-314, 328, 351, 358-359, 367-368, 378, 388, 395, 405-409, 419-423, 434-438, 489-506, 535-536, 545, 554, 562, 580-581, 595-596, 610-633, 641-652, 660-664, 677, 689-697, 701, 705-707, 711-712, 716-722, 726-733, 748-763, 774-819, 827, 841-863, 871, 885-902, 944, 956-960, 971, 980, 996-1005, 1014-1030, 1039-1045, 1101, 1111, 1118, 1124-1147, 1152, 1171-1174, 1187-1190, 1207-1230, 1249-1261, 1271, 1287-1298, 1310-1315, 1331-1340, 1344-1351, 1362-1379, 1385-1415, 1420, 1427, 1433-1435, 1439-1441, 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/home/admin/.local/lib/python3.8/site-packages/oauth2client/transport.py 89 66 26% 39, 42, 45, 58, 73, 86, 101-107, 123-134, 150-201, 217-251, 279-280 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/__init__.py 16 0 100% /home/admin/.local/lib/python3.8/site-packages/opt_einsum/_version.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/opt_einsum/backends/__init__.py 6 0 100% /home/admin/.local/lib/python3.8/site-packages/opt_einsum/backends/cupy.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/opt_einsum/backends/dispatch.py 55 33 40% 37-44, 64-69, 79-88, 97-106, 132, 139, 145 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/backends/jax.py 13 8 38% 17-27 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/backends/object_arrays.py 24 20 17% 33-60 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/backends/tensorflow.py 63 50 21% 17-34, 41-56, 65-76, 83-94, 103-106, 113, 120-122, 126-128 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/backends/theano.py 25 18 28% 16-24, 30-42, 47-53 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/backends/torch.py 61 47 23% 22-28, 34, 42-45, 51-95, 100-105, 127-128 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/blas.py 77 72 6% 55-120, 168-243 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/contract.py 315 279 11% 30-44, 48-71, 75-87, 196-330, 337-353, 358, 365-366, 373-374, 470-507, 511, 518-527, 536-600, 611-626, 634-647, 657-667, 674-678, 681-686, 691-693, 710-719, 735-771, 774-778, 781-787, 797, 861-882 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/helpers.py 70 58 17% 42-50, 76-79, 125-134, 168-173, 228-283 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/parser.py 124 106 15% 32, 46, 64-66, 77-84, 97-99, 113-119, 137-138, 154, 183-186, 199-206, 212-243, 272-356 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/path_random.py 165 131 21% 18-25, 87-101, 107, 111, 116-139, 144-155, 158-160, 163, 166-204, 208-209, 247-283, 289-304, 310-319, 355-359, 367-370, 376-378, 384-385 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/paths.py 440 368 16% 51-56, 60, 71-77, 88-97, 130-138, 146-149, 183-236, 243, 247, 257, 267, 274, 312-319, 323, 352-448, 452-453, 462-472, 476-482, 486-496, 502-505, 514-615, 657-661, 700-719, 749-767, 778, 786-794, 809-816, 825-832, 842, 853-865, 903-916, 955-1053, 1057-1058, 1076-1077, 1092-1095, 1117, 1125-1129 /home/admin/.local/lib/python3.8/site-packages/opt_einsum/sharing.py 96 58 40% 26, 32, 36, 40-43, 68-74, 81, 88-90, 98-103, 112-119, 130-139, 150-168, 185-190, 196-201 /home/admin/.local/lib/python3.8/site-packages/packaging/__init__.py 8 0 100% /home/admin/.local/lib/python3.8/site-packages/packaging/_structures.py 36 16 56% 8, 11, 14, 17, 20, 23, 26, 29, 37, 40, 43, 46, 49, 52, 55, 58 /home/admin/.local/lib/python3.8/site-packages/packaging/version.py 163 65 60% 69, 76, 81-84, 87-90, 93-96, 99-102, 105-108, 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/home/admin/.local/lib/python3.8/site-packages/pandas/_libs/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/_libs/tslibs/__init__.py 13 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/_libs/window/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/_testing/__init__.py 396 256 35% 121-125, 253-255, 265, 276, 292-317, 325-330, 338, 343, 350-351, 358-359, 363-367, 371-385, 389-392, 396-399, 403, 407-410, 416-418, 424, 428-429, 433-437, 441-450, 462-468, 473-477, 481, 485, 489-492, 496-497, 501-503, 509-511, 515, 519, 524-525, 529-530, 534-543, 547, 551-552, 585-664, 739-771, 775-798, 802-805, 818, 822, 830, 834, 840, 859-872, 891-892, 909-911, 934-942, 959-967, 975, 979, 983, 987, 991, 995, 1005-1047 /home/admin/.local/lib/python3.8/site-packages/pandas/_testing/_io.py 130 98 25% 30, 76-79, 102-111, 209-248, 267-278, 303-308, 329-337, 358-366, 388-418, 426-435 /home/admin/.local/lib/python3.8/site-packages/pandas/_testing/_random.py 9 3 67% 14-19, 29 /home/admin/.local/lib/python3.8/site-packages/pandas/_testing/_warnings.py 61 48 21% 86-102, 112-115, 126-150, 163-188, 196-199, 205-216 /home/admin/.local/lib/python3.8/site-packages/pandas/_testing/asserters.py 402 358 11% 92-142, 163-170, 176-177, 234-343, 352-377, 394-416, 420-435, 440-443, 471-504, 525-535, 539-542, 548-554, 560-564, 570-599, 633-679, 732-782, 877-1032, 1152-1224, 1253-1280, 1292-1313, 1317-1318, 1330-1336, 1350, 1358-1364, 1373-1378 /home/admin/.local/lib/python3.8/site-packages/pandas/_testing/compat.py 10 6 40% 10-14, 22-24 /home/admin/.local/lib/python3.8/site-packages/pandas/_testing/contexts.py 86 61 29% 46-47, 72-89, 114-134, 145-150, 173-184, 189-202, 206-213 /home/admin/.local/lib/python3.8/site-packages/pandas/_typing.py 149 33 78% 34-84, 204, 209, 213, 217, 223, 229, 233, 238, 243, 249, 253, 257, 262, 314 /home/admin/.local/lib/python3.8/site-packages/pandas/_version.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/api/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/api/extensions/__init__.py 6 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/api/indexers/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/api/interchange/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/api/types/__init__.py 5 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/arrays/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/compat/__init__.py 33 14 58% 41-44, 56, 68, 80, 92, 104, 118, 131, 148-154 /home/admin/.local/lib/python3.8/site-packages/pandas/compat/_constants.py 9 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/compat/_optional.py 49 29 41% 71-88, 145, 149-173 /home/admin/.local/lib/python3.8/site-packages/pandas/compat/compressors.py 27 12 56% 16-17, 30-41, 54, 69 /home/admin/.local/lib/python3.8/site-packages/pandas/compat/numpy/__init__.py 18 2 89% 19, 25 /home/admin/.local/lib/python3.8/site-packages/pandas/compat/numpy/function.py 161 57 65% 68-86, 99-103, 113-115, 125-127, 158-164, 175, 180, 192-201, 221-226, 325-330, 345-351, 365-371, 388-391 /home/admin/.local/lib/python3.8/site-packages/pandas/compat/pickle_compat.py 93 66 29% 27-57, 147-149, 157-174, 181-190, 195-196, 209-220, 233-234, 244-249 /home/admin/.local/lib/python3.8/site-packages/pandas/compat/pyarrow.py 17 6 65% 17-22 /home/admin/.local/lib/python3.8/site-packages/pandas/core/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/_numba/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/_numba/executor.py 18 10 44% 41-59 /home/admin/.local/lib/python3.8/site-packages/pandas/core/accessor.py 84 27 68% 28, 34, 44-46, 55, 58, 61, 96, 99, 112, 224-230, 306-319, 324-326, 331-333, 338-340 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11% 49-90, 121-157, 167-207 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/arrow/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/arrow/_arrow_utils.py 24 16 33% 17-20, 43-61 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/arrow/array.py 1003 805 20% 105-109, 117-120, 142-147, 154-159, 168-181, 234-245, 252-285, 294-348, 374-417, 423-429, 433, 437, 440, 443, 446, 449, 454-456, 459-460, 463-487, 490-536, 539, 542, 545-549, 556, 563, 573, 577-585, 589, 597, 655, 713, 723-732, 735-748, 751, 754, 766, 776, 785-834, 838-844, 860-861, 868-895, 898, 927, 936-944, 1006-1042, 1051-1081, 1091-1104, 1123-1151, 1168-1175, 1207-1225, 1251-1345, 1369-1424, 1438-1491, 1508-1530, 1548-1571, 1575-1588, 1613-1632, 1658-1685, 1689, 1698-1700, 1708-1718, 1723-1733, 1736-1739, 1742-1745, 1756-1764, 1767-1774, 1779-1781, 1786-1788, 1791-1804, 1807-1824, 1827, 1830-1832, 1835-1837, 1842-1846, 1853-1857, 1860, 1863, 1866, 1869, 1872, 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1487, 1501-1505, 1519-1523, 1549-1560, 1564-1570, 1573-1580, 1637-1638, 1799-1866, 1870, 1877, 1881-1888, 1903-1928, 1937, 1943, 1950, 1953-1967, 1974-1980, 1985-1993, 1997-2017, 2026, 2035, 2044, 2051, 2056, 2062, 2077-2091, 2100-2109, 2117-2147, 2152, 2157, 2178-2184, 2210-2221, 2241-2249, 2265-2267 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/datetimes.py 617 485 21% 90-91, 109-112, 117-148, 198, 263-265, 275-287, 291, 309-370, 389-502, 508-514, 517, 520-522, 529-531, 556, 569, 574, 584, 591, 595, 601-605, 615-634, 641-701, 709-713, 722-729, 733-748, 756-782, 794-797, 863-873, 1021-1058, 1071, 1111-1118, 1164-1190, 1244-1250, 1301-1307, 1319-1321, 1330, 1343-1345, 1381-1390, 1911-1917, 1971-1979, 2022-2134, 2172-2202, 2229-2256, 2281-2290, 2315-2344, 2370-2397, 2422-2440, 2446-2453, 2478-2486, 2521-2595 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/floating.py 34 3 91% 36, 40, 51 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/integer.py 70 9 87% 36, 40, 50-57 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/interval.py 638 486 24% 104, 220, 238-275, 288-293, 305-379, 389, 395-400, 458-460, 536-548, 608-631, 645-661, 674-677, 684, 688, 693, 699, 702, 706, 710, 715-731, 734-738, 742-817, 821, 825, 829, 833, 837, 841, 851-859, 864-878, 881-895, 926-935, 956-996, 999-1002, 1023-1033, 1043-1046, 1049, 1052-1077, 1133-1146, 1150-1168, 1171-1182, 1185-1205, 1225, 1233-1260, 1266-1270, 1273-1274, 1284-1286, 1293-1295, 1302, 1309-1313, 1372-1385, 1396, 1438-1444, 1466-1474, 1487-1498, 1504-1550, 1573-1577, 1582-1591, 1608-1613, 1616-1624, 1632-1635, 1683-1686, 1691-1720, 1724-1730, 1736-1748, 1753-1757, 1776-1796 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/masked.py 572 451 21% 88-90, 121-134, 140-141, 145, 149, 153, 158-167, 173-198, 204, 214-231, 234-248, 251-264, 267, 271, 275, 278-280, 283-285, 288-290, 294-296, 300, 326-330, 336, 339, 342, 345, 415-439, 443-446, 450, 454, 458, 461-504, 513, 521-592, 598-600, 609, 614-625, 628-730, 735-773, 782-821, 824, 828, 832, 840-842, 854-876, 881-898, 901-904, 914-915, 924-932, 939-971, 975, 994-1021, 1025-1037, 1050-1078, 1084-1097, 1100-1109, 1119-1135, 1147-1155, 1160-1167, 1174-1182, 1189-1197, 1202-1203, 1211-1212, 1281-1298, 1362-1380, 1385-1391 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/numeric.py 152 112 26% 41, 52, 56, 60, 64, 72-114, 118, 125-136, 145, 149-235, 248-263, 267-268, 274-280, 286-289 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/numpy_.py 186 130 30% 80-95, 101-120, 123, 130, 136, 143-188, 194-202, 205, 208-211, 214-218, 231-233, 243-245, 250-254, 259-263, 273-277, 287-291, 302-304, 315-319, 331-335, 347-351, 363-367, 378-382, 393-397, 408-420, 426, 429, 432, 435, 438-459, 466-472 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/period.py 420 311 26% 83-92, 105-107, 179, 215-236, 247-249, 259-274, 280, 297-298, 302-319, 331-338, 341, 344-346, 353, 361, 364-370, 376-397, 479, 497-536, 541, 589-609, 615-617, 626-643, 650-664, 672-677, 680-688, 708-712, 715-718, 731-740, 754-781, 803-818, 837-847, 912-943, 948, 953, 977-993, 1018-1033, 1037-1081, 1094-1128, 1132-1143 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/sparse/__init__.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/sparse/accessor.py 110 78 29% 20, 30-31, 34, 46-47, 50, 53-58, 102-108, 185-190, 216-218, 232-234, 265-287, 309-312, 334-355, 362-363, 367-386 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/sparse/array.py 786 648 18% 107-123, 155-158, 180-266, 275-287, 378-497, 506-510, 538-554, 557-579, 585-586, 590, 594, 604, 618, 622, 631, 635, 642-645, 649-651, 654, 658, 661-664, 668, 682, 696, 701-706, 746-772, 775-799, 809-820, 823-834, 838, 849-853, 868-893, 900, 907, 913-1001, 1004-1012, 1017-1030, 1035-1097, 1100-1120, 1128-1133, 1136-1137, 1143-1195, 1254-1274, 1316-1326, 1336, 1341-1344, 1351-1361, 1364-1367, 1374-1384, 1398-1405, 1419-1426, 1454-1470, 1490-1498, 1512-1521, 1538-1539, 1556-1557, 1572-1592, 1595-1618, 1621-1624, 1627-1630, 1639-1702, 1709-1739, 1742-1765, 1774-1782, 1785, 1788, 1791, 1794, 1800-1803, 1808, 1832-1870, 1875, 1880, 1885-1892 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/sparse/dtype.py 143 94 34% 39, 85-99, 104, 109-140, 156, 159-160, 178, 182, 186, 193, 197, 201, 205, 208, 219-221, 250-273, 297-307, 311-317, 357-370, 396-398, 403-426 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/string_.py 257 193 25% 58-65, 105, 110-120, 124, 154-165, 180-185, 193-215, 225-227, 315-320, 324-336, 340-365, 371, 375-377, 383-390, 393-396, 399-429, 435, 438-468, 473-476, 479-483, 486-490, 493-497, 500-503, 512-517, 520-547, 560-608 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/string_arrow.py 200 142 29% 53-55, 112-116, 128, 132-152, 158, 165, 168-170, 174-185, 188-201, 204-216, 231-283, 288-306, 309-310, 313-314, 325-331, 336-338, 343-345, 348-349, 352-353, 356-357, 360-361, 364-365, 368-369, 372-373, 376-377, 380-381, 384-385, 388, 391, 394-398, 401-405, 408-412 /home/admin/.local/lib/python3.8/site-packages/pandas/core/arrays/timedeltas.py 440 333 24% 78, 83-96, 142, 164-167, 186, 197-199, 207-214, 218-227, 242-271, 279-319, 325-331, 334, 338, 348-368, 371-384, 400-407, 419-426, 432-441, 447-449, 454-460, 466-467, 473-500, 509-550, 553-559, 567-581, 586-610, 615-631, 635-660, 664-678, 683-685, 690-692, 697-702, 707-712, 715-718, 721, 725, 784-785, 795, 826-853, 896-966, 985-1006, 1039-1042, 1046-1062 /home/admin/.local/lib/python3.8/site-packages/pandas/core/base.py 322 197 39% 75-82, 113, 120, 126-131, 138-144, 163, 172-178, 196-200, 204-207, 212, 217-230, 233-246, 261, 264, 283, 288, 299-300, 320, 324, 331, 348-350, 357, 364, 429, 526-561, 566, 608-610, 666-678, 722-724, 730-742, 763, 780-784, 799, 802, 818-823, 849-926, 1015, 1025-1031, 1068-1071, 1082, 1093-1095, 1106-1108, 1135-1144, 1164-1177, 1293, 1302, 1311-1323, 1331-1333, 1337, 1340-1350, 1357 /home/admin/.local/lib/python3.8/site-packages/pandas/core/common.py 195 126 35% 57, 77-81, 85-92, 126-138, 141-145, 164, 176, 183, 190, 197, 204, 211, 221, 226, 230-258, 276-287, 291-293, 301, 310, 322, 334, 342, 352-364, 379, 405-413, 418, 425, 453-478, 510-518, 527-533, 543-548, 563-568, 576, 626, 634, 653 /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/align.py 99 76 23% 32-35, 42-51, 57, 64, 71-80, 87-142, 149-165, 188-213 /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/api.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/check.py 8 1 88% 8 /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/common.py 29 23 21% 14-16, 24-48 /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/engines.py 50 23 54% 23, 37-42, 53-55, 63, 77-82, 88, 113-121, 134, 137 /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/eval.py 111 90 19% 27, 51-72, 88-89, 95-99, 119-120, 147-149, 153-167, 299-413 /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/expr.py 361 213 41% 65-66, 84-91, 114-117, 165-166, 262, 314, 397-401, 404-415, 418-421, 424, 428-451, 454-459, 462-482, 491, 504-532, 535-537, 540, 543-545, 548, 551, 554, 557, 560-561, 564-565, 571, 574-591, 595-605, 617-635, 638-655, 658-706, 709, 712-730, 733-735, 738-746, 768, 776, 804-809, 813, 816, 819, 822, 828, 835-837 /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/expressions.py 107 70 35% 24, 46, 58-61, 68-70, 75-89, 93-130, 171, 176-188, 196-199, 211-220, 235-240, 255-256, 267-268, 272-273, 281-283 /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/ops.py 293 182 38% 72-75, 81-87, 91, 94, 97, 100, 103-117, 129-135, 139, 143-152, 158, 162-167, 171, 175, 179, 183, 188, 191, 195, 200, 214-216, 219, 226-227, 232-234, 238-240, 244, 248, 252-257, 265-273, 281-289, 346-355, 359, 374-387, 405-408, 427-457, 464-490, 493-511, 515, 529-539, 565-571, 577-579, 582, 586-593, 598-599, 603-605, 608-609, 614-617, 620 /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/parsing.py 45 33 27% 35-67, 90-93, 125-130, 159-164, 181-195 /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/pytables.py 352 257 27% 49-50, 57-61, 64, 68-78, 83, 88-89, 92, 103-106, 109, 112-151, 155-159, 164, 172, 177, 182, 187, 191-192, 200-256, 259, 266-268, 272-278, 282, 285-310, 313-316, 321, 324, 329, 336, 342, 345-368, 373-374, 379-393, 401-404, 411-416, 419, 422-425, 430-444, 449-470, 473, 476, 497-503, 545-585, 588-590, 594-609, 616-619, 623-631, 636-641 /home/admin/.local/lib/python3.8/site-packages/pandas/core/computation/scope.py 125 84 33% 36-40, 49-53, 60, 76-82, 88-89, 118-120, 153-188, 191-193, 207, 226-246, 261-271, 285-294, 304-314, 330-338, 343, 356-357 /home/admin/.local/lib/python3.8/site-packages/pandas/core/config_init.py 197 20 90% 40-42, 54-56, 68-70, 290-292, 307-310, 345, 421-423, 641-643, 664-672 /home/admin/.local/lib/python3.8/site-packages/pandas/core/construction.py 218 142 35% 67-71, 290-379, 386, 393, 442-450, 453, 464-466, 469-471, 480-491, 520, 524, 530-532, 535-536, 539-542, 548-553, 557-559, 564, 572-576, 580-581, 596, 599, 622-633, 641, 656, 662-679, 696-699, 710, 734-767 /home/admin/.local/lib/python3.8/site-packages/pandas/core/dtypes/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/dtypes/api.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/dtypes/astype.py 114 92 19% 40, 50, 57, 83-140, 149-159, 177-193, 220-251, 266-306 /home/admin/.local/lib/python3.8/site-packages/pandas/core/dtypes/base.py 140 59 58% 33-36, 104, 124-133, 138, 141, 152, 164, 180, 189, 199, 210, 226-227, 275-284, 310-327, 338, 356, 380-384, 391, 404, 410-412, 416, 420, 472, 478, 482, 486, 492, 509, 517 /home/admin/.local/lib/python3.8/site-packages/pandas/core/dtypes/cast.py 756 615 19% 102-103, 134, 151, 172-179, 194-210, 222-236, 245-251, 256, 261, 269-317, 324, 331, 350-422, 437-445, 475-492, 512-527, 532, 537, 545-551, 553, 556, 609-611, 635-640, 649-652, 658, 662-739, 760-764, 779-781, 795-873, 888, 926-944, 972-978, 990-995, 1000-1007, 1051-1168, 1199, 1227-1254, 1273-1294, 1326-1348, 1369-1385, 1407-1410, 1416, 1421, 1426, 1447, 1454, 1460-1465, 1469, 1471, 1477-1479, 1487-1509, 1531-1560, 1566-1570, 1636-1707, 1723-1747, 1767-1910, 1919-1921 /home/admin/.local/lib/python3.8/site-packages/pandas/core/dtypes/common.py 323 197 39% 82-89, 105-109, 128-139, 186, 231-234, 265-272, 306, 341-348, 383, 413-419, 451-457, 489-495, 537-548, 579-587, 589, 595-598, 646, 760, 809, 864, 900-906, 944-953, 987, 1025, 1060-1070, 1112, 1115-1124, 1165, 1202, 1286, 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/home/admin/.local/lib/python3.8/site-packages/pandas/core/generic.py 2254 1609 29% 193-200, 279, 292-311, 331-333, 352, 357, 448-451, 457-467, 478, 488, 503-507, 514-515, 520-521, 538, 543-569, 573-579, 590-595, 601, 605, 612, 621, 644, 670, 708, 714-721, 729-731, 744-780, 848-850, 853-856, 962-963, 987-1042, 1055, 1068, 1081, 1216-1256, 1313-1324, 1331, 1414-1417, 1424-1438, 1442-1453, 1457-1462, 1466, 1507-1518, 1588-1589, 1593, 1597, 1629-1631, 1689, 1723-1735, 1775-1778, 1782-1792, 1825-1872, 1891, 1905, 1917-1918, 1922, 1927, 1987, 1997-2010, 2016, 2023-2024, 2035-2067, 2075-2076, 2084-2087, 2095-2100, 2237-2252, 2522-2532, 2678-2682, 2876-2878, 2953-2955, 3032-3034, 3113-3118, 3145, 3172, 3356-3459, 3515-3533, 3560, 3587, 3761-3772, 3798, 3817-3824, 3827, 3907-3909, 3922-3938, 3948-3952, 4064, 4067-4078, 4083-4131, 4134, 4142-4151, 4158-4159, 4172-4174, 4202-4249, 4255-4286, 4293-4294, 4353-4356, 4362, 4466-4474, 4488, 4502, 4516, 4529-4555, 4582-4642, 4657-4660, 4721-4734, 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3036-3093, 3144-3310, 3376-3394, 3451-3453, 3527-3546, 3564-3569, 3582-3587, 3602-3610, 3627-3635, 3686-3774, 3804-3820, 3844-3861, 3884-3902, 3939-3940, 3978-3983, 4000-4006, 4040-4104, 4202-4235, 4247-4258, 4282-4292 /home/admin/.local/lib/python3.8/site-packages/pandas/core/groupby/grouper.py 405 322 20% 54, 250-254, 265-278, 294-309, 332-395, 400-409, 414-420, 425-431, 436-442, 447-454, 458-465, 520-611, 614, 617, 621, 625-639, 646-654, 658, 663-667, 671, 679-686, 692-698, 702-720, 725-783, 787, 822-1019, 1023, 1027-1044 /home/admin/.local/lib/python3.8/site-packages/pandas/core/groupby/indexing.py 105 78 26% 24-28, 114-120, 126-149, 152-155, 158-169, 172-184, 187-226, 230-235, 239-244, 250, 283-284, 293, 300, 303 /home/admin/.local/lib/python3.8/site-packages/pandas/core/groupby/numba_.py 52 39 25% 45-56, 93-119, 153-179 /home/admin/.local/lib/python3.8/site-packages/pandas/core/groupby/ops.py 533 383 28% 99, 121-123, 156-179, 197-220, 234-265, 268-284, 287-296, 312-322, 337-381, 386-397, 408-419, 434-461, 475-497, 519-615, 631-657, 692-697, 701, 705, 708, 712, 725-727, 736-737, 742-748, 754-782, 787-792, 802-819, 824, 828, 832, 839-845, 850-855, 861, 869, 873-878, 883-884, 891-897, 902, 906-908, 912-917, 925-935, 953-959, 987-1001, 1007-1025, 1068-1074, 1081-1086, 1091, 1096-1100, 1111-1125, 1129-1137, 1141-1151, 1160, 1164-1167, 1171, 1175, 1179-1185, 1189-1196, 1211-1216, 1221, 1226, 1229-1239, 1243, 1246, 1252-1254, 1264-1266, 1272-1278 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexers/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexers/objects.py 130 95 27% 55-59, 70, 85-100, 119, 140-142, 153-213, 228, 268-282, 315-318, 336-375, 390 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexers/utils.py 148 122 18% 29-30, 54-57, 94-99, 114-118, 152-186, 226-234, 270-274, 278-279, 282-284, 300-331, 342-343, 358-370, 390-396, 403-414, 513-555 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/accessors.py 140 92 34% 43, 56-64, 67-80, 85-114, 117, 123-144, 163-170, 173-191, 194-210, 213, 216-229, 332, 336, 368, 438, 467, 475, 554-580 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/api.py 126 97 23% 94-95, 103-109, 138-157, 174-191, 210-308, 332-346, 362-364 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/base.py 2276 1712 25% 187-193, 259-267, 279-297, 366-372, 379-386, 393-400, 407-414, 433, 482, 488, 492-495, 499, 502, 505-513, 516, 518, 522, 528, 533-535, 541, 544, 548, 552-557, 572, 575, 580, 589-606, 609-611, 614-616, 622-625, 658, 671-681, 685, 701-706, 725-738, 756-758, 764-767, 774-776, 800-807, 818, 827-834, 840, 842, 844, 851, 865, 885, 888-919, 925-929, 951, 956-981, 1007-1038, 1080, 1082, 1095, 1109-1117, 1165-1170, 1202-1208, 1212, 1222, 1232-1243, 1252, 1259, 1266-1275, 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4818-4863, 4872-4885, 4892-4900, 4925, 4930-4935, 4971, 4984, 4992-4999, 5006-5010, 5014-5018, 5053-5058, 5066, 5081-5091, 5099-5101, 5107, 5147-5148, 5157, 5177-5203, 5209-5210, 5222-5228, 5242-5258, 5264-5268, 5283-5312, 5373-5399, 5412, 5479-5496, 5531-5541, 5606-5624, 5631, 5689, 5731, 5734-5737, 5744, 5803-5837, 5858-5861, 5867-5894, 5917-5941, 5947, 5953, 5959, 5988-5999, 6009, 6020-6057, 6065-6081, 6089-6099, 6105-6111, 6130-6138, 6159-6187, 6198-6208, 6291-6293, 6298, 6344-6352, 6365, 6373-6376, 6401-6408, 6411-6422, 6442-6484, 6517-6572, 6603-6612, 6629-6664, 6690-6701, 6712-6735, 6744-6785, 6789-6795, 6799-6804, 6807-6817, 6821-6822, 6825, 6828, 6831, 6835, 6876-6882, 6923-6929, 6936-6944, 6948-6956, 6960-6968, 6972-6993, 6997-7018, 7029, 7062-7069, 7105, 7109-7110, 7113, 7119, 7122-7124, 7128, 7135-7140, 7155-7159, 7163-7164, 7174, 7178, 7196-7199, 7215-7228, 7232-7243 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/category.py 123 74 40% 178, 182, 194, 213-223, 246-273, 285-296, 303, 311-319, 322-326, 332, 337-340, 356-368, 376-381, 384-396, 401, 470-471, 475-486 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/datetimelike.py 384 272 29% 73, 91, 95, 100, 104, 109, 114, 119, 125, 131-161, 165-170, 173-174, 189-200, 206, 212, 218-226, 230-234, 243, 247, 251-269, 273-277, 295-321, 340-354, 386, 392-401, 423, 437-438, 441-442, 447, 451-473, 478, 487-490, 493, 496-512, 516-519, 523-526, 532-548, 552-568, 572-586, 592-616, 622-651, 655-667, 676-679, 684-687, 691, 695-696, 705-721, 727-748, 752-754, 758-762, 776-787 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/datetimes.py 285 213 25% 64, 75-100, 254, 264-265, 269-270, 279-280, 284-287, 291-292, 296-297, 301, 320-354, 367-372, 375-376, 382-386, 393-396, 404-416, 428-445, 456-471, 491-510, 513-523, 530-534, 544-586, 591-598, 617-659, 667, 690-705, 731-755, 942-956, 1031-1049, 1063-1064 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/extension.py 83 37 55% 28-29, 62, 71-78, 81, 90, 96-105, 154, 160-171, 177, 188, 191-192 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/frozen.py 44 21 52% 45-47, 63-65, 74-76, 79-81, 84-86, 91, 96, 100, 106, 109, 112 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/interval.py 376 267 29% 113-123, 127-137, 145, 221-232, 263-267, 299-303, 334-336, 344-348, 363-373, 377, 380-386, 391, 398, 408, 415-432, 482, 502-506, 525-571, 574-597, 639-667, 676-693, 699-724, 733-736, 744-768, 772, 779-790, 798, 801, 804-807, 813, 817, 821, 825, 833, 839, 844, 854-867, 882-889, 907-918, 926, 932, 941, 955-957, 1059-1137 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/multi.py 1380 1162 16% 105, 143-153, 184-194, 206-211, 326-359, 377-383, 407-445, 489-510, 561-597, 645-658, 717-722, 729-750, 754, 766, 776-779, 782, 790, 800-804, 818-846, 931-940, 956, 972, 979, 990-1016, 1074-1078, 1089-1113, 1119, 1123-1125, 1128-1137, 1180-1204, 1208, 1212-1214, 1218-1223, 1227, 1232-1235, 1243, 1248, 1261-1270, 1279-1280, 1285-1316, 1328-1390, 1396, 1425-1454, 1479, 1482-1506, 1513-1537, 1545, 1550, 1554-1557, 1567, 1571-1580, 1599-1605, 1655-1657, 1661-1665, 1727-1755, 1787, 1823, 1835-1837, 1873-1898, 1941-1989, 1996-2002, 2007-2032, 2044-2050, 2067-2086, 2113-2137, 2140-2144, 2148-2152, 2184-2221, 2226-2242, 2287-2298, 2334-2344, 2357-2363, 2425-2480, 2483-2496, 2499-2506, 2512-2516, 2524, 2529-2539, 2542-2559, 2565-2569, 2619-2621, 2677, 2680-2727, 2748-2752, 2795-2872, 2915-2926, 2934-3075, 3085-3188, 3226-3319, 3343-3407, 3435-3447, 3463-3514, 3521-3527, 3533-3564, 3567, 3575-3579, 3587-3596, 3599-3600, 3603-3608, 3611-3627, 3633-3644, 3647-3658, 3674-3696, 3714-3731, 3743-3744, 3753-3768, 3804-3808, 3812-3836, 3840-3845, 3862-3878, 3897-3901, 3908-3918 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/period.py 191 122 36% 61-67, 157, 162, 175-176, 180-181, 186, 191, 196, 211-265, 272, 291-308, 314-322, 338-343, 351-356, 362, 372-378, 400-440, 443-455, 458-463, 467-470, 473-474, 478-482, 537-547 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/range.py 508 388 24% 103, 117-142, 155-161, 183-188, 213-214, 217-219, 228-231, 235, 239-245, 277-278, 306, 315, 319, 323, 326-331, 335, 342-351, 360-381, 388, 393, 397, 401-413, 416-418, 422-424, 427-433, 437-439, 443-445, 460-471, 478-483, 489-491, 500-526, 534-575, 579-580, 589-597, 602-608, 630-683, 687-770, 773-782, 791-808, 811-829, 840-890, 900, 906-924, 930-931, 935-947, 953, 956, 961-964, 975-1037 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexes/timedeltas.py 69 38 45% 110, 121, 136-176, 184, 197-204, 208-209, 213-215, 221, 308-315 /home/admin/.local/lib/python3.8/site-packages/pandas/core/indexing.py 917 749 18% 83, 137, 548, 613, 661, 676-683, 689-716, 728-775, 789-829, 833-849, 871, 879-893, 900-910, 919-921, 926-928, 932-940, 950-965, 970-1026, 1033-1084, 1087, 1093-1097, 1106, 1109, 1112, 1115, 1120-1123, 1144-1158, 1161, 1173-1192, 1215-1219, 1238-1242, 1269-1273, 1278-1289, 1293, 1297-1307, 1310-1343, 1350-1362, 1379-1434, 1459-1464, 1479-1518, 1529-1554, 1566-1569, 1589, 1594-1598, 1617-1621, 1625, 1627, 1633, 1636, 1639, 1642-1643, 1647, 1653, 1662-1669, 1675, 1679-1685, 1701-1837, 1844-1928, 1933-1950, 1953-1999, 2011-2036, 2042-2078, 2084-2181, 2188-2198, 2217-2299, 2302-2348, 2360, 2363-2371, 2374-2386, 2401-2404, 2409-2410, 2413-2419, 2422-2430, 2441-2444, 2462-2464, 2471-2473, 2502-2525, 2533-2541, 2549-2552, 2559-2562, 2572-2579, 2589, 2602, 2618, 2627 /home/admin/.local/lib/python3.8/site-packages/pandas/core/interchange/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/interchange/dataframe_protocol.py 101 1 99% 158 /home/admin/.local/lib/python3.8/site-packages/pandas/core/interchange/from_dataframe.py 171 151 12% 48-54, 73-91, 108-137, 156-164, 181-216, 233-307, 313-340, 357-376, 411-436, 469-499 /home/admin/.local/lib/python3.8/site-packages/pandas/core/interchange/utils.py 44 11 75% 75-90 /home/admin/.local/lib/python3.8/site-packages/pandas/core/internals/__init__.py 7 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/internals/api.py 36 26 28% 50-81, 88-97 /home/admin/.local/lib/python3.8/site-packages/pandas/core/internals/array_manager.py 583 443 24% 130, 134-138, 142, 150, 155, 160-161, 165-167, 170, 176, 179, 182-183, 186-193, 216-255, 261-310, 313-319, 327, 330, 333-339, 347-348, 351, 354-361, 366-370, 375-378, 381-401, 404, 407-411, 423-425, 434, 438, 442, 447, 453, 457, 460-468, 479, 490, 509-529, 544-545, 578-632, 644-660, 665-679, 686-689, 698, 708-715, 718-736, 756-768, 771-781, 787-788, 794, 802, 822-861, 872-881, 894-916, 922-927, 944-969, 983-1001, 1008-1013, 1023-1034, 1052-1089, 1115-1144, 1158, 1166-1177, 1180-1185, 1192, 1196-1199, 1203, 1207, 1211, 1215, 1219, 1223, 1227-1230, 1234-1238, 1242, 1245, 1248-1253, 1256-1258, 1261-1265, 1276-1278, 1284-1289, 1293-1296, 1305, 1311-1314, 1331, 1335, 1351-1361 /home/admin/.local/lib/python3.8/site-packages/pandas/core/internals/base.py 88 40 55% 44, 48, 52, 61-70, 85, 98-100, 114, 121-130, 138, 142, 148, 151, 154, 160, 181-193, 196-201, 205, 222 /home/admin/.local/lib/python3.8/site-packages/pandas/core/internals/blocks.py 1041 770 26% 120-121, 135-139, 167, 175-178, 186, 190, 201-203, 211, 221-228, 241, 249-256, 260, 273-277, 288-293, 298-299, 315-318, 329-331, 337-348, 353-369, 376-385, 402-408, 422-424, 430-447, 457-459, 472-474, 509-526, 531-532, 537-544, 567-647, 678-701, 715-806, 839-862, 878, 884, 890, 906, 922-924, 939-940, 954, 961, 991-1007, 1034-1068, 1087-1141, 1160-1260, 1275-1311, 1333-1393, 1398-1399, 1412-1433, 1459-1467, 1484-1500, 1512-1551, 1556, 1563, 1570, 1573, 1608-1639, 1645-1709, 1715-1778, 1782-1789, 1793, 1799-1803, 1806, 1819-1825, 1854-1870, 1875-1877, 1888-1905, 1910-1912, 1919-1934, 1944-1976, 1981, 1985, 2006-2025, 2034-2035, 2040-2041, 2052-2053, 2070-2094, 2103, 2107, 2115, 2134, 2140, 2163-2166, 2171-2173, 2181-2186, 2197, 2211-2238, 2271-2298, 2325, 2329, 2354, 2356, 2358, 2361, 2364, 2379-2382, 2421, 2429, 2434-2440, 2450-2459, 2467-2478, 2486-2494, 2507-2581, 2593-2607 /home/admin/.local/lib/python3.8/site-packages/pandas/core/internals/concat.py 350 303 13% 68-69, 90-117, 139-173, 194-252, 262-290, 303-319, 336-395, 402-406, 409, 413-418, 422-428, 435-458, 462-487, 492-569, 576-615, 622-638, 651-668, 678-681, 707, 720-738, 749-791 /home/admin/.local/lib/python3.8/site-packages/pandas/core/internals/construction.py 428 290 32% 128-140, 147, 156-159, 174-194, 209-230, 244-388, 400-408, 429-464, 479, 496, 503, 529-560, 567-571, 584-591, 596-605, 622, 633-634, 636-637, 641-642, 645, 648, 650, 655, 658, 663-668, 682-703, 707-721, 730-739, 766-768, 794-804, 807-821, 825-827, 831-838, 848, 861-883, 909-920, 935-937, 972, 987-994, 1042, 1044-1063 /home/admin/.local/lib/python3.8/site-packages/pandas/core/internals/managers.py 951 659 31% 155, 161, 165, 190, 196-209, 212, 219-221, 225-226, 235, 243-244, 252, 259-266, 273-274, 277-278, 295-304, 327-356, 359-365, 374, 386-394, 397-403, 413-414, 417, 422-426, 429-433, 443-451, 460-468, 471-475, 484, 494-505, 512, 516, 521, 526-536, 539-540, 553-565, 574-580, 586-614, 618, 634-665, 675-681, 715, 721-727, 734, 737, 740, 795-901, 908-927, 992-1002, 1005-1011, 1052-1082, 1106-1108, 1121-1136, 1148-1279, 1299-1326, 1340-1353, 1364-1385, 1398-1427, 1441-1444, 1453-1466, 1472-1479, 1496-1515, 1530-1539, 1545, 1552, 1580-1592, 1610-1655, 1670-1675, 1703-1704, 1717, 1724, 1727, 1729-1730, 1737, 1761-1762, 1764, 1766, 1781-1800, 1829-1832, 1840, 1869-1871, 1880-1881, 1887-1892, 1900, 1903-1919, 1922-1939, 1942, 1951, 1956, 1960-1979, 1984-1994, 1998, 2002, 2005, 2009, 2017, 2020-2022, 2026, 2038-2042, 2050-2054, 2061, 2073-2074, 2082-2086, 2106-2116, 2139-2140, 2153-2169, 2184, 2195-2196, 2213, 2217, 2221-2235, 2241, 2267-2276, 2282-2311, 2316-2320, 2326-2343 /home/admin/.local/lib/python3.8/site-packages/pandas/core/internals/ops.py 62 46 26% 12-15, 33-52, 61-86, 93-95, 107-136, 143-147 /home/admin/.local/lib/python3.8/site-packages/pandas/core/methods/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/methods/describe.py 148 115 22% 46, 80-95, 108, 127-130, 153-159, 162-176, 180-196, 201-207, 220-247, 263-279, 295-327, 341-351, 364-373, 387-408 /home/admin/.local/lib/python3.8/site-packages/pandas/core/methods/selectn.py 120 97 19% 34, 42-47, 50, 54, 58, 67-69, 88-156, 176-182, 185-262 /home/admin/.local/lib/python3.8/site-packages/pandas/core/missing.py 314 268 15% 46, 53-61, 81-118, 123-140, 168-183, 204-224, 247-267, 302-359, 366-381, 408-489, 507-566, 605-611, 650-654, 734-740, 765-787, 818-858, 866-870, 880-888, 899-901, 910-912, 917-924, 929-936, 943-946, 950, 984-1013, 1028-1030 /home/admin/.local/lib/python3.8/site-packages/pandas/core/nanops.py 626 505 19% 71, 83, 88-104, 130-160, 167-182, 186-195, 202-217, 253-261, 310-350, 354-356, 361-397, 415-429, 451-462, 474-494, 533-551, 588-606, 643-655, 664-674, 711-740, 768-821, 844-848, 880-895, 934-941, 981-1017, 1058-1070, 1083-1097, 1145-1149, 1191-1195, 1237-1285, 1327-1384, 1419-1427, 1439-1456, 1483-1497, 1513-1545, 1568-1576, 1581-1585, 1599-1614, 1620-1643, 1657-1671, 1675-1700, 1708-1720, 1747-1767 /home/admin/.local/lib/python3.8/site-packages/pandas/core/ops/__init__.py 184 134 27% 78, 133-150, 163-173, 183-201, 233-334, 343-365, 384-409, 417-433, 446-473, 489-494 /home/admin/.local/lib/python3.8/site-packages/pandas/core/ops/array_ops.py 191 155 19% 68-83, 99-139, 164-188, 217-234, 256-298, 302-339, 358-405, 424, 430, 433, 435, 448, 470-519, 537-542 /home/admin/.local/lib/python3.8/site-packages/pandas/core/ops/common.py 56 34 39% 64, 69-81, 101-105, 128-151 /home/admin/.local/lib/python3.8/site-packages/pandas/core/ops/dispatch.py 6 1 83% 26 /home/admin/.local/lib/python3.8/site-packages/pandas/core/ops/docstrings.py 57 2 96% 50, 60 /home/admin/.local/lib/python3.8/site-packages/pandas/core/ops/invalid.py 17 9 47% 30-37, 54-55 /home/admin/.local/lib/python3.8/site-packages/pandas/core/ops/mask_ops.py 59 52 12% 42-73, 106-126, 156-184, 188-189 /home/admin/.local/lib/python3.8/site-packages/pandas/core/ops/methods.py 34 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/ops/missing.py 56 48 14% 49-73, 105-134, 158-180 /home/admin/.local/lib/python3.8/site-packages/pandas/core/reshape/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/reshape/api.py 7 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/reshape/concat.py 284 246 13% 54-58, 78, 95, 112, 129, 146, 364-385, 406-563, 570-623, 626-629, 632-633, 639-640, 653-699, 702-705, 709, 713-821 /home/admin/.local/lib/python3.8/site-packages/pandas/core/reshape/encoding.py 154 138 10% 147-224, 236-334, 447-533 /home/admin/.local/lib/python3.8/site-packages/pandas/core/reshape/melt.py 138 117 15% 33-35, 50-158, 214-248, 489-540 /home/admin/.local/lib/python3.8/site-packages/pandas/core/reshape/merge.py 919 816 11% 104-106, 128, 148-162, 176-217, 324-358, 616-633, 680-747, 760-803, 806-825, 830-831, 835-840, 847-869, 872-884, 906-927, 935-1034, 1038, 1046-1101, 1125-1135, 1155-1276, 1285-1440, 1461-1463, 1471-1558, 1562-1605, 1642-1690, 1737-1779, 1799-1800, 1816-1842, 1846-1847, 1859-1864, 1891-1898, 1914-1990, 1996-2063, 2068-2189, 2204-2234, 2240-2242, 2247, 2275-2279, 2285-2309, 2369-2468, 2475-2505, 2511-2517, 2527-2554, 2558-2560, 2564, 2568-2575, 2591-2645 /home/admin/.local/lib/python3.8/site-packages/pandas/core/reshape/pivot.py 366 333 9% 51, 71-110, 129-255, 269-339, 345-362, 368-436, 448-480, 484-494, 506-562, 671-734, 740-814, 818-831, 864-885 /home/admin/.local/lib/python3.8/site-packages/pandas/core/reshape/tile.py 181 158 13% 241-305, 369-389, 403-472, 481-505, 522-539, 557-561, 568-591, 602-608, 617-625, 632-640, 647-651 /home/admin/.local/lib/python3.8/site-packages/pandas/core/reshape/util.py 28 22 21% 33-60, 77-82 /home/admin/.local/lib/python3.8/site-packages/pandas/core/roperator.py 29 15 48% 11, 15, 19, 23, 27, 31, 38-42, 46, 50, 54, 58, 62 /home/admin/.local/lib/python3.8/site-packages/pandas/core/sample.py 58 48 17% 19, 31-76, 90-113, 144-151 /home/admin/.local/lib/python3.8/site-packages/pandas/core/series.py 1122 756 33% 179-187, 221-230, 384, 394-519, 546-570, 576, 584-586, 591, 605, 619, 716, 754-756, 762, 778-781, 787, 857-863, 916-921, 938, 945-960, 971, 985, 990, 997, 1001, 1004, 1009-1033, 1037-1073, 1077-1093, 1096-1097, 1113, 1121-1138, 1141-1219, 1222-1225, 1230-1248, 1251-1256, 1259-1263, 1280-1290, 1298, 1302-1305, 1311-1312, 1320, 1325, 1331-1336, 1346-1367, 1376, 1429-1432, 1446, 1458, 1470, 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/home/admin/.local/lib/python3.8/site-packages/pandas/core/shared_docs.py 13 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/sorting.py 252 201 20% 47-49, 81-106, 144-200, 223-224, 228-232, 239-254, 276-287, 293-301, 329-366, 399-400, 410, 417, 436-439, 458-473, 480-484, 516-533, 549-577, 587-594, 606-623, 656-670, 681-692, 710-725 /home/admin/.local/lib/python3.8/site-packages/pandas/core/strings/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/strings/accessor.py 581 386 34% 49, 123-129, 140-141, 179-195, 220-236, 239-240, 251-393, 411-448, 593-683, 888-895, 912-913, 1008-1009, 1022-1023, 1085-1086, 1151-1152, 1281-1290, 1321-1322, 1354-1355, 1485-1508, 1551-1552, 1613-1625, 1650, 1655, 1660, 1723-1728, 1802-1803, 1878-1879, 1898-1907, 1925-1926, 2014-2015, 2023-2024, 2032-2033, 2088-2089, 2096-2097, 2155-2156, 2197-2198, 2224-2225, 2292-2293, 2359-2363, 2429-2433, 2525-2526, 2612-2654, 2732, 2771-2776, 2788-2793, 2812-2813, 2855-2860, 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/home/admin/.local/lib/python3.8/site-packages/pandas/core/window/__init__.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/window/common.py 81 72 11% 18-146, 150-161, 166-168 /home/admin/.local/lib/python3.8/site-packages/pandas/core/window/doc.py 15 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/core/window/ewm.py 227 170 25% 18-19, 70-94, 118-121, 347-394, 409, 415, 445, 492, 517-546, 569-600, 621-630, 651-663, 700-735, 771-812, 825-830, 843-847, 868-892, 898, 901, 904, 912, 921, 924, 970-1012 /home/admin/.local/lib/python3.8/site-packages/pandas/core/window/expanding.py 74 23 69% 17-18, 125, 137, 171, 186, 209, 239, 266, 293, 320, 347, 406, 466, 508, 526, 566, 602, 676, 719, 789, 812-816 /home/admin/.local/lib/python3.8/site-packages/pandas/core/window/numba_.py 146 129 12% 49-75, 111-173, 208-236, 244-257, 293-349 /home/admin/.local/lib/python3.8/site-packages/pandas/core/window/online.py 52 43 17% 32-86, 91-99, 102-114, 117-118 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/home/admin/.local/lib/python3.8/site-packages/pandas/io/_util.py 6 2 67% 9-10 /home/admin/.local/lib/python3.8/site-packages/pandas/io/api.py 17 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/io/clipboards.py 11 1 91% 20 /home/admin/.local/lib/python3.8/site-packages/pandas/io/common.py 444 337 24% 124-132, 135, 138, 154-156, 161, 166, 183-185, 189-214, 219, 226, 252-260, 268-270, 278, 319-458, 480-482, 522-531, 560-586, 598-600, 615, 630, 645, 702-913, 936, 939-951, 963-969, 977-984, 991-999, 1003-1006, 1017-1025, 1032-1037, 1041-1042, 1053, 1056, 1059-1061, 1064-1066, 1069-1071, 1078-1084, 1087, 1090-1100, 1107-1134, 1139-1148, 1154-1167, 1175-1187, 1209-1212, 1233-1253 /home/admin/.local/lib/python3.8/site-packages/pandas/io/excel/__init__.py 9 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/io/excel/_base.py 413 301 27% 395, 434, 473-515, 523-545, 552, 556, 559-569, 574, 578, 582, 586, 589-591, 596-597, 620-626, 655-690, 716-897, 1103-1121, 1129, 1134, 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102 71 30% 24-27, 43, 65-86, 90-93, 115-125, 149-158, 163, 168, 173, 178, 197-209, 214, 219, 223-236, 260-271, 295-305, 327-332 /home/admin/.local/lib/python3.8/site-packages/pandas/io/excel/_xlrd.py 62 43 31% 33-35, 39-41, 44-50, 54, 57-58, 61-62, 67-126 /home/admin/.local/lib/python3.8/site-packages/pandas/io/excel/_xlsxwriter.py 83 63 24% 101-172, 192-210, 219, 223-224, 230, 241-275 /home/admin/.local/lib/python3.8/site-packages/pandas/io/feather_format.py 43 28 35% 54-96, 139-162 /home/admin/.local/lib/python3.8/site-packages/pandas/io/formats/__init__.py 4 2 50% 5-8 /home/admin/.local/lib/python3.8/site-packages/pandas/io/formats/console.py 33 28 15% 15-47, 63-76, 87-94 /home/admin/.local/lib/python3.8/site-packages/pandas/io/formats/format.py 908 752 17% 112, 209-214, 217-231, 234, 243-261, 279-295, 298-322, 325-363, 366-374, 377, 386-421, 426, 429, 432, 435, 442-451, 457-460, 468-476, 480-484, 504-510, 537-549, 585-609, 615-621, 625, 631, 635, 639, 643, 647, 651, 655, 659, 663, 666-668, 673-678, 684-687, 690-697, 702-721, 725-732, 738-751, 761-765, 769, 772, 775, 779-789, 795-799, 809-825, 834-843, 846-890, 893-895, 906-915, 918-956, 961-996, 999-1005, 1026, 1044-1058, 1094-1109, 1131-1135, 1159-1194, 1205-1210, 1221-1244, 1292-1330, 1349-1360, 1363-1364, 1367-1442, 1447-1456, 1465-1512, 1520-1611, 1614, 1619-1625, 1636-1638, 1642-1653, 1658-1684, 1721-1754, 1759-1779, 1783-1788, 1796-1803, 1812-1817, 1824-1833, 1839-1846, 1857-1859, 1862-1865, 1879-1912, 1921-1946, 1954-1971, 1979-1983, 1994-2019, 2023-2026, 2060-2061, 2083-2123, 2181, 2202-2224, 2238-2240 /home/admin/.local/lib/python3.8/site-packages/pandas/io/formats/info.py 356 179 50% 28, 315, 342-346, 353-355, 412, 416-427, 438, 451-452, 456, 468, 480, 485, 490, 494-495, 505-511, 524-525, 535-545, 549, 553, 557-559, 570-571, 581-585, 615-619, 624, 629, 634, 639, 642-644, 647-650, 656-667, 692-695, 701-707, 710-713, 730, 735, 740, 745, 750, 754, 758, 762, 766-769, 783, 786-791, 795-797, 806, 811, 816, 820, 830-835, 838, 859, 863-864, 871-872, 880-883, 894-900, 903-911, 914-921, 925-926, 930-931, 945-948, 952-960, 965-967, 970, 974, 982, 991-992, 996-997, 1011, 1014-1016, 1021, 1025, 1039-1043, 1057-1060, 1064-1072, 1075, 1080-1082, 1086, 1090, 1101 /home/admin/.local/lib/python3.8/site-packages/pandas/io/formats/printing.py 203 183 10% 43-59, 66-71, 107-130, 140-161, 195-234, 240-241, 245-275, 279, 320-456, 481-497, 504 /home/admin/.local/lib/python3.8/site-packages/pandas/io/gbq.py 21 14 33% 12, 18-23, 173-186, 214-215 /home/admin/.local/lib/python3.8/site-packages/pandas/io/html.py 367 291 21% 54, 67-80, 105, 127-134, 150-161, 242-247, 257-258, 278, 294, 310, 326, 341, 360, 375, 401, 420, 431, 458-476, 501-558, 576-579, 603-606, 609-630, 633-634, 637, 640, 643, 646, 649-652, 655, 658-661, 664-679, 698-702, 728-729, 732, 737, 740-765, 768, 786-824, 827-842, 845-848, 851, 855-862, 866-886, 918-935, 939-940, 944-968, 972-1021, 1192-1212 /home/admin/.local/lib/python3.8/site-packages/pandas/io/json/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/io/json/_json.py 501 386 23% 84, 107, 127, 146-204, 222-237, 240, 243-244, 266-269, 272-273, 281-286, 292-301, 327-379, 383, 408, 433, 458, 483, 743-784, 817-862, 872-878, 894-919, 925, 931, 935, 939, 946-981, 987-1008, 1017-1018, 1021, 1025, 1029, 1033, 1036-1061, 1064, 1072, 1099-1122, 1128-1131, 1134-1141, 1144, 1150-1160, 1163, 1176-1241, 1251-1280, 1283, 1291-1298, 1301-1307, 1315-1346, 1354-1374, 1377-1382, 1387-1415 /home/admin/.local/lib/python3.8/site-packages/pandas/io/json/_normalize.py 142 126 11% 35-39, 86-120, 146-166, 184-191, 237-244, 388-536 /home/admin/.local/lib/python3.8/site-packages/pandas/io/json/_table_schema.py 134 114 15% 42-43, 79-96, 101-120, 124-151, 195-224, 283-316, 355-382 /home/admin/.local/lib/python3.8/site-packages/pandas/io/orc.py 52 38 27% 80-97, 162-205 /home/admin/.local/lib/python3.8/site-packages/pandas/io/parquet.py 168 131 22% 46-75, 88-115, 121-122, 125, 128, 133-141, 153-194, 205-237, 244-247, 259-287, 299-342, 405-425, 493-509 /home/admin/.local/lib/python3.8/site-packages/pandas/io/parsers/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/io/parsers/arrow_parser_wrapper.py 67 53 21% 21-25, 31-42, 48-79, 101-136, 149-164 /home/admin/.local/lib/python3.8/site-packages/pandas/io/parsers/base_parser.py 578 491 15% 96, 109-176, 202-234, 240, 245, 253-267, 294-340, 349-352, 359-383, 387-406, 410-434, 438-451, 455-503, 515-593, 617-662, 683-766, 784-837, 845, 853, 862-874, 891-898, 911, 917, 931-933, 957-964, 991-1013, 1016-1050, 1055-1096, 1105-1165, 1221-1302, 1308-1327, 1353-1362, 1371-1384, 1388 /home/admin/.local/lib/python3.8/site-packages/pandas/io/parsers/c_parser_wrapper.py 177 149 16% 50, 61-192, 196-199, 208-220, 232-337, 341-346, 349-357, 360-365, 375-402, 412-423 /home/admin/.local/lib/python3.8/site-packages/pandas/io/parsers/python_parser.py 630 576 9% 50, 67-176, 179-243, 250-300, 307-323, 333-336, 343-364, 376-573, 587-621, 627-630, 642-683, 698, 701-754, 773-777, 792-825, 828-846, 863-872, 875-878, 885-899, 902-905, 910, 928-989, 992-1075, 1078-1156, 1159-1163, 1180-1204, 1234-1245, 1251-1267, 1272-1281, 1292-1294, 1297, 1313, 1321, 1345-1351 /home/admin/.local/lib/python3.8/site-packages/pandas/io/parsers/readers.py 486 399 18% 473, 478, 483, 502-513, 531-537, 546-583, 640, 697, 754, 811, 884-912, 969, 1026, 1083, 1140, 1213-1242, 1312-1352, 1368-1407, 1410-1412, 1415-1456, 1460-1465, 1472-1620, 1623-1627, 1634-1683, 1686, 1689-1724, 1727-1733, 1736, 1744, 1802-1803, 1808-1840, 1845-1853, 1858-1878, 1936-2008, 2019-2028, 2050-2052, 2074-2106, 2123-2127 /home/admin/.local/lib/python3.8/site-packages/pandas/io/pickle.py 28 15 46% 92-103, 178-204 /home/admin/.local/lib/python3.8/site-packages/pandas/io/pytables.py 2255 1832 19% 118-124, 136-138, 143-146, 156-158, 173-182, 235-248, 272-307, 389-462, 467-476, 557-579, 582, 587-589, 593, 596, 599, 602, 606-610, 619-624, 627, 630-631, 634, 642, 666-674, 679, 685-686, 699-731, 737-739, 746-748, 766-770, 785-791, 839-866, 894-898, 935-938, 983-1059, 1113-1116, 1154-1188, 1249-1259, 1309-1373, 1406-1413, 1426-1430, 1470-1489, 1493-1505, 1509-1515, 1545-1574, 1584-1613, 1619-1620, 1625-1630, 1643-1721, 1746-1783, 1786-1788, 1792-1806, 1811-1827, 1867-1894, 1898-1910, 1913-1914, 1918-1939, 1977-2001, 2006, 2010, 2014-2016, 2019-2022, 2031, 2037, 2042-2045, 2053-2092, 2096, 2100, 2104, 2109, 2114, 2117, 2125-2130, 2133, 2136-2141, 2146-2160, 2164-2167, 2176-2201, 2205-2207, 2211, 2215-2223, 2230-2231, 2239, 2254-2257, 2260, 2296-2310, 2314, 2318, 2321-2326, 2335, 2341-2348, 2352, 2359-2384, 2388, 2393-2403, 2407, 2411, 2415, 2419, 2424, 2428-2435, 2455-2537, 2541-2544, 2553-2555, 2559, 2563, 2567, 2571, 2605-2611, 2615, 2620-2627, 2631, 2635-2642, 2646-2647, 2650-2651, 2655, 2659, 2663, 2667, 2671, 2675, 2679, 2690, 2694, 2698, 2702-2704, 2714-2718, 2727, 2732, 2743-2747, 2759, 2765, 2768-2811, 2817-2823, 2830, 2834-2835, 2839-2842, 2846, 2850-2880, 2885-2892, 2897-2917, 2920-2942, 2947-2963, 2970-3003, 3008-3012, 3021-3102, 3113-3116, 3125-3128, 3132-3135, 3145-3168, 3178-3203, 3207-3229, 3282-3288, 3292, 3296-3306, 3314-3317, 3321-3347, 3355, 3364-3372, 3377, 3382, 3386, 3391, 3395, 3399, 3403, 3408, 3412, 3417, 3427-3436, 3441, 3445, 3449-3450, 3461, 3472-3474, 3478-3487, 3491-3499, 3503-3506, 3517-3528, 3536-3607, 3639-3689, 3712-3727, 3732, 3739-3770, 3804-4002, 4015-4070, 4075-4125, 4136-4156, 4166-4182, 4196-4225, 4247, 4255, 4280-4321, 4327-4375, 4398-4424, 4428-4482, 4495, 4500-4502, 4512-4581, 4594, 4598, 4602-4605, 4614-4629, 4640-4646, 4660, 4664, 4668-4674, 4679-4709, 4712, 4725, 4728-4737, 4746-4754, 4760-4777, 4785-4786, 4793, 4798, 4814-4836, 4840-4900, 4906-4925, 4938-4998, 5017-5029, 5051-5067, 5071-5075, 5079-5082, 5090-5092, 5109-5117, 5124-5150, 5157-5172, 5194-5230, 5234-5253, 5259-5265, 5271-5289 /home/admin/.local/lib/python3.8/site-packages/pandas/io/sas/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/io/sas/sasreader.py 51 29 43% 29, 40, 44, 47, 55, 69, 83, 134-180 /home/admin/.local/lib/python3.8/site-packages/pandas/io/spss.py 22 12 45% 18-20, 54-67 /home/admin/.local/lib/python3.8/site-packages/pandas/io/sql.py 746 610 18% 71-72, 85-90, 96-118, 126-139, 148-165, 178-188, 208-219, 238, 253, 332-353, 368, 383, 464-469, 494, 510, 629-663, 758-769, 804-805, 821-841, 868-886, 889, 892-894, 898-900, 903-914, 928-930, 941-946, 949-986, 992-1030, 1043-1066, 1077-1113, 1117-1145, 1148-1159, 1162-1189, 1207-1244, 1247-1314, 1317-1343, 1352, 1355, 1368, 1382, 1399, 1403, 1407, 1418, 1437, 1442, 1458-1470, 1475-1502, 1526-1544, 1547-1548, 1552-1556, 1560-1563, 1627-1631, 1653-1671, 1738-1765, 1782-1815, 1826-1840, 1908-1933, 1937, 1940-1943, 1946-1956, 1959-1964, 1974-1983, 2001-2005, 2016-2023, 2035-2044, 2047, 2050-2052, 2055-2071, 2074-2076, 2079-2082, 2090-2133, 2136-2167, 2182, 2186-2194, 2197-2214, 2228-2245, 2266-2293, 2296-2299, 2353-2379, 2382-2385, 2388, 2391-2392, 2402-2411, 2444-2445 /home/admin/.local/lib/python3.8/site-packages/pandas/io/stata.py 1590 1368 14% 84, 280-397, 412-505, 577-664, 682-692, 697-736, 752-788, 811-819, 897-900, 912, 924, 927, 930, 933, 941-953, 973-1051, 1134-1169, 1175-1176, 1182-1207, 1211-1212, 1220-1221, 1231-1239, 1245-1248, 1251, 1254, 1257, 1260, 1263, 1266, 1269, 1272, 1275, 1278, 1284-1293, 1297-1348, 1354-1377, 1381-1382, 1386-1395, 1399-1405, 1408-1420, 1423-1426, 1429-1438, 1441-1450, 1453-1462, 1465-1537, 1541-1553, 1556-1558, 1562-1579, 1582-1636, 1639-1667, 1670-1671, 1686-1688, 1702-1847, 1851-1894, 1897-1904, 1907-1936, 1948-2013, 2020-2021, 2028-2029, 2039-2040, 2050-2053, 2072-2090, 2094-2099, 2106-2108, 2115-2133, 2137-2147, 2167-2183, 2205-2228, 2336-2357, 2363, 2369, 2378-2402, 2409-2444, 2452-2461, 2486-2494, 2509-2567, 2570-2574, 2580-2640, 2650-2677, 2683-2730, 2740-2743, 2759, 2762-2763, 2770-2818, 2821-2822, 2827-2830, 2834-2835, 2839-2840, 2844-2852, 2856-2876, 2880, 2883-2912, 2915, 2919-2920, 2923, 2944-2965, 2972-2974, 3013-3037, 3040-3041, 3072-3092, 3123-3155, 3266-3284, 3289-3291, 3295-3296, 3304-3354, 3362-3384, 3387-3391, 3394-3402, 3405-3407, 3410-3415, 3418-3430, 3434-3462, 3465-3466, 3469-3472, 3475-3476, 3482-3488, 3491-3493, 3501-3504, 3511-3522, 3525-3536, 3659-3684, 3707-3721 /home/admin/.local/lib/python3.8/site-packages/pandas/io/xml.py 241 201 17% 50-54, 162-176, 186, 210-288, 313-390, 407, 421, 432, 442-461, 471-502, 507-520, 527-543, 561-580, 583-607, 612-626, 633-661, 671-676, 696-721, 733-739, 751-758, 801-846, 1116-1118 /home/admin/.local/lib/python3.8/site-packages/pandas/plotting/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/plotting/_core.py 191 134 30% 30-32, 98-99, 222-223, 474-475, 506-507, 596-597, 791, 802-892, 895-975, 1044, 1136, 1222, 1289, 1351, 1459, 1534, 1583-1589, 1674, 1760-1765, 1786-1831, 1857-1864 /home/admin/.local/lib/python3.8/site-packages/pandas/plotting/_misc.py 73 43 41% 12-16, 40-41, 64-65, 84-85, 159-160, 252-253, 321-322, 387-388, 455-456, 514-515, 549-550, 571-574, 577-578, 581-584, 587-588, 599, 602, 610-615 /home/admin/.local/lib/python3.8/site-packages/pandas/testing.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/tseries/__init__.py 4 2 50% 5-11 /home/admin/.local/lib/python3.8/site-packages/pandas/tseries/api.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/tseries/frequencies.py 307 236 23% 98, 132-175, 184-210, 216, 222, 226, 230, 241-280, 284-285, 289-290, 294, 298, 301, 305-306, 310, 313-342, 345-353, 356-367, 370-381, 384-391, 395-405, 413-427, 432-433, 437, 441-446, 470-506, 525-564, 580-583, 587-589, 593-594, 598-599, 603-604, 608-609 /home/admin/.local/lib/python3.8/site-packages/pandas/tseries/offsets.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/util/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/pandas/util/_decorators.py 135 79 41% 56-94, 164-214, 243-252, 257-260, 291-337, 368, 436, 448-449, 491 /home/admin/.local/lib/python3.8/site-packages/pandas/util/_exceptions.py 48 36 25% 16-27, 36-51, 75-89 /home/admin/.local/lib/python3.8/site-packages/pandas/util/_print_versions.py 48 34 29% 24-27, 34-36, 56-90, 108-134 /home/admin/.local/lib/python3.8/site-packages/pandas/util/_str_methods.py 12 1 92% 23 /home/admin/.local/lib/python3.8/site-packages/pandas/util/_tester.py 18 11 39% 25-35 /home/admin/.local/lib/python3.8/site-packages/pandas/util/_validators.py 122 87 29% 33-41, 55-79, 117-123, 132-136, 161-163, 206-221, 259, 285-302, 326-336, 341, 346, 357, 377-390, 409-424, 435-442, 446-448 /home/admin/.local/lib/python3.8/site-packages/pandas/util/version/__init__.py 270 129 52% 28, 31, 34, 37, 40, 43, 46, 49, 52, 60, 63, 66, 69, 72, 75, 78, 81, 84, 123-126, 139, 146, 151-154, 157-160, 164, 169-172, 175-178, 183-186, 193, 196, 200, 204, 208, 212, 216, 220, 224, 228, 232, 236, 240, 255-268, 276-294, 338, 363, 366-391, 395-396, 400-401, 405-406, 410, 418-421, 425, 429-438, 442, 446, 450, 454, 458, 462, 471-489, 493-495, 508, 537, 543, 550, 557, 570 /home/admin/.local/lib/python3.8/site-packages/psutil/__init__.py 950 691 27% 37-38, 127-128, 131-132, 135-136, 139-140, 143-180, 248-259, 271-281, 290-292, 298-304, 346, 349-393, 396-411, 421-423, 426, 429-431, 436, 467-505, 518-549, 556-568, 574-579, 586-601, 617-618, 628-647, 654-686, 690, 694-697, 703-715, 722-724, 728, 732-737, 746, 752, 758, 764, 776, 793-798, 813-816, 829-837, 850, 858, 862-866, 872, 876, 886, 915-956, 993-1048, 1059, 1070, 1074, 1090, 1102-1119, 1133-1147, 1154, 1178, 1184-1202, 1211-1212, 1222-1223, 1233-1234, 1244-1245, 1254-1255, 1273-1275, 1322-1323, 1326, 1329-1331, 1334-1347, 1350-1356, 1360-1364, 1383-1385, 1393-1403, 1431-1482, 1521-1571, 1593-1599, 1632-1634, 1638-1640, 1647-1659, 1666-1675, 1679-1696, 1736-1783, 1808-1859, 1864, 1877-1907, 1918, 1981-1984, 2000, 2013, 2025, 2060-2072, 2111-2121, 2155, 2176-2203, 2218, 2237-2259, 2272, 2290, 2304, 2317, 2327-2337, 2406, 2409 /home/admin/.local/lib/python3.8/site-packages/psutil/_common.py 442 251 43% 29-30, 33-34, 39, 131-133, 144-145, 157, 161-162, 278-279, 282-283, 295-304, 307, 320-332, 340-350, 360-367, 377-384, 412, 447-457, 462, 466-469, 481-488, 496-503, 509-517, 524-545, 552-553, 565-566, 576-590, 605-606, 623-628, 634-639, 645-678, 682-690, 694-695, 703-704, 721-727, 739-747, 757-760, 770-780, 785-798, 803-832, 836-842, 846 /home/admin/.local/lib/python3.8/site-packages/psutil/_compat.py 243 215 12% 27, 30-41, 57-119, 132-272, 278-324, 330-345 /home/admin/.local/lib/python3.8/site-packages/psutil/_pslinux.py 1130 874 23% 56, 113, 121-124, 217-232, 239-245, 258-264, 298-305, 310-313, 344-371, 390-492, 498-546, 592-616, 622-652, 657-672, 683-727, 778-797, 800-813, 832-868, 873-908, 913-946, 949-977, 985, 992-1022, 1027-1043, 1058-1146, 1151-1182, 1203-1290, 1303-1322, 1332-1405, 1415-1428, 1434-1441, 1452, 1459-1484, 1491-1506, 1515-1526, 1536-1539, 1545, 1558-1580, 1589-1590, 1595-1597, 1600-1602, 1605-1607, 1611-1615, 1618-1632, 1636-1657, 1661-1663, 1667-1672, 1678-1704, 1709-1715, 1720, 1724, 1728-1735, 1750-1753, 1766-1788, 1801-1858, 1862-1869, 1874-1883, 1890-1891, 1895-1919, 1928, 1932, 1939, 1944-1949, 1953-1968, 1975-1978, 1982-1988, 1997-2017, 2021-2025, 2029-2069, 2073-2075, 2079, 2083, 2087-2089, 2093-2095 /home/admin/.local/lib/python3.8/site-packages/psutil/_psposix.py 89 67 25% 30-47, 61-110, 120-158, 167-175 /home/admin/.local/lib/python3.8/site-packages/pyarrow/__init__.py 170 121 29% 41-59, 80-93, 97-102, 106-116, 123-157, 312-315, 343, 347, 351-356, 360-367, 375, 393-416, 426-466 /home/admin/.local/lib/python3.8/site-packages/pyarrow/_compute_docstrings.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/pyarrow/_generated_version.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/pyarrow/compute.py 203 92 55% 114, 137-138, 175-179, 208-211, 215-232, 238-245, 248-262, 391-403, 425-441, 484-485, 539-544, 584-591, 631-638, 663-664, 700-713, 730 /home/admin/.local/lib/python3.8/site-packages/pyarrow/filesystem.py 225 139 38% 54-55, 66, 79, 94-105, 108, 118, 124, 130, 143, 156, 167, 178, 189, 196, 225-228, 235, 239, 260-261, 265-266, 270-274, 278-279, 283-284, 288, 292-293, 300-301, 305, 311-312, 321-325, 329, 333, 341, 345-346, 350-351, 355-359, 366-367, 370-371, 377-378, 385-393, 397-402, 411-433, 437-440, 444-459, 467-511 /home/admin/.local/lib/python3.8/site-packages/pyarrow/hdfs.py 82 52 37% 42-49, 52, 59, 63, 67, 71, 86, 90, 94, 111, 126-131, 135-149, 153-165, 169-172, 176-185, 223-227, 235-240 /home/admin/.local/lib/python3.8/site-packages/pyarrow/ipc.py 61 36 41% 51-52, 84-85, 109-110, 121-122, 126-141, 146-150, 154, 190, 195, 234, 259-264, 282-285 /home/admin/.local/lib/python3.8/site-packages/pyarrow/types.py 155 47 70% 56, 61, 66, 71, 76, 81, 86, 91, 96, 101, 106, 111, 116, 121, 126, 131, 136, 141, 146, 151, 156, 161, 166, 171, 176, 181, 186, 191, 196, 201, 206, 211, 223, 228, 233, 238, 243, 248, 253, 258, 263, 268, 273, 278, 283, 288, 293 /home/admin/.local/lib/python3.8/site-packages/pyarrow/util.py 96 60 38% 64, 101-106, 114-123, 127-131, 135, 142-151, 158, 177-194, 198-202, 206-207, 213-230 /home/admin/.local/lib/python3.8/site-packages/pyarrow/vendored/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/pyarrow/vendored/docscrape.py 473 282 40% 24, 46, 62, 82, 101, 104, 109-112, 155-157, 164, 169, 172, 183, 187-188, 222, 224, 238-241, 297-341, 349-360, 365, 373-376, 395-396, 398-399, 406, 412-420, 424-428, 431-442, 447, 450, 453-455, 458-460, 463-465, 468-481, 484-489, 492-521, 524-538, 541-555, 565-574, 577-582, 585-599, 604-607, 616-666, 670-672, 680-682, 689-693, 697-716 /home/admin/.local/lib/python3.8/site-packages/pycparser/__init__.py 25 18 28% 32-48, 82-90 /home/admin/.local/lib/python3.8/site-packages/pycparser/ast_transforms.py 21 18 14% 64-96, 103-105 /home/admin/.local/lib/python3.8/site-packages/pycparser/c_ast.py 782 446 43% 25-28, 37-51, 56, 80-100, 149-158, 164-165, 176-179, 182-185, 192-194, 197-200, 203-206, 213-216, 219-222, 225-228, 235-238, 241-244, 247-250, 257, 260, 263-264, 271-273, 276-280, 283-286, 293-295, 298-301, 304-307, 314-315, 318-321, 324-325, 332-334, 337-340, 343-346, 358-359, 362-363, 370, 373, 376-377, 394-398, 401-406, 413-414, 417-420, 423-424, 431-432, 435-438, 441-442, 449-451, 454-457, 460-463, 470, 473, 476-477, 484, 487, 490-491, 498-500, 503-505, 508-509, 516-518, 521-523, 526-527, 534-535, 538-541, 544-545, 552-553, 556-559, 562-563, 574-577, 580-581, 588-592, 595-600, 603-610, 617-619, 622-625, 628-631, 643-646, 649-652, 659-662, 665-670, 673-678, 685-686, 689-690, 693-694, 701-702, 705-706, 709-710, 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339-340, 360-361, 368-396, 399-407, 411, 416, 419-422, 440, 450-454, 463-469, 494-523, 546, 578-581, 587-589, 592-594, 597-599, 605-612, 622-630, 637-638, 642-644, 647-649, 651-653, 655-657, 679-681, 693-694, 696-699, 708, 711-712, 717-718, 730-822, 833-856, 867, 881-882, 896, 902-903, 909-910, 920-1047, 1056-1080, 1092 /home/admin/.local/lib/python3.8/site-packages/pycparser/ply/yacc.py 1916 1562 18% 97, 114, 119, 122, 129, 132, 140-146, 150-156, 176-177, 180-181, 184-185, 190-198, 219, 222, 242, 246, 252, 264-266, 272-274, 277, 295, 298-303, 321, 325-327, 329, 350-683, 697-989, 1015-1016, 1030, 1063, 1087-1088, 1123-1135, 1157-1168, 1176-1271, 1312-1339, 1342, 1345, 1348, 1351, 1354, 1358-1370, 1374-1375, 1392, 1395, 1429-1437, 1440-1444, 1447, 1455-1460, 1475-1507, 1511, 1514, 1525-1530, 1551-1624, 1634-1640, 1652-1662, 1673-1727, 1737-1745, 1754-1759, 1769-1774, 1786-1791, 1804-1829, 1837-1864, 1875-1914, 1933-1958, 1980, 1986, 1999-2023, 2056-2064, 2067-2087, 2101-2133, 2138-2154, 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383-410, 416-423, 430-434, 441-457, 467-477, 484-486, 495-496, 505-511, 518-523, 531-533 /home/admin/.local/lib/python3.8/site-packages/pydrive/drive.py 15 5 67% 16-17, 28, 39, 47 /home/admin/.local/lib/python3.8/site-packages/pydrive/files.py 267 199 25% 41-43, 55, 63-72, 95-120, 133-142, 155-157, 169-173, 190-194, 207-213, 228-244, 252-270, 279-285, 292, 300, 309, 322-331, 341-342, 352, 362-375, 384-395, 405-416, 427-435, 446-460, 471-481, 490-492, 503-506, 518-531, 543-571, 583-609 /home/admin/.local/lib/python3.8/site-packages/pydrive/settings.py 46 34 26% 5-6, 141-146, 156, 169-171, 186-213 /home/admin/.local/lib/python3.8/site-packages/pygit2/__init__.py 92 43 53% 123-162, 203-225 /home/admin/.local/lib/python3.8/site-packages/pygit2/_build.py 18 12 33% 46-53, 58-67 /home/admin/.local/lib/python3.8/site-packages/pygit2/blame.py 69 36 48% 33-36, 44-47, 52, 58, 63, 68, 72, 77, 82, 86, 91-95, 102-105, 108, 111, 114-118, 130-137, 140 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/home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_enc_macroman.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_enc_pdfdoc.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_enc_standard.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_enc_symbol.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_enc_winansi.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_enc_zapfdingbats.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_courier.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_courierbold.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_courierboldoblique.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_courieroblique.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_helvetica.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_helveticabold.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_helveticaboldoblique.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_helveticaoblique.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_symbol.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_timesbold.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_timesbolditalic.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_timesitalic.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_timesroman.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/_fontdata_widths_zapfdingbats.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/reportlab/pdfbase/pdfdoc.py 1657 716 57% 32-35, 78, 89, 140, 165, 188-189, 194, 203, 206-213, 219, 223, 229-230, 236, 251-254, 273, 276-277, 283, 301, 304, 307-308, 311-314, 317-335, 342, 350, 359, 366, 373, 380, 385, 388-395, 410, 432-436, 444, 462, 468-469, 475-487, 516, 519, 526-529, 550, 554-555, 558, 565-572, 579-580, 593-595, 604-621, 627-633, 637-638, 642-643, 645, 647, 650, 653, 662, 676, 678, 680, 685-687, 701, 705-708, 714-717, 720, 725-726, 729-734, 766-769, 780, 783, 805, 832-839, 856, 861-864, 893-894, 913, 948, 950, 972, 983, 1041, 1044, 1047-1048, 1051-1052, 1070, 1116, 1127, 1134-1135, 1139, 1154, 1159, 1179, 1195, 1198-1209, 1274-1278, 1281-1283, 1287-1296, 1312, 1318-1327, 1362-1395, 1398, 1402-1408, 1411-1412, 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4 76% 5-10 /home/admin/.local/lib/python3.8/site-packages/requests/sessions.py 268 118 56% 56, 86, 100-103, 116-124, 129-157, 178-281, 288-301, 315-332, 338-354, 601-602, 612-613, 623-624, 637, 649, 661, 671, 684, 689, 716-717, 732-735, 763, 794, 810, 813-814, 817-818, 833 /home/admin/.local/lib/python3.8/site-packages/requests/status_codes.py 14 0 100% /home/admin/.local/lib/python3.8/site-packages/requests/structures.py 39 11 72% 55, 65, 68-73, 77, 80, 91, 96, 99 /home/admin/.local/lib/python3.8/site-packages/requests/utils.py 485 315 35% 76-121, 127-130, 141, 144-157, 170-191, 204, 216-220, 223-224, 230-253, 274-297, 303-310, 331-337, 358, 361, 393-398, 424-433, 445-459, 469-474, 485, 493-506, 548, 556, 566-577, 582-587, 602-626, 643-655, 674-678, 689-693, 703-704, 711-715, 724-739, 752-753, 758-761, 784, 789-809, 815-816, 819, 831, 845, 856-857, 873-886, 920-946, 962-984, 993-1013, 1038-1040, 1044-1056, 1068-1076, 1083-1094 /home/admin/.local/lib/python3.8/site-packages/seaborn/__init__.py 16 0 100% /home/admin/.local/lib/python3.8/site-packages/seaborn/_core.py 638 564 12% 48, 52-54, 58, 62-65, 90-138, 142-159, 163-174, 180-211, 215-254, 273-314, 318-325, 329-338, 342-399, 403-478, 498-546, 550-554, 558-577, 604-615, 621-627, 632, 647-653, 657-681, 706-821, 850-935, 963-1016, 1021-1058, 1062-1073, 1091-1161, 1165-1178, 1186-1191, 1218-1273, 1304-1348, 1369-1399, 1418-1445, 1467-1484 /home/admin/.local/lib/python3.8/site-packages/seaborn/_decorators.py 31 7 77% 32-46 /home/admin/.local/lib/python3.8/site-packages/seaborn/_docstrings.py 36 1 97% 30 /home/admin/.local/lib/python3.8/site-packages/seaborn/_statistics.py 196 168 14% 69-79, 83-87, 91-96, 100-114, 118-126, 130-140, 144-158, 162-182, 186-189, 232-241, 245-259, 263-312, 316-342, 346-366, 370-373, 389-391, 395, 399-413, 417-426 /home/admin/.local/lib/python3.8/site-packages/seaborn/algorithms.py 66 60 9% 36-86, 91-105, 114-129 /home/admin/.local/lib/python3.8/site-packages/seaborn/axisgrid.py 1011 915 9% 38-43, 47-50, 54-56, 60-64, 95-176, 180-183, 187-196, 200-226, 231-234, 309-474, 581-606, 632-688, 720-755, 759-763, 768-779, 783-785, 791-799, 803-804, 808-815, 819-826, 830-837, 841-853, 857-865, 890-957, 964, 969, 974-980, 991, 998-1011, 1016-1023, 1028-1035, 1040-1052, 1057-1069, 1145-1250, 1263-1267, 1280-1282, 1295-1297, 1310-1321, 1335-1406, 1411-1447, 1454-1469, 1473-1508, 1512-1553, 1557-1562, 1566-1570, 1591-1669, 1673-1676, 1700-1702, 1724-1738, 1761-1799, 1820-1822, 1830-1831, 1962-2049, 2064-2214 /home/admin/.local/lib/python3.8/site-packages/seaborn/categorical.py 1249 1116 11% 44-240, 245-265, 269-324, 329-337, 342-346, 350-388, 392-397, 406-415, 419-476, 481-505, 509-512, 522-546, 551-671, 675-686, 690-692, 702-714, 718-724, 728-747, 752-757, 761-935, 939-946, 954-979, 987-995, 1001-1010, 1015-1016, 1021-1039, 1043-1046, 1057-1082, 1086-1088, 1099-1112, 1116-1156, 1160-1164, 1172-1177, 1184-1192, 1196-1209, 1215-1242, 1249-1276, 1280-1298, 1303-1332, 1336-1416, 1420-1424, 1434-1438, 1442-1545, 1550-1571, 1584-1593, 1598-1630, 1639-1642, 1655-1687, 1692-1697, 1702-1781, 1788-1791, 1805-1839, 1844-1874, 1878-1883, 1887-1890, 1896-1999, 2003-2058, 2062-2065, 2240-2249, 2397-2406, 2631-2640, 2799-2820, 2996-3017, 3179-3188, 3372-3381, 3577-3608, 3708-3724, 3743-3862 /home/admin/.local/lib/python3.8/site-packages/seaborn/cm.py 16 0 100% /home/admin/.local/lib/python3.8/site-packages/seaborn/colors/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/seaborn/colors/crayons.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/seaborn/colors/xkcd_rgb.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/seaborn/distributions.py 923 859 7% 109, 118, 124-126, 132, 140-155, 164-176, 180-186, 192-200, 204-210, 215-268, 284-329, 353-713, 728-873, 889-1031, 1050-1215, 1221-1279, 1285-1322, 1328-1358, 1391-1456, 1618-1754, 1922-1956, 2044-2082, 2147-2302, 2395-2403, 2543-2661 /home/admin/.local/lib/python3.8/site-packages/seaborn/external/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/seaborn/external/docscrape.py 455 272 40% 43, 64, 80, 100, 119, 122, 127-130, 173-175, 182, 187, 190, 201, 236, 238, 250-253, 308-350, 358-369, 374, 382-385, 391, 404-405, 407-408, 415, 421-429, 432-443, 448, 451-454, 457-460, 463-466, 469-472, 475-488, 491-496, 499-528, 531-546, 549-563, 567-571, 580, 585-609, 612-617, 620-634, 643-691, 695-697, 705-707, 714-718 /home/admin/.local/lib/python3.8/site-packages/seaborn/external/husl.py 194 151 22% 32, 36, 40, 44, 48, 52, 56, 60, 64, 68, 72-91, 95-114, 118-119, 123, 127-130, 134-137, 141-144, 148-153, 157-175, 179-184, 188-189, 193-194, 198-199, 203-219, 223-235, 239-247, 251-257, 261-271, 275-285, 289-299, 303-313 /home/admin/.local/lib/python3.8/site-packages/seaborn/matrix.py 548 491 10% 25-28, 33-36, 41-49, 61-86, 98-182, 189-239, 243-255, 259-268, 272-284, 289-343, 535-549, 563-616, 619-621, 624-638, 643-651, 666, 672, 683-728, 774-780, 790-857, 861-899, 906-919, 939-949, 974-986, 990-1004, 1033-1055, 1058-1060, 1065-1085, 1100-1150, 1153-1207, 1214-1235, 1402-1408 /home/admin/.local/lib/python3.8/site-packages/seaborn/miscplot.py 27 20 26% 20-30, 35-48 /home/admin/.local/lib/python3.8/site-packages/seaborn/palettes.py 231 199 14% 64-67, 71-72, 76-77, 81-90, 145-226, 287-297, 359-371, 431-454, 459-467, 543-548, 624-629, 702-709, 729-735, 761-762, 789-790, 905-942, 948-977, 1021-1038 /home/admin/.local/lib/python3.8/site-packages/seaborn/rcmod.py 113 83 27% 113-117, 122, 127, 132-135, 174-298, 330-331, 378-443, 483-484, 489-491, 494, 497-501, 548-556 /home/admin/.local/lib/python3.8/site-packages/seaborn/regression.py 319 271 15% 13-14, 36-56, 60-66, 69, 86-136, 141-153, 158-188, 193-229, 233-248, 252-265, 269-290, 294-296, 300-317, 321-331, 335-340, 345-376, 385-408, 413-425, 576-636, 826-839, 1071-1096 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/home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/eventwebhook/__init__.py 14 6 57% 19, 30, 46-50 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/eventwebhook/eventwebhook_header.py 5 1 80% 10 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/__init__.py 63 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/amp_html_content.py 25 14 44% 14-18, 26, 34, 43-44, 53-59 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/asm.py 33 20 39% 16-23, 31, 40-43, 52, 62-65, 74-80 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/attachment.py 75 47 37% 43-62, 70, 79-82, 90, 99-102, 110, 119-122, 137, 162-165, 176, 191-194, 203-218 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/batch_id.py 15 7 53% 14-17, 25, 34, 41, 50 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/bcc_email.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/bcc_settings.py 27 16 41% 16-23, 31, 40, 48, 57, 66-72 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/bcc_settings_email.py 13 6 54% 11-14, 22, 31, 40 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/bypass_bounce_management.py 16 9 44% 16-19, 27, 36, 45-48 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/bypass_list_management.py 16 9 44% 16-19, 27, 36, 45-48 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/bypass_spam_management.py 16 9 44% 15-18, 26, 35, 44-47 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/bypass_unsubscribe_management.py 16 9 44% 17-20, 28, 37, 46-49 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/category.py 13 6 54% 10-13, 21, 31, 40 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/cc_email.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/click_tracking.py 27 16 41% 12-19, 27, 36, 45, 56, 65-71 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/content.py 30 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/content_id.py 13 6 54% 13-16, 27, 41, 50 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/custom_arg.py 34 19 44% 21-30, 38, 47, 55, 64, 72, 82, 91-94 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/disposition.py 13 6 54% 21-24, 39, 63, 72 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/dynamic_template_data.py 24 12 50% 16-22, 30, 39, 47, 57, 64, 73 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/email.py 79 13 84% 50-54, 78, 137, 154, 171, 189, 202-203, 209, 224 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/exceptions.py 22 10 55% 24-31, 39, 48, 56, 65 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/file_content.py 13 6 54% 10-13, 21, 30, 39 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/file_name.py 13 6 54% 10-13, 21, 30, 39 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/file_type.py 13 6 54% 10-13, 21, 30, 39 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/footer_html.py 13 6 54% 10-13, 21, 30, 39 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/footer_settings.py 38 23 39% 14-25, 33, 42, 50, 59, 67, 76, 85-94 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/footer_text.py 13 6 54% 10-13, 21, 30, 39 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/from_email.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/ganalytics.py 63 35 44% 26-38, 48-49, 57, 66, 75, 86, 94, 103, 111, 120, 128, 137, 145, 154, 163-176 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/group_id.py 13 6 54% 10-13, 21, 30, 39 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/groups_to_display.py 15 8 47% 13-16, 25, 37-39, 48 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/header.py 34 19 44% 21-30, 38, 47, 55, 64, 72, 82, 91-94 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/html_content.py 25 14 44% 14-18, 26, 34, 43-44, 53-59 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/ip_pool_name.py 13 6 54% 11-14, 22, 31, 40 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/mail.py 470 245 48% 72, 78, 88, 151-167, 171, 177-178, 183-187, 213, 229-241, 259-268, 273, 280, 296-308, 324-330, 335, 356-368, 388-394, 416-431, 445, 454-458, 466-490, 494, 503-507, 515-535, 547, 557-561, 569-592, 612-629, 633, 642-653, 674, 692-696, 708, 717-721, 737-748, 752, 768, 777-781, 789, 806-809, 821, 829-833, 841, 853, 861-865, 872, 889, 906, 923, 940, 957, 997-1013 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/mail_settings.py 93 58 38% 38-69, 77, 86, 94, 103, 111, 120, 128, 137, 145, 154, 162, 171, 179, 188, 196, 206, 215-243 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/mime_type.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/open_tracking.py 27 16 41% 16-23, 31, 40, 50, 65, 74-80 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/open_tracking_substitution_tag.py 13 6 54% 12-15, 26, 39, 49 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/personalization.py 130 38 71% 23-29, 55, 63-67, 70, 73-76, 90, 98, 110, 118, 133, 145, 152, 164, 171-174, 186, 193, 207, 220-223, 242, 247-250 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/plain_text_content.py 25 14 44% 15-19, 27, 35, 44-45, 54-60 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/reply_to.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/sandbox_mode.py 16 9 44% 12-15, 23, 32, 41-44 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/section.py 25 14 44% 12-18, 26, 35, 43, 52, 61-64 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/send_at.py 24 12 50% 22-28, 36, 45, 53, 63, 70, 79 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/spam_check.py 44 27 39% 18-27, 35, 44, 54, 68-71, 80, 91-94, 103-112 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/spam_threshold.py 13 6 54% 15-18, 29, 44, 53 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/spam_url.py 13 6 54% 12-15, 24, 35, 44 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/subject.py 23 4 83% 18, 43, 53, 60 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/subscription_html.py 13 6 54% 12-15, 24, 36, 45 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/subscription_substitution_tag.py 13 6 54% 18-21, 32, 48, 58 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/subscription_text.py 13 6 54% 12-15, 24, 36, 45 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/subscription_tracking.py 49 30 39% 21-33, 41, 50, 59, 71, 80, 92, 103, 120, 129-142 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/substitution.py 34 19 44% 17-26, 34, 43, 51, 60, 68, 78, 87-90 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/template_id.py 13 6 54% 10-13, 21, 30, 39 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/to_email.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/tracking_settings.py 49 30 39% 30-45, 53, 63, 71, 81, 89, 98, 106, 115, 124-134 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/utm_campaign.py 13 6 54% 11-14, 22, 31, 40 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/utm_content.py 13 6 54% 11-14, 22, 31, 40 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/utm_medium.py 13 6 54% 11-14, 22, 31, 40 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/utm_source.py 13 6 54% 11-14, 23, 34, 43 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/utm_term.py 13 6 54% 11-14, 22, 31, 40 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/mail/validators.py 27 10 63% 23-24, 46-55, 69 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/stats/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/stats/stats.py 166 108 35% 12-22, 29, 38-53, 61, 70, 78, 87, 95, 104, 112, 121, 129, 138, 146, 155, 163, 172, 187-194, 202-220, 228, 236-238, 253-260, 268-286, 294, 302-304, 317-319, 327, 336, 344, 357-359, 367, 376, 384 /home/admin/.local/lib/python3.8/site-packages/sendgrid/sendgrid.py 7 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/twilio_email.py 9 4 56% 63-73 /home/admin/.local/lib/python3.8/site-packages/sendgrid/version.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/__check_build/__init__.py 18 12 33% 19-31, 45-46 /home/admin/.local/lib/python3.8/site-packages/sklearn/__init__.py 29 9 69% 69, 103-112 /home/admin/.local/lib/python3.8/site-packages/sklearn/_config.py 21 13 38% 75-82, 144-150 /home/admin/.local/lib/python3.8/site-packages/sklearn/_distributor_init.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/_loss/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/_loss/glm_distribution.py 86 54 37% 59-66, 132, 156, 175, 204, 208, 215-235, 246, 272-323, 329, 335, 341, 347 /home/admin/.local/lib/python3.8/site-packages/sklearn/base.py 259 142 45% 54-88, 108-138, 159, 169, 197-198, 221-244, 265-291, 304, 310, 322, 325-333, 362, 365, 413-419, 424-434, 449-453, 460, 464-467, 499-500, 503, 552-554, 557, 583-584, 587, 599, 619-621, 639-640, 662-665, 697-702, 724, 750, 761, 767, 784, 800, 816, 840-857 /home/admin/.local/lib/python3.8/site-packages/sklearn/cluster/__init__.py 10 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/cluster/_affinity_propagation.py 142 119 16% 22-32, 119-254, 370-377, 385, 388, 409-434, 450-463, 485 /home/admin/.local/lib/python3.8/site-packages/sklearn/cluster/_agglomerative.py 337 242 28% 42-80, 90-131, 221, 228, 240-241, 245-342, 423-603, 608-609, 613-614, 618-619, 658, 838, 842, 848, 852, 857, 864-866, 874-880, 888-889, 907, 910, 920-924, 946, 1077-1082, 1098-1105, 1109 /home/admin/.local/lib/python3.8/site-packages/sklearn/cluster/_bicluster.py 178 145 19% 35-47, 58-69, 74-83, 93-100, 103-105, 119-126, 133-164, 167-179, 291, 301-315, 444-454, 457-481, 486-520, 532-540, 544-546 /home/admin/.local/lib/python3.8/site-packages/sklearn/cluster/_birch.py 231 194 16% 27-37, 50-89, 140-152, 155-164, 171-175, 179-242, 281-290, 293-297, 303-315, 320-321, 437-441, 460-461, 464-518, 529-534, 555-561, 564-568, 588-595, 614-617, 623-659 /home/admin/.local/lib/python3.8/site-packages/sklearn/cluster/_dbscan.py 52 37 29% 141-145, 276-283, 310-361, 389-390 /home/admin/.local/lib/python3.8/site-packages/sklearn/cluster/_feature_agglomeration.py 19 12 37% 38-51, 70-73 /home/admin/.local/lib/python3.8/site-packages/sklearn/cluster/_kmeans.py 526 454 14% 85-144, 152-158, 289-298, 354-428, 484-541, 579-601, 771-781, 785-844, 848-853, 858-861, 869-887, 924-951, 979-1052, 1077, 1105, 1124-1127, 1131, 1154-1160, 1183-1189, 1193, 1264-1337, 1346-1403, 1571-1579, 1585, 1591, 1597, 1600-1633, 1660-1781, 1805-1813, 1835-1891, 1914-1917, 1920, 1988-2019 /home/admin/.local/lib/python3.8/site-packages/sklearn/cluster/_mean_shift.py 116 94 19% 68-86, 92-109, 186-191, 223-240, 358-364, 377-450, 465-468 /home/admin/.local/lib/python3.8/site-packages/sklearn/cluster/_optics.py 218 193 11% 210-222, 246-287, 291-298, 327-338, 448-503, 509-538, 571-578, 631-646, 690-709, 716-722, 736-744, 790-898, 920-927 /home/admin/.local/lib/python3.8/site-packages/sklearn/cluster/_spectral.py 120 96 20% 76-158, 260-284, 462-476, 499-544, 568, 571, 580 /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/__init__.py 12 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/_base.py 47 28 40% 37-44, 57-77, 131, 154-158 /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/_dict_learning.py 359 309 14% 27-28, 113-191, 297-354, 394-435, 547-632, 766-891, 899-905, 910-926, 945-946, 1066-1071, 1089, 1096, 1115, 1118, 1122, 1126, 1304-1318, 1336-1358, 1546-1560, 1578-1599, 1623-1650 /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/_factor_analysis.py 139 119 14% 155-167, 183-264, 282-294, 306-310, 320-339, 354-362, 379, 384-390, 396-414 /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/_fastica.py 181 154 15% 49-50, 57-60, 69-95, 104-122, 128-136, 140-143, 147, 272-301, 399-411, 431-540, 557, 574-575, 593-600, 617-624 /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/_incremental_pca.py 88 76 14% 170-173, 191-216, 237-319, 350-358 /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/_kernel_pca.py 106 80 25% 151-168, 176, 179-185, 192-256, 259-267, 283-295, 310-318, 331-344, 361-369, 372 /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/_lda.py 238 208 13% 75-132, 303-318, 322-335, 341-362, 396-426, 456-476, 479, 491-494, 510-537, 556-609, 624-640, 658-664, 692-740, 757-763, 787-813, 837 /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/_nmf.py 422 383 9% 38, 51, 55-61, 91-167, 172-187, 192-203, 207-233, 238-248, 311-401, 413-432, 508-538, 544-633, 638-715, 789-850, 1022-1093, 1268-1279, 1282, 1307-1326, 1342-1343, 1358-1374, 1391-1392 /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/_pca.py 164 92 44% 59-97, 105-109, 376-386, 394, 402-405, 414, 416, 424-427, 435-436, 439, 445, 468, 476-477, 484, 500-564, 583-592, 613, 616 /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/_sparse_pca.py 68 52 24% 116-126, 144-175, 198-206, 309-316, 334-362 /home/admin/.local/lib/python3.8/site-packages/sklearn/decomposition/_truncated_svd.py 58 39 33% 125-129, 146-147, 164-208, 223-225, 242-243, 246 /home/admin/.local/lib/python3.8/site-packages/sklearn/exceptions.py 15 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/isotonic.py 109 84 23% 56-76, 117-131, 222-225, 228-231, 237-247, 252-295, 325-342, 361-385, 400, 404-407, 414-416, 419 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/__init__.py 17 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_base.py 207 160 23% 81-101, 124-179, 197-207, 218-221, 238, 245-249, 252, 282-293, 309-314, 323-330, 353-357, 385-388, 485-489, 514-575, 588-642 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_bayes.py 203 180 11% 162-174, 197-300, 324-332, 343-356, 361-386, 515-526, 546-633, 641-650, 656-661, 685-694 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_coordinate_descent.py 492 409 17% 58-75, 124-168, 311, 440-551, 706-717, 751-874, 879, 893-898, 1031, 1085-1146, 1157-1171, 1200-1356, 1518, 1526, 1529, 1532, 1725-1740, 1743, 1746, 1749, 1880-1889, 1913-1958, 1961, 2078-2087, 2263-2276, 2279, 2282, 2285, 2444, 2452, 2455, 2458 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_glm/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_glm/glm.py 158 122 23% 32-35, 40-48, 133-141, 161-298, 313-317, 333-335, 371-376, 380-388, 458, 465, 469-470, 540, 547, 551-552, 654, 664-666, 670-673 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_glm/link.py 40 13 68% 68, 71, 74, 77, 84, 87, 90, 93, 100, 103, 106, 109-110 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_huber.py 88 74 16% 52-122, 229-234, 255-307 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_least_angle.py 435 384 12% 166-171, 301, 442-798, 917-926, 930-936, 940-994, 1017-1035, 1177-1188, 1195-1197, 1283-1310, 1438-1442, 1449, 1467-1529, 1685-1695, 1823-1832, 1835, 1858-1904 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py 546 500 8% 75-82, 114-133, 162-169, 202-246, 286-302, 343-355, 396-428, 432-458, 462-475, 632-819, 957-1009, 1261-1275, 1306-1435, 1463-1478, 1499, 1751-1767, 1789-2062, 2085-2088, 2091 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_omp.py 273 245 10% 72-138, 194-264, 349-408, 490-544, 632-636, 655-687, 735-764, 870-876, 894-919 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_passive_aggressive.py 34 20 41% 173-191, 216-228, 254-256, 401-418, 435-437, 464-466 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_perceptron.py 6 1 83% 164 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_ransac.py 153 133 13% 47-54, 215-226, 256-464, 480-482, 502-504, 507 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_ridge.py 614 520 15% 41-114, 118-132, 137-156, 161-217, 221-228, 232-235, 366, 385-518, 527-534, 539-600, 737, 762, 895-899, 924-946, 950, 954-966, 982-984, 995-999, 1002-1003, 1008, 1014, 1025-1029, 1032-1040, 1043-1050, 1057, 1060, 1070, 1073, 1122-1130, 1135, 1140-1143, 1176-1192, 1223-1236, 1261-1276, 1281-1290, 1297-1313, 1319-1338, 1347-1355, 1370-1385, 1394-1397, 1402-1412, 1421-1433, 1454-1581, 1590-1597, 1627-1665, 1917-1920, 1943-1959, 1963, 1966 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_sag.py 75 63 16% 67-85, 234-344 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_stochastic_gradient.py 446 345 23% 56-62, 65-68, 80-102, 117-119, 127-156, 160-168, 171-174, 178-182, 187-241, 258-281, 285-288, 298, 307, 315, 323, 331-355, 413-450, 478-488, 494-535, 539-578, 583-605, 616-649, 684-695, 729, 975, 986-987, 1027-1028, 1031-1069, 1096-1097, 1100, 1103, 1129, 1141-1166, 1192-1193, 1201-1225, 1252, 1270-1276, 1290, 1294-1363, 1582, 1593 /home/admin/.local/lib/python3.8/site-packages/sklearn/linear_model/_theil_sen.py 113 89 21% 57-74, 112-128, 147, 178-193, 298-306, 309-343, 359-400 /home/admin/.local/lib/python3.8/site-packages/sklearn/manifold/__init__.py 6 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/manifold/_isomap.py 54 38 30% 131-141, 144-169, 190-193, 211-212, 229-230, 254-272 /home/admin/.local/lib/python3.8/site-packages/sklearn/manifold/_locally_linear.py 225 201 11% 49-73, 108-114, 159-189, 292-521, 644-655, 658-665, 688-689, 705-706, 725-734 /home/admin/.local/lib/python3.8/site-packages/sklearn/manifold/_mds.py 111 89 20% 71-132, 234-276, 379-387, 390, 398, 418-419, 439-461 /home/admin/.local/lib/python3.8/site-packages/sklearn/manifold/_spectral_embedding.py 179 148 17% 52-72, 89-95, 120-141, 221-360, 463-469, 472, 481, 503-536, 560-579, 601-602 /home/admin/.local/lib/python3.8/site-packages/sklearn/manifold/_t_sne.py 258 224 13% 58-64, 94-121, 163-193, 255-272, 345-401, 453-477, 664-679, 684-841, 854-910, 932-934, 950-951 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/__init__.py 78 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/_base.py 78 71 9% 67-131, 175-202, 234-251 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/_classification.py 511 452 12% 48-52, 83-128, 132-137, 202-210, 296-355, 456-557, 618-639, 758-785, 852-875, 935-946, 1068, 1192-1200, 1214-1247, 1251-1261, 1269-1299, 1458-1540, 1653-1660, 1771-1778, 1846-1858, 1966-2060, 2135-2152, 2225-2281, 2365-2403, 2477-2506 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/_plot/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/_plot/base.py 37 33 11% 26-45, 81-114 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/_plot/confusion_matrix.py 61 47 23% 71-72, 107-162, 255-272 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/_plot/det_curve.py 44 36 18% 65-68, 88-129, 210-229 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/_plot/precision_recall_curve.py 47 35 26% 77-81, 107-140, 203-225 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/_plot/roc_curve.py 47 35 26% 73-77, 100-132, 210-230 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/_ranking.py 336 292 13% 83-106, 199-224, 294-317, 326-349, 522-547, 595-648, 688-730, 811-823, 913-956, 1005-1046, 1090-1106, 1149-1191, 1238-1250, 1290-1299, 1303-1307, 1407-1411, 1458-1466, 1564-1569, 1646-1717 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/_regression.py 168 137 18% 88-122, 182-194, 257-271, 335-351, 408-416, 477-492, 552-584, 676-723, 753-756, 808-821, 857, 896 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/_scorer.py 226 132 42% 52-60, 77, 81-92, 107-122, 133-134, 155-166, 169-171, 199, 204, 236-242, 276-288, 291, 326-362, 365, 383-392, 397, 426-459, 485-530, 614 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/cluster/__init__.py 20 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/cluster/_bicluster.py 32 22 31% 12-17, 22-28, 38-45, 80-86 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/cluster/_supervised.py 170 139 18% 43-69, 74-83, 127-149, 214-229, 289-299, 383-389, 453-473, 542, 611, 710, 768-798, 889-919, 998-1020, 1091-1100, 1115-1123 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/cluster/_unsupervised.py 93 76 18% 33-34, 109-117, 135-149, 214-248, 281-298, 339-363 /home/admin/.local/lib/python3.8/site-packages/sklearn/metrics/pairwise.py 412 339 18% 45-61, 135-164, 194-198, 272-323, 399-439, 451-508, 512-514, 587-601, 670-673, 722-723, 782-804, 833-841, 861-862, 880-886, 910-911, 967-978, 1004-1005, 1033-1041, 1067-1075, 1101-1108, 1136-1142, 1180-1191, 1241-1251, 1296-1298, 1342, 1347, 1354-1373, 1379-1405, 1422-1434, 1443-1470, 1594-1635, 1747-1790, 1845, 1937-1954 /home/admin/.local/lib/python3.8/site-packages/sklearn/model_selection/__init__.py 32 1 97% 37 /home/admin/.local/lib/python3.8/site-packages/sklearn/model_selection/_search.py 342 251 27% 96-116, 127-136, 141-142, 160-184, 244-265, 268, 274-306, 310-314, 380-386, 390-406, 421-429, 433, 437, 450, 473-489, 510-511, 514-523, 539-540, 556-557, 573-574, 590-591, 607-608, 624-625, 631-639, 643-644, 704, 708-721, 747-892, 896-968, 1278-1284, 1288, 1608-1611, 1619 /home/admin/.local/lib/python3.8/site-packages/sklearn/model_selection/_split.py 467 353 24% 78-83, 92-95, 99, 106, 155-161, 183-185, 235, 238-245, 262-264, 273-298, 324-333, 354, 428, 432-444, 499, 502-536, 562, 636, 640-690, 693-695, 731-732, 831-834, 859-887, 934-944, 968-971, 997, 1057, 1060-1075, 1099-1102, 1128, 1156-1169, 1195-1202, 1226-1229, 1232, 1284, 1340, 1350-1354, 1386-1388, 1413, 1416, 1484-1489, 1492-1503, 1575-1580, 1583-1594, 1626, 1691-1696, 1699-1757, 1793-1794, 1803-1864, 1906-1909, 1933-1937, 1941-1945, 1966, 1972, 1993, 2017-2018, 2058-2073, 2168-2199, 2211-2241, 2250-2252 /home/admin/.local/lib/python3.8/site-packages/sklearn/model_selection/_validation.py 380 335 12% 231-279, 288-304, 309-313, 438-446, 543-657, 666-709, 838-892, 937-964, 980-1021, 1039-1045, 1165-1182, 1189-1197, 1202-1209, 1353-1417, 1444-1476, 1483-1518, 1625-1645, 1671 /home/admin/.local/lib/python3.8/site-packages/sklearn/neighbors/__init__.py 14 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/neighbors/_base.py 443 394 11% 61-66, 86-111, 135-139, 160-197, 223-248, 274-296, 307-315, 318-358, 361-525, 529, 538, 547, 581-594, 649-765, 816-846, 855, 889-901, 978-1083, 1139-1170 /home/admin/.local/lib/python3.8/site-packages/sklearn/neighbors/_classification.py 158 136 14% 153-159, 179, 195-221, 239-275, 414-421, 441-487, 504-529, 548-616 /home/admin/.local/lib/python3.8/site-packages/sklearn/neighbors/_graph.py 60 35 42% 16-21, 29-36, 106-113, 187-194, 307-311, 327, 345-347, 371, 374, 490-494, 510, 528-529, 553, 556 /home/admin/.local/lib/python3.8/site-packages/sklearn/neighbors/_kde.py 86 66 23% 101-119, 124-139, 164-179, 197-211, 233, 256-283, 286 /home/admin/.local/lib/python3.8/site-packages/sklearn/neighbors/_lof.py 80 54 32% 184-190, 218-223, 246, 265-299, 320-327, 346-356, 384-393, 421, 450-458, 486-498, 521-526 /home/admin/.local/lib/python3.8/site-packages/sklearn/neighbors/_nca.py 157 129 18% 169-176, 197-244, 265-268, 304-377, 400-443, 453-456, 483-524, 527 /home/admin/.local/lib/python3.8/site-packages/sklearn/neighbors/_nearest_centroid.py 70 54 23% 91-92, 107-181, 202-205 /home/admin/.local/lib/python3.8/site-packages/sklearn/neighbors/_regression.py 62 40 35% 152-157, 161, 170, 190, 206-229, 352-358, 378, 395-426 /home/admin/.local/lib/python3.8/site-packages/sklearn/neighbors/_unsupervised.py 10 2 80% 118, 142 /home/admin/.local/lib/python3.8/site-packages/sklearn/preprocessing/__init__.py 28 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/preprocessing/_data.py 810 681 16% 71-80, 161-217, 323-325, 335-341, 362-363, 386-417, 432-441, 456-463, 466, 545-561, 683-685, 695-699, 726-727, 762-860, 877-897, 914-937, 940, 1007, 1017-1020, 1040-1041, 1065-1085, 1100-1110, 1125-1134, 1137, 1198-1215, 1319-1323, 1344-1387, 1402-1416, 1431-1444, 1447, 1536-1555, 1632-1635, 1639-1641, 1646-1651, 1668-1681, 1701-1708, 1739-1837, 1891-1937, 2001-2002, 2023-2024, 2043-2045, 2048, 2083-2098, 2157-2158, 2179-2180, 2200-2205, 2208, 2253, 2272-2282, 2299-2310, 2313, 2321, 2350-2378, 2484-2489, 2499-2519, 2531-2568, 2589-2625, 2630-2694, 2699-2717, 2737-2750, 2768-2771, 2789-2793, 2796, 2920-2931, 3020-3022, 3043-3044, 3047, 3050-3077, 3092-3106, 3139-3152, 3158-3163, 3169-3185, 3192-3207, 3217-3219, 3228-3243, 3267-3290, 3293, 3394-3395 /home/admin/.local/lib/python3.8/site-packages/sklearn/preprocessing/_discretization.py 117 102 13% 131-134, 153-237, 242-271, 288-318, 337-353 /home/admin/.local/lib/python3.8/site-packages/sklearn/preprocessing/_encoders.py 272 241 11% 42-67, 70-74, 77-110, 113-156, 159, 318-322, 325-333, 339-397, 416-420, 442-443, 459-505, 524-600, 617-635, 721-724, 743-771, 787-793, 809-844 /home/admin/.local/lib/python3.8/site-packages/sklearn/preprocessing/_function_transformer.py 41 26 37% 11, 91-97, 100-102, 106-109, 128-132, 147, 162, 166-171, 174 /home/admin/.local/lib/python3.8/site-packages/sklearn/preprocessing/_label.py 274 229 16% 100-102, 116-118, 132-138, 152-163, 166, 262-274, 289-298, 321, 343-350, 387-403, 406, 471-569, 577-613, 619-657, 725-726, 742-754, 773-798, 816-824, 827-831, 847-864, 881-898, 902 /home/admin/.local/lib/python3.8/site-packages/sklearn/svm/__init__.py 3 0 100% 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970-979, 1197, 1247-1252, 1271-1277, 1511, 1732 /home/admin/.local/lib/python3.8/site-packages/sklearn/tree/_export.py 377 339 10% 44-70, 75, 181-194, 203-214, 218-237, 241-262, 266-366, 376-406, 412-427, 431-436, 439-463, 466-524, 534-560, 565-574, 577-625, 628-662, 769-795, 802-815, 876-972 /home/admin/.local/lib/python3.8/site-packages/sklearn/tree/_reingold_tilford.py 131 110 16% 9-22, 25, 28, 31-38, 41-44, 48, 51, 54-56, 60-64, 68-70, 74-95, 99-132, 136-144, 148-154, 162-165, 169-178, 183-188 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/__init__.py 366 299 18% 84, 87, 90, 93-96, 107, 125-132, 165-167, 172-179, 184-193, 198-205, 224-268, 312-346, 355-409, 502-563, 631, 651-661, 668-672, 708-722, 755-768, 778-783, 817-819, 845-851, 868-878, 898-903, 933-944, 1019-1045, 1059-1062, 1080-1084, 1113-1182 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/_arpack.py 5 3 40% 28-30 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/_encode.py 115 99 14% 30-50, 60-65, 84-102, 108-112, 115-117, 122-123, 128-144, 176-187, 215-269 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/_estimator_html_repr.py 76 62 18% 39-50, 53, 61-76, 82-102, 111-143, 303-311 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/_joblib.py 12 0 100% /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/_mask.py 20 14 30% 9-21, 41-54 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/_pprint.py 243 172 29% 79, 99, 101, 105, 185-199, 203, 207, 222-268, 276-317, 323-332, 354-379, 383-413, 418, 420, 427, 441, 446-447 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/_show_versions.py 33 26 21% 24-32, 44-73, 82-93 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/_tags.py 16 13 19% 50-67 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/class_weight.py 61 55 10% 41-72, 115-181 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/deprecation.py 56 11 80% 67-68, 86-87, 101-102, 117-123 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/home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/module_attachment_pb2.py 13 0 100% /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/module_def_pb2.py 17 0 100% /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/module_impl.py 17 6 65% 46, 50-52, 57, 62 /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/module_spec.py 39 20 49% 40, 74-78, 83, 88, 109, 129, 162-171, 185, 200 /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/module_v2.py 20 5 75% 91, 96, 99-103 /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/native_module.py 440 365 17% 50-54, 58-82, 124, 127-131, 134-136, 139-151, 212-233, 262-278, 325-328, 348-354, 359, 362-363, 366-367, 370-371, 374-380, 383, 386-387, 402-411, 428-451, 454-468, 483-532, 536-632, 636-643, 648, 653-654, 669-670, 676-688, 693-707, 719, 727-732, 750-759, 776-816, 821-826, 831-835, 841, 854-863, 921-922, 945-947, 951-959, 963-967, 983-1017, 1036-1089, 1094-1111, 1116-1128, 1133-1153, 1158-1173, 1177-1178 /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/registry.py 21 5 76% 22-23, 41, 52-54 /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/resolver.py 199 100 50% 132-135, 145-156, 164-174, 178, 190-199, 204, 209, 219-227, 249-252, 257-258, 268-273, 278-283, 302-335, 380-426, 436-437, 442-445, 462, 476, 485, 488-490, 506-510, 514, 518-521 /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/saved_model_lib.py 205 160 22% 53, 60, 66-75, 79, 86-91, 107-119, 123-126, 133-138, 148, 155-161, 180-192, 197-198, 203-208, 223-240, 263-321, 359, 363-372, 375, 379-382, 386, 390, 394, 405-411, 415-423, 426-429, 432-437, 440-443, 451-458, 463-467 /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/saved_model_module.py 16 9 44% 46-49, 86-93 /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/tensor_info.py 134 107 20% 35-41, 45, 50-56, 61-67, 75, 80, 85, 89, 93-97, 102-115, 132, 139-144, 161-185, 202-206, 223-243, 262-281, 298-307 /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/tf_utils.py 89 60 33% 32-34, 68-70, 98-115, 132-133, 150-165, 182-195, 227, 232-236, 241-249, 253-258 /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/tools/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/uncompressed_module_resolver.py 37 24 35% 32-34, 37, 41-47, 65-77, 80-87 /home/admin/.local/lib/python3.8/site-packages/tensorflow_hub/version.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/_VF.py 11 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/__config__.py 7 3 57% 9, 16, 20 /home/admin/.local/lib/python3.8/site-packages/torch/__future__.py 5 1 80% 16 /home/admin/.local/lib/python3.8/site-packages/torch/__init__.py 362 162 55% 20, 27, 59-142, 148, 175-188, 207, 214-231, 262-278, 298, 307, 329-331, 377, 502, 508, 515, 533-555, 565-571, 577, 622, 634, 640, 664, 669, 674, 679, 684, 689, 694, 699, 704, 709, 714, 719, 724, 729, 734, 739, 744, 768, 772, 789, 829-833, 896, 949-954 /home/admin/.local/lib/python3.8/site-packages/torch/_classes.py 25 11 56% 6-7, 10-13, 22-24, 28, 48 /home/admin/.local/lib/python3.8/site-packages/torch/_jit_internal.py 591 404 32% 35, 41-43, 59-111, 141-161, 168-174, 227-241, 247-258, 275-289, 297-311, 331-381, 391-404, 414-423, 426-427, 435, 550-556, 564, 567, 639-660, 668-674, 681-684, 688-689, 693, 696, 700-704, 707-710, 738-739, 748-752, 760, 763-766, 780, 783, 832, 840-855, 859-865, 870-875, 880-885, 890-893, 898-910, 913-919, 926-932, 935-940, 943, 990, 993, 998-1001, 1005, 1011, 1016, 1027-1028, 1035, 1042, 1049-1051, 1055-1070, 1075-1080, 1084-1087, 1091-1096, 1099-1101, 1104-1110, 1118, 1122, 1126-1133, 1137-1138, 1148-1206, 1210-1229, 1234-1235, 1238-1257, 1267-1270 /home/admin/.local/lib/python3.8/site-packages/torch/_linalg_utils.py 49 35 29% 13-19, 26-29, 38-42, 50-52, 58-59, 65, 71, 77, 83-88, 94-101, 106 /home/admin/.local/lib/python3.8/site-packages/torch/_lobpcg.py 424 387 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523-525, 529-540, 550, 558, 561, 564-568, 575-577 /home/admin/.local/lib/python3.8/site-packages/torch/_utils_internal.py 24 6 75% 15, 18, 27, 31-33 /home/admin/.local/lib/python3.8/site-packages/torch/_vmap_internals.py 85 67 21% 15-21, 24-26, 31-35, 41-85, 92-108, 116-124, 128-132, 138-144, 250-257, 265-278 /home/admin/.local/lib/python3.8/site-packages/torch/amp/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/amp/autocast_mode.py 100 89 11% 9-14, 180-222, 225-248, 251-271, 274-276 /home/admin/.local/lib/python3.8/site-packages/torch/ao/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/ao/nn/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/ao/nn/sparse/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/ao/nn/sparse/quantized/__init__.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/ao/nn/sparse/quantized/dynamic/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/ao/nn/sparse/quantized/dynamic/linear.py 77 54 30% 20-36, 39, 42, 47, 50, 53-54, 58-73, 78, 81, 84, 88-89, 97-136 /home/admin/.local/lib/python3.8/site-packages/torch/ao/nn/sparse/quantized/linear.py 128 92 28% 11-22, 25, 30-36, 42, 45, 48-50, 54-61, 66-67, 71-73, 76, 87-105, 109, 112, 117, 120, 123-125, 129-141, 146, 149, 152, 156-157, 167-207 /home/admin/.local/lib/python3.8/site-packages/torch/ao/nn/sparse/quantized/utils.py 25 12 52% 4, 21-26, 29, 32-34, 38 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/__init__.py 14 2 86% 20-21 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/fake_quantize.py 172 100 42% 22, 25, 28, 31, 48-53, 57, 61, 65, 69, 73, 77, 118-152, 156, 159-178, 182, 192-194, 200-224, 235-241, 246, 250, 280-285, 289, 293, 309, 445-451, 461-462, 472-473, 483-484, 494-495 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/fuse_modules.py 61 47 23% 16-20, 24-30, 45-67, 70-82, 85-95, 151, 162 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/fuser_method_mappings.py 96 68 29% 26-45, 63-91, 108-119, 135-141, 149, 175-181, 190, 195, 200-201, 244-252, 260-270 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/observer.py 535 396 26% 26-29, 32, 35, 38-40, 81-82, 102-103, 107, 111, 172-202, 216-223, 250-253, 272-327, 331, 422-439, 446-455, 460, 464, 469-470, 528-529, 540-554, 597-615, 620, 623-648, 652, 655, 667-703, 724, 737-738, 781-791, 794-817, 862-877, 890-893, 900-943, 953-1006, 1017-1032, 1045-1068, 1071-1127, 1131-1147, 1150-1154, 1166-1187, 1220-1226, 1229, 1233, 1253-1260, 1263, 1267, 1284-1285, 1288-1289, 1293, 1297, 1315-1317, 1320, 1324, 1340, 1343, 1347, 1351-1356, 1360, 1368-1374, 1382-1393, 1402-1422 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/qconfig.py 141 96 32% 66, 89-93, 197-213, 270-315, 339, 364-372, 375-383, 390-405, 427-451, 458-482, 489-495, 498 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/quant_type.py 9 2 78% 13-19 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/quantization_mappings.py 83 38 54% 177-181, 186, 191, 196-199, 204, 213-222, 230-237, 242, 249-252, 257, 262, 268-274, 280-289, 293, 299-302, 311, 314 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/quantize.py 251 219 13% 32, 56-72, 92-96, 101, 106, 109-116, 135-203, 206, 224-229, 262-285, 290-306, 316-322, 341-350, 382-435, 452-463, 478-485, 516-524, 542-564, 577-614, 624-631 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/quantize_jit.py 82 64 22% 8-9, 12-13, 20, 29, 38-45, 48-63, 66-67, 70-71, 75-94, 97-98, 101-102, 107-119, 171-172, 212-213 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/stubs.py 30 17 43% 13-15, 18, 30-32, 35, 54-59, 62-64 /home/admin/.local/lib/python3.8/site-packages/torch/ao/quantization/utils.py 147 113 23% 100-103, 106-108, 111, 115, 123, 126-151, 165-170, 173-175, 178-180, 186, 193-195, 202, 208, 214, 220, 226-228, 239-243, 246-264, 271-295, 304-348, 355-359, 367-372 /home/admin/.local/lib/python3.8/site-packages/torch/autograd/__init__.py 88 60 32% 32-74, 78-82, 150-173, 238-276, 295, 299, 308, 324-326 /home/admin/.local/lib/python3.8/site-packages/torch/autograd/anomaly_mode.py 20 8 60% 74-75, 80, 83, 102-103, 106, 109 /home/admin/.local/lib/python3.8/site-packages/torch/autograd/forward_ad.py 42 25 40% 21-26, 37-43, 68-75, 103-111, 147, 150, 153 /home/admin/.local/lib/python3.8/site-packages/torch/autograd/function.py 191 119 38% 58, 104-109, 144, 147, 182, 226, 235-239, 246-253, 257, 308-309, 315, 340, 366, 391, 398-434, 449-450, 456-457, 462-475, 485-487, 493-511, 523-537, 558-563, 566-571, 574-576, 581-585, 588-589, 593-594, 597, 600, 603, 606 /home/admin/.local/lib/python3.8/site-packages/torch/autograd/functional.py 329 308 6% 9-14, 19-36, 44-53, 63-75, 81-87, 92-103, 109-135, 142-159, 168-203, 266-293, 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1295-1306, 1310, 1386-1396 /home/admin/.local/lib/python3.8/site-packages/torch/fx/graph_module.py 355 283 20% 40-52, 57-59, 62-64, 70-71, 76-80, 84-89, 93-96, 103-105, 112-113, 119-124, 136-178, 183-205, 210-224, 228-229, 243-260, 263-277, 301-309, 336-379, 392, 401-404, 418-468, 493-510, 531-553, 570-612, 620-622, 631-656, 661-667, 670-679, 689-693, 699-701, 704, 707-708, 711-713 /home/admin/.local/lib/python3.8/site-packages/torch/fx/immutable_collections.py 27 5 81% 14, 37, 40, 43, 46 /home/admin/.local/lib/python3.8/site-packages/torch/fx/interpreter.py 144 96 33% 67-89, 108-133, 149-152, 173-185, 203-204, 221-224, 242-246, 266-269, 287, 301-307, 321-325, 338-343, 387-399, 415-417, 433-434, 439-441, 446, 454-459 /home/admin/.local/lib/python3.8/site-packages/torch/fx/node.py 246 180 27% 12, 36-43, 54-62, 66-71, 74-92, 153-200, 211, 222, 237-244, 255, 258-259, 271, 282, 294, 305, 319, 332-334, 347-349, 359, 363, 369-380, 383-385, 394-407, 441-461, 483-503, 515-533, 562-569, 582-589, 597-598, 605-616 /home/admin/.local/lib/python3.8/site-packages/torch/fx/operator_schemas.py 221 176 20% 14, 30, 34, 43-45, 61, 64-84, 88-120, 138-154, 158-182, 186-230, 259-328, 353-367, 392-408 /home/admin/.local/lib/python3.8/site-packages/torch/fx/proxy.py 223 134 40% 40-43, 47, 63-84, 94-105, 115-151, 160, 169, 184, 191-192, 196, 234-238, 241, 246, 249, 252-260, 263-284, 288, 291, 297-319, 327-330, 336-338, 341, 352-355, 358, 362, 365, 368, 372, 375, 378, 384-386, 396-397 /home/admin/.local/lib/python3.8/site-packages/torch/fx/subgraph_rewriter.py 152 133 12% 20-31, 41-42, 49-86, 90-132, 250-428 /home/admin/.local/lib/python3.8/site-packages/torch/hub.py 304 250 18% 20-55, 83-90, 94-98, 103, 108-110, 122-140, 144-145, 150-169, 176-241, 244-290, 294-295, 299-304, 308-322, 336-341, 352, 394-407, 446-458, 530-541, 563-573, 591-633, 640-643, 647-660, 699-731 /home/admin/.local/lib/python3.8/site-packages/torch/jit/__init__.py 52 16 69% 75, 130, 194, 215-217, 220, 223, 230-235, 242, 248, 253 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_async.py 10 2 80% 84, 96 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_builtins.py 42 1 98% 163 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_check.py 87 75 14% 63-82, 85-112, 125-132, 140-181, 195-240 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_decomposition_utils.py 6 3 50% 5-8 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_freeze.py 29 23 21% 101-121, 167-173, 207-220 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_fuser.py 73 61 16% 12-17, 30-63, 69-74, 77, 80-107, 140 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_ir_utils.py 14 7 50% 6-8, 11-12, 15, 18 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_monkeytype_config.py 102 75 26% 15-18, 24-32, 38-53, 61-66, 69, 73-149, 155, 163, 179-183 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_recursive.py 501 443 12% 39-47, 50-52, 55-66, 70-79, 82-93, 102-107, 118, 127-330, 347-362, 368-375, 378-384, 399-414, 423-435, 453-458, 469-595, 602-608, 611-612, 616-638, 643-651, 654-657, 660-669, 672-685, 693-740, 747-776, 784-797, 809-824, 827-845, 851, 857-867, 870-877, 886-910 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_script.py 595 404 32% 62, 71-72, 151, 155, 161-162, 182, 185, 188, 191, 194, 197, 200-205, 208, 211-213, 218-225, 228-229, 232, 244-248, 254, 272, 279-280, 292-318, 326, 334-350, 355, 358, 366-379, 427-434, 437-443, 446-452, 457-461, 464, 467-470, 475, 496, 501-503, 506-523, 526-545, 548, 559-561, 592-598, 614-620, 624-633, 642-665, 673, 682, 691, 705-706, 714, 728, 731, 734, 737, 740, 743, 747-749, 760-761, 764-785, 788-814, 817, 820, 827-832, 835, 838, 841, 844, 849-854, 860-865, 870-874, 943, 959-969, 972-1002, 1006-1007, 1022, 1036, 1239-1351, 1359-1361, 1370-1389, 1394-1416, 1420-1422, 1430-1457, 1461-1466, 1473-1475, 1480-1483, 1486, 1489-1503, 1508-1509, 1512-1531, 1536, 1539, 1542, 1545-1570, 1573, 1577-1578 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_serialization.py 70 57 19% 78-84, 150-169, 173-184, 188-194, 198-209, 251-261, 285-291 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_state.py 63 35 44% 27-37, 47, 51, 66-67, 71-74, 78, 82-83, 98-102, 105, 108-114, 118-119 /home/admin/.local/lib/python3.8/site-packages/torch/jit/_trace.py 453 383 15% 34-54, 61-72, 84-92, 95-140, 144-160, 173-185, 222-277, 281-283, 287, 292-305, 321-535, 554-559, 563-577, 581-584, 734-830, 922-1005, 1014, 1023-1087, 1090, 1093-1095, 1098-1100, 1103, 1106, 1119, 1129-1130, 1171-1176 /home/admin/.local/lib/python3.8/site-packages/torch/jit/annotations.py 254 213 16% 34-37, 54-56, 59-63, 66-91, 97, 101-109, 113-127, 132-144, 154-170, 175-232, 245-250, 255-270, 276-287, 290-301, 306-398, 402-405 /home/admin/.local/lib/python3.8/site-packages/torch/jit/frontend.py 612 469 23% 30-31, 42, 100-105, 108, 118-125, 133-134, 138-139, 153-166, 170-183, 189-216, 234-265, 270-281, 285-288, 292-294, 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310-322, 326, 329, 333, 336, 340, 343-365 /home/admin/.local/lib/python3.8/site-packages/torch/multiprocessing/spawn.py 98 71 28% 16-19, 22, 36, 50-52, 55, 66-76, 81-83, 89, 105-160, 165-166, 179-199, 235-240 /home/admin/.local/lib/python3.8/site-packages/torch/nn/__init__.py 20 13 35% 32-47 /home/admin/.local/lib/python3.8/site-packages/torch/nn/_reduction.py 31 26 16% 8-20, 28-43, 47 /home/admin/.local/lib/python3.8/site-packages/torch/nn/common_types.py 25 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/functional.py 1164 929 20% 13, 461-482, 492-503, 562-587, 597-608, 657-671, 682-696, 743-757, 768-782, 829-843, 854-868, 885-912, 926-948, 962-980, 994-1012, 1027-1037, 1052-1061, 1076-1080, 1084-1088, 1116-1121, 1125-1129, 1157-1162, 1166-1170, 1211-1214, 1228-1231, 1248-1252, 1260-1264, 1282-1302, 1320-1346, 1364-1385, 1408-1414, 1422-1428, 1453, 1455, 1489-1493, 1503-1509, 1529-1535, 1544-1550, 1573-1579, 1600-1606, 1628-1634, 1668-1676, 1733-1735, 1745-1747, 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/home/admin/.local/lib/python3.8/site-packages/torch/nn/init.py 193 102 47% 24-54, 102, 104, 106, 109, 114, 116-119, 136, 154, 176, 190-192, 233-238, 256-281, 287, 323-327, 350-353, 360, 396, 405-406, 444-451, 469-495, 514-526, 535-537 /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/modules/__init__.py 15 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/modules/fused.py 57 26 54% 13-16, 22-25, 31-34, 40-43, 49-52, 58-61, 67-70, 76-79, 85-88, 94-97, 104-107, 113-116, 123-125 /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/qat/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/qat/modules/__init__.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/qat/modules/conv_fused.py 250 143 43% 44-66, 69, 72-79, 82, 85-87, 90-92, 95-114, 118, 121, 129-133, 158-185, 197-218, 221-258, 296-300, 342, 349, 353, 376-382, 385, 390, 428-432, 474, 481, 485, 508-514, 517, 522, 568-572, 637, 654, 658, 690-704, 707, 713, 716-719, 722-725 /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/qat/modules/linear_fused.py 84 65 23% 37-57, 60, 63-65, 68, 71-73, 76-78, 81-118, 126-130, 139-155, 158-167 /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/qat/modules/linear_relu.py 20 9 55% 32, 35, 39, 42-47 /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/quantized/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/quantized/dynamic/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/quantized/dynamic/modules/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/quantized/dynamic/modules/linear_relu.py 22 10 55% 27, 30-39, 42, 46, 50 /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/quantized/modules/__init__.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/quantized/modules/bn_relu.py 36 14 61% 21, 26-28, 33, 38, 42, 57, 62-64, 69, 74, 78 /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/quantized/modules/conv_relu.py 74 40 46% 28, 36-43, 47, 51-55, 59-61, 78, 86-92, 96, 100-104, 108-110, 127-128, 136-142, 146, 150-160, 164-166 /home/admin/.local/lib/python3.8/site-packages/torch/nn/intrinsic/quantized/modules/linear_relu.py 17 5 71% 25, 28, 32, 36, 40 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/__init__.py 23 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/_functions.py 137 119 13% 10-103, 107-172, 178-230, 234-265, 270-271, 275 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/activation.py 397 222 44% 47-50, 54, 57-58, 101-102, 157-160, 163, 166-167, 216-227, 230, 233-234, 262, 265-266, 290, 325-326, 329, 354, 387-388, 391, 394-395, 423-424, 427, 430-431, 468-469, 472, 509-511, 514, 517-518, 553-555, 558, 561-562, 603-604, 607, 610-611, 637-638, 641, 644, 684, 719-720, 723, 726, 767-769, 772, 775-776, 799, 833-835, 838, 841, 874-875, 878, 881, 945-983, 986-999, 1003-1006, 1060-1164, 1220-1223, 1226, 1229, 1252, 1275, 1311-1312, 1315-1317, 1320, 1323, 1367-1368, 1371-1373, 1376, 1379, 1405-1406, 1438-1439, 1442-1444, 1447, 1450 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/adaptive.py 114 92 19% 122-161, 164-167, 170-241, 247-259, 278-279, 296-312 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/batchnorm.py 197 143 27% 37-63, 66-71, 74-77, 80, 83, 98-107, 129-130, 135-168, 190-209, 213-214, 217-227, 297-298, 332-333, 406-407, 439-440, 512-513, 545-546, 661-665, 668-669, 674-675, 681-748, 795-819 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/channelshuffle.py 13 4 69% 45-46, 49, 52 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/container.py 345 202 41% 19-24, 76, 80, 85-86, 93-98, 102-105, 108-109, 112-117, 121, 125-127, 148-149, 187, 189, 195, 200-201, 204-211, 225-228, 232-234, 243-245, 263, 320-322, 326, 329, 332, 336, 340, 344, 349, 357-359, 365, 371, 377, 391-412, 446-449, 453-458, 462, 466, 469-477, 485-488, 491, 494, 497, 500-502, 510-513, 522-527, 530-543, 546, 587-590, 593-599, 602-603, 611-615, 618-620, 623, 626, 629, 636, 639, 651-653, 658-659, 667-669, 675-680, 690, 699, 704, 709, 714, 729-751, 754-766, 769, 772-774, 777-779, 782-783 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/conv.py 331 168 49% 51, 84, 86, 89-94, 98, 115-122, 152-166, 169-171, 287-294, 299-303, 307, 450, 580-585, 590-602, 607, 616, 632-665, 774-780, 785-795, 940, 1080-1086, 1091-1102, 1124-1127, 1146-1150, 1155-1169, 1173-1180, 1185, 1233-1251, 1254, 1302-1320, 1323, 1371-1389, 1392, 1438-1457, 1460, 1506-1525, 1528, 1574-1593, 1596 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/distance.py 25 9 64% 37-40, 43, 72-74, 77 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/dropout.py 33 12 64% 13-18, 21, 58, 100, 149, 191, 233, 282 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/flatten.py 48 27 44% 40-42, 45, 48, 106-116, 119-125, 129-135, 138, 141 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/fold.py 38 15 61% 136-141, 144, 148, 287-291, 294, 298 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/instancenorm.py 72 40 44% 18-19, 23, 26, 29, 32, 38-62, 67-72, 143, 146-147, 182, 185-186, 259, 262-263, 298, 301-302, 375, 378-379, 414, 417-418 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/lazy.py 79 49 38% 15, 18, 23, 26, 29, 33, 37, 41, 45, 49, 175-178, 185-194, 208-217, 224, 231-236, 248-256, 260 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/linear.py 91 36 60% 42, 45, 100, 117, 130, 180-191, 194-197, 200, 203, 243-250, 253-254, 257-263 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/loss.py 201 83 59% 16-20, 25-27, 93, 96, 207-208, 211, 217-220, 286-289, 292, 367-369, 372, 461-462, 465, 527, 530, 610, 613, 707-711, 714, 773-774, 777, 838, 841, 918-919, 922, 978-979, 982, 1020, 1023, 1159-1161, 1164, 1210, 1213, 1262-1263, 1266, 1319-1320, 1323, 1392-1397, 1400, 1477-1481, 1484, 1591-1595, 1598, 1739-1741, 1744 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py 660 395 40% 22-24, 30-38, 79-81, 111-113, 131-139, 176-184, 201, 304, 307, 310, 313, 315, 317, 319, 343, 347, 350, 352, 354, 359, 363, 382, 385, 388, 390, 392, 397, 447-465, 489-503, 527-540, 557, 572, 593, 608-611, 614-621, 667-670, 689, 708, 727, 738, 752, 763, 774, 785, 796, 808, 813, 817, 821, 911-915, 923, 943-951, 986-994, 1001-1013, 1016-1053, 1077-1079, 1100-1102, 1105-1122, 1132-1174, 1179-1192, 1217, 1222, 1227-1231, 1236, 1241-1245, 1249-1253, 1258-1266, 1275-1277, 1292-1300, 1308, 1312, 1357-1386, 1403-1407, 1435-1437, 1474, 1485-1489, 1497, 1501-1504, 1508-1515, 1519-1522, 1524, 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1108-1109, 1112, 1140, 1179, 1218 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/rnn.py 473 382 19% 21, 43-124, 127-131, 140-175, 182-191, 194-196, 199-205, 210-221, 225-226, 229-232, 235-237, 241-254, 257-292, 296, 299-304, 411-420, 425, 430, 433-499, 673, 676-683, 692-695, 703-705, 712, 719, 722-784, 898-900, 905, 910, 913-967, 983-997, 1000-1005, 1008-1010, 1072-1074, 1077-1108, 1173-1174, 1177-1197, 1264-1265, 1268-1288 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/sparse.py 130 71 45% 129-133, 142-144, 154-155, 158, 163-174, 205-218, 318-341, 344-345, 348-350, 383, 390-400, 432-447 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/transformer.py 187 144 23% 57-83, 136-149, 156, 161-163, 186-190, 203-246, 267-270, 288-299, 361-388, 391-393, 410-466, 471-475, 479-480, 523-546, 549-551, 570-580, 585-589, 594-598, 602-603, 607, 611-616 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/upsampling.py 37 17 54% 141-150, 153, 157-162, 207, 253 /home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/utils.py 35 17 51% 32-38, 57-75 /home/admin/.local/lib/python3.8/site-packages/torch/nn/parallel/__init__.py 10 3 70% 11-14 /home/admin/.local/lib/python3.8/site-packages/torch/nn/parallel/_functions.py 88 60 32% 14-30, 34, 41-45, 49, 56-75, 79-82, 89-104, 108, 118-124 /home/admin/.local/lib/python3.8/site-packages/torch/nn/parallel/_replicated_tensor_ddp_utils.py 13 7 46% 18-23, 27, 31 /home/admin/.local/lib/python3.8/site-packages/torch/nn/parallel/comm.py 81 70 14% 29-38, 56-58, 76-104, 126-149, 186-199, 228-241 /home/admin/.local/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py 94 76 19% 17-37, 122-145, 148-169, 172, 175, 178, 181, 199-232 /home/admin/.local/lib/python3.8/site-packages/torch/nn/parallel/distributed.py 440 339 23% 46-53, 57-60, 67-79, 83-137, 159-168, 172-178, 186-193, 200-230, 237, 538-664, 667-672, 675-677, 691-766, 769-776, 780-794, 798-839, 850-860, 865-898, 905-916, 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/home/admin/.local/lib/python3.8/site-packages/torch/nn/qat/dynamic/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/qat/dynamic/modules/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/qat/dynamic/modules/linear.py 7 3 57% 20-22 /home/admin/.local/lib/python3.8/site-packages/torch/nn/qat/modules/__init__.py 6 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/qat/modules/conv.py 84 50 40% 29-35, 38, 48-65, 71-95, 126-130, 148, 181-185, 202, 206, 239-243, 260, 264 /home/admin/.local/lib/python3.8/site-packages/torch/nn/qat/modules/embedding_ops.py 56 38 32% 27-36, 39, 50-64, 67-72, 95-104, 107, 120-134, 137-142 /home/admin/.local/lib/python3.8/site-packages/torch/nn/qat/modules/linear.py 38 26 32% 30-34, 37, 45-69, 72-77 /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantizable/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantizable/modules/__init__.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantizable/modules/activation.py 242 222 8% 64-83, 86, 90-150, 160-219, 224-247, 305, 321-471 /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantizable/modules/rnn.py 230 196 15% 34-48, 51-73, 76-80, 83, 93-104, 108-115, 126-128, 131-136, 140-143, 151-157, 160-209, 218-241, 277-312, 315-361, 364, 368-379, 383 /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/_reference/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/_reference/modules/__init__.py 5 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/_reference/modules/conv.py 108 58 46% 19-35, 51-54, 67-71, 74, 78, 87-90, 103-107, 110, 114, 123-126, 139-143, 146, 150, 160-177, 195-198, 211-221, 224, 228, 239-242, 254-266, 269, 273, 283-286, 299-309, 312, 316 /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/_reference/modules/linear.py 23 11 52% 25-26, 29, 42-44, 48-55 /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/_reference/modules/rnn.py 262 210 20% 11, 14-22, 25-29, 32-36, 41-54, 57-79, 83, 86, 89, 92, 95, 105-107, 110, 115-146, 150-162, 172-173, 176, 179-199, 203-214, 224-225, 228, 231-251, 255-266, 274-289, 292-312, 322, 329-331, 334-341, 350-353, 365-375, 378-388, 391-453, 456, 460-471 /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/_reference/modules/sparse.py 29 12 59% 19-21, 24, 27-28, 34, 60-63, 66, 69-70, 78 /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/_reference/modules/utils.py 73 61 16% 6-41, 52-55, 64-67, 76-77, 83-87, 98-112, 124-133, 136-142, 147-154 /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/dynamic/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/dynamic/modules/__init__.py 4 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/dynamic/modules/conv.py 111 64 42% 56-67, 72, 77-84, 120-131, 136, 141-147, 184-195, 200, 205-211, 253-259, 264, 269-271, 313-319, 324, 329-331, 373-379, 384, 389-391 /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/dynamic/modules/linear.py 58 43 26% 34-39, 43-55, 58, 61-66, 70-72, 83-112, 122-126 /home/admin/.local/lib/python3.8/site-packages/torch/nn/quantized/dynamic/modules/rnn.py 506 403 20% 12, 16-33, 37-38, 41-42, 46-47, 59-123, 126, 129-140, 147-170, 173-179, 184-191, 197-198, 202-204, 208-210, 214-216, 221-254, 258-341, 346-364, 367, 370, 391, 394, 401-426, 432-440, 446-455, 461-463, 469-474, 479-482, 486, 490-504, 616, 619, 622-625, 633-670, 677-685, 691-699, 704-706, 710-713, 717, 725-763, 766, 769-774, 777-778, 783-789, 795-841, 845-873, 877-886, 889, 892, 897-901, 907-909, 913-915, 937-938, 941, 944-962, 966, 989, 992, 995-1001, 1008, 1029, 1032, 1035-1039, 1047 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126-132 /home/admin/.local/lib/python3.8/site-packages/torch/package/find_file_dependencies.py 70 55 21% 15-18, 21-23, 26-28, 31-32, 35-43, 46-49, 52-55, 59-99 /home/admin/.local/lib/python3.8/site-packages/torch/package/glob_group.py 31 19 39% 42-45, 48, 51, 54-55, 61-64, 70-82 /home/admin/.local/lib/python3.8/site-packages/torch/package/importer.py 101 75 26% 52, 73-133, 143-162, 169, 172, 185, 197-203, 206-224, 227-232 /home/admin/.local/lib/python3.8/site-packages/torch/package/package_exporter.py 441 342 22% 74, 107-109, 128-152, 200-241, 256-290, 299-301, 320-350, 368-381, 393-396, 399-408, 411-415, 418-428, 434-485, 498-503, 513-559, 586-686, 696, 706-707, 724-726, 743-745, 762-764, 788, 829, 860, 874, 879-930, 933, 939-944, 947-961, 965-972, 977-979, 985-1035, 1039, 1048-1052, 1056-1058, 1061-1063, 1066-1067, 1078, 1083-1089, 1098, 1107, 1116, 1125, 1133-1136, 1146, 1161-1163 /home/admin/.local/lib/python3.8/site-packages/torch/package/package_importer.py 346 274 21% 70-111, 132-134, 147-148, 168-169, 183-264, 273, 290, 303-304, 311, 320-356, 359-371, 374-376, 382-383, 388-394, 397-402, 406-425, 429-446, 457-461, 472-502, 505-527, 535-545, 548-555, 560-574, 582-595, 598-602, 616-617, 624, 641-642, 657-658, 661-663, 668-676, 679-680, 683-704 /home/admin/.local/lib/python3.8/site-packages/torch/profiler/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/profiler/profiler.py 171 127 26% 27, 70-77, 80-81, 84, 87-98, 101-107, 110-111, 117-128, 144-145, 155-156, 163-164, 171-172, 179, 182-186, 211-232, 240, 249-266, 393-424, 464-465, 468, 471-474, 477-479, 485-497, 500-501, 504-507 /home/admin/.local/lib/python3.8/site-packages/torch/quantization/__init__.py 14 2 86% 18-19 /home/admin/.local/lib/python3.8/site-packages/torch/quantization/fake_quantize.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/quantization/fuse_modules.py 7 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/quantization/fuser_method_mappings.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/quantization/observer.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/quantization/qconfig.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/quantization/quant_type.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/quantization/quantization_mappings.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/quantization/quantize.py 20 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/quantization/quantize_jit.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/quantization/stubs.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/quasirandom.py 66 54 18% 48-68, 85-104, 120-129, 135-137, 148-153, 156-171, 174-179 /home/admin/.local/lib/python3.8/site-packages/torch/random.py 46 33 28% 18, 23, 36-42, 49-55, 62, 85-129 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84-164 /home/admin/.local/lib/python3.8/site-packages/torch/testing/_deprecated.py 59 30 49% 32-36, 55-57, 72-80, 116-141 /home/admin/.local/lib/python3.8/site-packages/torch/testing/_legacy.py 80 38 52% 45-47, 57, 61, 65, 68, 72, 75, 79, 83, 86, 90, 93, 97, 100, 104, 107, 111, 123-130, 133, 137, 141, 145-150, 154, 158 /home/admin/.local/lib/python3.8/site-packages/torch/torch_version.py 36 20 44% 21-27, 30, 33, 58-71, 74-81 /home/admin/.local/lib/python3.8/site-packages/torch/types.py 44 11 75% 45, 48, 51, 54, 57, 60, 63, 66, 69, 72, 75 /home/admin/.local/lib/python3.8/site-packages/torch/utils/__init__.py 11 2 82% 10, 15 /home/admin/.local/lib/python3.8/site-packages/torch/utils/_crash_handler.py 17 8 53% 9, 12-17, 21, 25 /home/admin/.local/lib/python3.8/site-packages/torch/utils/_mode_utils.py 60 38 37% 27-33, 48, 52, 59, 66-102, 110-132 /home/admin/.local/lib/python3.8/site-packages/torch/utils/_pytree.py 118 79 33% 43, 46, 49, 52, 55, 58, 61, 64, 74-81, 84-86, 90, 100-103, 106, 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42-45, 49-51, 55-57, 61-63, 70, 75, 79-80, 84-85, 89-90, 94-95, 99-100, 104-105, 109-110 /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/dataframe/dataframes.py 198 106 46% 33-34, 37-38, 51, 54, 57-62, 65-67, 70, 73, 77-81, 84-88, 91-95, 100-103, 108, 111, 116, 119, 129-133, 136, 139, 143-146, 154-156, 159, 162, 171-174, 177, 180, 189-191, 194, 197, 205-207, 210, 213, 221-223, 226, 229, 237-239, 242, 245-246, 250-255, 261-263, 272, 276, 279, 282-285, 294-297, 300, 303, 306-308, 316-317 /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/dataframe/datapipes.py 100 70 30% 21, 24-26, 32, 35-37, 43-44, 47-54, 60, 63-78, 84-85, 88-106, 112-114, 117-120, 123-130 /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/dataframe/structures.py 12 7 42% 13-15, 18-21 /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/datapipe.py 179 100 44% 21-22, 116-123, 127, 132, 135-141, 152-154, 157-162, 166-168, 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33-47, 50 /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/map/__init__.py 7 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/map/callable.py 21 7 67% 15, 49-52, 55, 58 /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/map/combinatorics.py 24 11 54% 44-49, 52-54, 59-60, 63 /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/map/combining.py 54 35 35% 35-42, 45-51, 54-56, 80-87, 90-96, 99-101 /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/map/grouping.py 39 25 36% 40-46, 49-59, 62-70 /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/map/utils.py 17 9 47% 32-42, 45, 48 /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/utils/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/torch/utils/data/datapipes/utils/common.py 116 91 22% 21-22, 30-39, 50-76, 80-90, 94-101, 138-173, 183, 186-187, 190-192, 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75-109, 114-133, 139-168, 179-196, 199, 210-219, 222, 225-241 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/kinetics.py 100 72 28% 20, 116-156, 160-167, 176-197, 211-229, 236, 239, 242-248, 312-323 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/kitti.py 58 39 33% 61-84, 105-109, 112-128, 131, 135, 139-142, 147-154 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/lfw.py 125 96 23% 42-58, 61-63, 66-72, 75-82, 85, 88, 91, 123-126, 129-144, 147-151, 161-170, 173, 205-207, 210-235, 245-255 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/lsun.py 94 75 20% 18-31, 34-50, 53, 79-93, 96-136, 146-161, 164, 167 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/mnist.py 243 152 37% 65-66, 70-71, 75-76, 80-81, 91-104, 107-111, 118-119, 122-128, 138-150, 153, 157, 161, 165, 168, 176-195, 198-199, 294-298, 302, 306, 310, 314, 318, 321, 324, 329-339, 421-428, 432-433, 437-438, 441, 444-461, 467-474, 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61-96, 99-100, 103-104, 110-116, 119, 122-123 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/sbu.py 59 45 24% 36-58, 68-77, 81, 85-89, 93-114 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/semeion.py 43 28 35% 37-51, 61-73, 76, 79-83, 86-91 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/stanford_cars.py 49 38 22% 41-74, 77, 81-88, 91-111, 118-121 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/stl10.py 104 79 24% 55-88, 91-100, 111-126, 129, 132-145, 148-154, 157-161, 164, 168-176 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/sun397.py 36 23 36% 36-51, 56, 59-68, 71, 74-76 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/svhn.py 44 30 32% 61-91, 101-113, 116, 119-122, 125-126, 129 /home/admin/.local/lib/python3.8/site-packages/torchvision/datasets/ucf101.py 45 32 29% 71-101, 105, 108-118, 121, 124-130 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585-673, 794-819, 862-891 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/detection/roi_heads.py 481 441 8% 28-49, 69-79, 91-94, 109-126, 131-162, 168-213, 220-231, 244-295, 300-326, 331-342, 347-360, 368-383, 389, 394-400, 405-425, 429-461, 466-471, 476-489, 522-548, 551-557, 560-566, 570-601, 605-610, 614-616, 620-628, 636-666, 676-725, 742-876 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/detection/rpn.py 175 149 15% 29-41, 53-62, 73-79, 83-86, 90-111, 161-181, 184-186, 189-191, 197-229, 232-240, 250-297, 314-337, 363-391 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/detection/ssd.py 273 223 18% 49-53, 58-60, 63, 71-73, 80-87, 90-103, 108-112, 117-121, 201-242, 248-251, 260-319, 327-410, 415-461, 466-535, 539-548, 552-568, 643-679 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/detection/ssdlite.py 119 79 34% 33, 49-51, 74-78, 85-87, 90, 100-104, 109-113, 125-148, 152-161, 169-184, 262-328 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/detection/transform.py 185 159 14% 14-16, 22, 32-71, 96-105, 110-146, 149-157, 165-166, 173-194, 200-218, 221-225, 228-245, 253-267, 270-275, 279-293, 297-309 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/efficientnet.py 265 159 40% 59, 76-81, 85, 100-102, 113-162, 165-169, 179-223, 226-230, 255-342, 345-352, 355, 366-374, 382-429, 754-757, 782-785, 810-813, 838-841, 866-869, 894-897, 930-933, 966-969, 1003-1006, 1040-1043, 1077-1080 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/googlenet.py 185 143 23% 42-100, 103-108, 112-163, 167-170, 173-181, 196-212, 218-224, 227-228, 239-246, 250-263, 268-270, 273-275, 319-342 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/inception.py 299 243 19% 38-93, 96-101, 105-155, 159-162, 165-173, 180-192, 195-208, 211-212, 217-224, 227-236, 239-240, 247-263, 266-282, 285-286, 291-300, 303-313, 316-317, 322-336, 339-360, 363-364, 371-378, 382-395, 400-402, 405-407, 457-475 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/mnasnet.py 119 73 39% 38-45, 60-63, 70-77, 84-87, 93-94, 113-156, 159-162, 174-209, 306-314, 339-341, 366-368, 393-395, 420-422 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/mobilenet.py 5 0 100% /home/admin/.local/lib/python3.8/site-packages/torchvision/models/mobilenetv2.py 105 72 31% 23-32, 43-78, 81-84, 112-181, 186-191, 194, 265-275 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/mobilenetv3.py 138 97 30% 29-33, 54-61, 65, 76-124, 127-130, 155-223, 226-233, 236, 242-285, 295-303, 398-401, 428-431 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/optical_flow/__init__.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/torchvision/models/optical_flow/_utils.py 25 18 28% 10-17, 21-23, 33-45 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/optical_flow/raft.py 288 219 24% 31-59, 62-68, 75-92, 103-110, 120-143, 146-148, 151-159, 169-190, 193-202, 209-212, 215-220, 225, 236-255, 258-260, 270-273, 276, 286-291, 294-299, 310-320, 323-325, 339-349, 359-370, 374-400, 403-409, 449-460, 464-511, 747-798, 824-826, 878-880 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/quantization/__init__.py 5 0 100% /home/admin/.local/lib/python3.8/site-packages/torchvision/models/quantization/googlenet.py 95 59 38% 27-28, 31-34, 37, 42-43, 46-47, 53-54, 58-71, 77-81, 84-94, 104-106, 178-207 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/quantization/inception.py 130 81 38% 28-29, 32-35, 38, 44-45, 48-49, 55-56, 59-60, 66-67, 70-71, 77-78, 81-82, 88-91, 94-112, 115-116, 122, 132-147, 150-160, 170-172, 250-276 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/quantization/mobilenet.py 5 0 100% /home/admin/.local/lib/python3.8/site-packages/torchvision/models/quantization/mobilenetv2.py 62 33 47% 26-27, 30-33, 36-38, 49-51, 54-57, 60-64, 136-152 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/quantization/mobilenetv3.py 88 53 40% 34-36, 39, 42, 54-72, 86-87, 90-93, 104-106, 109-112, 115-122, 133-158, 231-234 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/quantization/resnet.py 120 70 42% 39-40, 43-57, 60-62, 67-70, 73-88, 91-95, 100-103, 106-112, 121-124, 135-149, 315-317, 364-366, 413-417, 456-460 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/quantization/shufflenetv2.py 86 43 50% 37-38, 41-49, 55-57, 60-63, 75-82, 99-113, 253-254, 306-307, 351-352, 396-397 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/quantization/utils.py 30 24 20% 8-18, 22-42, 48-51 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/regnet.py 273 142 48% 62, 81-105, 122-141, 144-148, 168-182, 195-200, 234-266, 276, 287-293, 307-374, 377-384, 393-402, 1123-1126, 1148-1151, 1173-1178, 1200-1205, 1227-1232, 1254-1259, 1281-1286, 1308-1313, 1335-1338, 1360-1363, 1389-1392, 1418-1421, 1447-1450, 1476-1479, 1505-1508 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/resnet.py 236 150 36% 42, 56, 73-87, 90-105, 128-141, 144-163, 178-223, 233-264, 268-282, 285, 295-303, 668-670, 693-695, 724-726, 755-757, 786-788, 813-817, 842-846, 870-874, 904-907, 937-940 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/segmentation/__init__.py 3 0 100% /home/admin/.local/lib/python3.8/site-packages/torchvision/models/segmentation/_utils.py 27 18 33% 14-18, 21-37 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/segmentation/deeplabv3.py 127 81 36% 50, 61-66, 71, 79-82, 87-101, 109-113, 121-128, 203-218, 257-273, 312-328, 365-381 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/segmentation/fcn.py 64 36 44% 38-47, 103-110, 152-168, 210-226 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/segmentation/lraspp.py 70 44 37% 38-41, 44-51, 56-68, 71-79, 83-93, 157-175 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273-288, 300-308, 396-398, 432-434, 468-470 /home/admin/.local/lib/python3.8/site-packages/torchvision/models/vision_transformer.py 223 155 30% 46-52, 64-75, 98-108, 111-119, 136-152, 155-157, 178-266, 269-287, 291-305, 318-337, 618-620, 651-653, 684-686, 717-719, 749-751, 784-838 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/__init__.py 18 0 100% /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/_box_convert.py 28 22 21% 17-25, 39-47, 61-63, 77-81 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/_register_onnx_ops.py 34 16 53% 16-21, 25-44, 57-60 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/_utils.py 59 49 17% 13-15, 19-25, 29-38, 45-69, 74-77, 82-84, 92-106 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/boxes.py 162 123 24% 73, 90, 106-112, 128-133, 148-165, 189-216, 232-235, 241-252, 269-273, 292-304, 320-337, 356-362, 367-381, 398-415 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/ciou_loss.py 25 20 20% 45-71 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/deform_conv.py 65 50 23% 63-92, 126-151, 154-159, 170, 182-195 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/diou_loss.py 32 26 19% 45-57, 66-87 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/drop_block.py 68 52 24% 28-52, 74-102, 114-119, 129, 132-133, 145, 155 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/feature_pyramid_network.py 100 80 20% 33, 84-110, 122-134, 149-156, 163-170, 184-204, 218-220, 229-235, 243-249 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/focal_loss.py 18 14 22% 35-51 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/giou_loss.py 24 20 17% 43-70 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/misc.py 93 67 28% 27-33, 45-49, 56-62, 65, 85-114, 153, 202, 237-243, 246-250, 253-254, 282-298, 309-310, 313 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/poolers.py 123 92 25% 20-34, 45, 68-72, 80-85, 89-96, 101-107, 114-135, 140-144, 169-228, 278-288, 291-292, 295-296, 303-304, 325-331, 341 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/ps_roi_align.py 29 18 38% 46-57, 71-75, 78, 81-88 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/ps_roi_pool.py 28 17 39% 40-49, 58-61, 64, 67-68 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/roi_align.py 31 18 42% 53-61, 78-83, 86, 89-97 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/roi_pool.py 30 17 43% 42-51, 60-63, 66, 69-70 /home/admin/.local/lib/python3.8/site-packages/torchvision/ops/stochastic_depth.py 34 24 29% 26-44, 56-59, 62, 65-66 /home/admin/.local/lib/python3.8/site-packages/torchvision/transforms/__init__.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/torchvision/transforms/_pil_constants.py 18 8 56% 17-25 /home/admin/.local/lib/python3.8/site-packages/torchvision/transforms/_presets.py 119 91 24% 24-26, 29, 32, 48-53, 56-62, 65-72, 75, 93-98, 101-118, 121-128, 131, 149-153, 156-162, 165-171, 174, 184-199, 202, 205 /home/admin/.local/lib/python3.8/site-packages/torchvision/transforms/autoaugment.py 207 167 19% 16-90, 127-131, 136-221, 224, 249-253, 262-281, 284, 314-319, 322, 347-365, 368-377, 402-405, 408, 433-453, 456-463, 497-507, 510-531, 535, 539, 543, 552-601, 604-615 /home/admin/.local/lib/python3.8/site-packages/torchvision/transforms/functional.py 505 409 19% 39-47, 71-76, 88-93, 105-110, 115, 120, 135-174, 193-209, 234-239, 259, 262-271, 275, 279, 283, 287-289, 292, 295-307, 310-315, 318-323, 327, 332, 355-360, 417-421, 424, 428, 432, 476-481, 501-506, 523-547, 581-585, 600-605, 623-633, 668-688, 703-708, 730-753, 779-797, 814-819, 836-841, 858-863, 897-902, 930-935, 961-995, 1042-1081, 1132-1214, 1232-1237, 1259-1264, 1283-1288, 1317-1355, 1370-1375, 1391-1399, 1414-1419, 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167, 172-173, 177, 179, 182-231, 240-241, 270-274, 276-279, 289-295, 298-299, 304-306, 311-312, 321-323, 340, 343-344, 358-370, 400, 408, 418-419, 422-423, 435, 437, 442-445, 456-458, 471-473, 506, 509, 512, 524-540 /home/admin/workarea/git/Velours/python/dev/generate_new_image.py 477 245 49% 27-28, 31-36, 72-77, 83-84, 87-88, 94, 99-106, 135-147, 156-157, 162-175, 223-227, 245-248, 251, 254-261, 268, 279-280, 296-297, 302-312, 316-333, 337-357, 362-370, 404-405, 407-408, 411-412, 414, 420, 423-431, 437-438, 440, 459-466, 498-508, 543-578, 585-586, 593, 611, 655-656, 664-671, 678-771 /home/admin/workarea/git/Velours/python/dev/poly_crop_reduction.py 238 157 34% 9-20, 40, 45, 54-56, 58-59, 117, 119-120, 127-168, 172-226, 229-244, 260-310, 330-381 /home/admin/workarea/git/Velours/python/file_uploader.py 73 35 52% 14-15, 23-24, 28-30, 36-37, 54-56, 62-64, 70-80, 84-95, 98 /home/admin/workarea/git/Velours/python/misc/__init__.py 1 0 100% /home/admin/workarea/git/Velours/python/misc/split_time_score.py 928 711 23% 30-47, 51-60, 67-224, 311, 314-329, 353-354, 368-376, 386-387, 412-413, 420-424, 432, 441-442, 447-448, 457-463, 468-499, 515, 528, 533-535, 560-594, 600-644, 775-796, 801, 812-814, 837, 839, 842, 860, 862, 882-943, 957-1805 /home/admin/workarea/git/Velours/python/mtr/Gan2/pre_ops.py 265 175 34% 14-16, 19-21, 24, 27, 30, 33-35, 51-52, 76-86, 89-105, 141-201, 215-293, 317-320, 322-325, 327-334, 337, 361-415 /home/admin/workarea/git/Velours/python/mtr/Rubbia_Report.py 577 544 6% 95-134, 141-202, 211-225, 234-252, 260-300, 309-315, 323-338, 352-379, 387-394, 397-429, 437-446, 450-465, 471-476, 481-527, 530-541, 545-607, 612-673, 677-771, 774-791, 797-804, 808-828, 832-930 /home/admin/workarea/git/Velours/python/mtr/__init__.py 1 0 100% /home/admin/workarea/git/Velours/python/mtr/cnn/__init__.py 1 0 100% /home/admin/workarea/git/Velours/python/mtr/cnn/classifier_new.py 289 89 69% 24-39, 66, 80, 83-92, 124, 130, 184, 213-215, 221, 225-227, 240, 245-254, 263-270, 277, 291, 337-338, 354, 356-357, 365-369, 378-379, 395, 427-430, 456-457, 465, 485, 507, 522-523, 536-550 /home/admin/workarea/git/Velours/python/mtr/cnn/ordonner.py 73 39 47% 20-29, 36, 44, 54, 66-101, 104 /home/admin/workarea/git/Velours/python/mtr/database_queries/CacheModelConfig.py 63 45 29% 15-18, 23-26, 30, 35-48, 54-68, 73-77, 81-85, 88-95, 98, 101 /home/admin/workarea/git/Velours/python/mtr/database_queries/CacheModelData_queries.py 180 77 57% 19, 26, 35-42, 61, 66-82, 102, 111-133, 144, 148, 150, 154-159, 161-162, 164, 166, 168, 171-172, 205-206, 226-227, 231-232, 240-256, 293 /home/admin/workarea/git/Velours/python/mtr/database_queries/CachePhotoData_queries.py 364 90 75% 35-37, 56, 58, 63, 88, 101-110, 117, 119, 133, 139-141, 149-150, 160, 169, 182-184, 201-202, 225-227, 253-255, 275-277, 288-289, 304, 327-333, 337, 350-352, 378-387, 397-398, 489-490, 501, 517, 524-529, 537, 594-597, 618-620, 634-654 /home/admin/workarea/git/Velours/python/mtr/database_queries/__init__.py 1 0 100% /home/admin/workarea/git/Velours/python/mtr/database_queries/admin_queries.py 457 380 17% 32-39, 44-50, 56-66, 71-87, 92, 96-99, 102-116, 120-135, 138-143, 146-148, 156-165, 168-177, 180-187, 192-206, 211-227, 232-250, 254-271, 275-291, 294-295, 298-299, 302-308, 326-331, 334-337, 340-349, 353-357, 360-367, 370-376, 379-389, 392-399, 402-404, 407-414, 417-430, 433-444, 447-469, 476, 485, 488-495, 498-504, 507-510, 514-518, 522-540, 543-548, 551-556, 559-564, 568-577, 580-588, 591-600, 603-612, 615-621, 625-648 /home/admin/workarea/git/Velours/python/mtr/database_queries/classification_admin_tools.py 87 53 39% 27-28, 30-34, 45, 61, 64, 76-92, 97-105, 110-137, 142, 147-163, 166-171 /home/admin/workarea/git/Velours/python/mtr/database_queries/classification_queries.py 291 200 31% 22-42, 45-49, 52-71, 74-82, 85-91, 94-98, 101-106, 109-117, 124-134, 139-148, 152-159, 162-172, 176-197, 200-220, 223-233, 236-248, 253-261, 267-283, 301-363, 379, 382, 390, 411, 414, 423, 489-511, 514-528 /home/admin/workarea/git/Velours/python/mtr/database_queries/database_objet/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/mtr/database_queries/database_objet/objet_thcl.py 146 114 22% 32-50, 56-65, 70-77, 81, 84, 87, 90, 93, 96, 99, 102, 105, 108, 111, 114, 117, 120, 123, 126, 129-132, 138-139, 143-147, 152-171, 177-196, 200-202, 205-212, 226-232, 237-269 /home/admin/workarea/git/Velours/python/mtr/database_queries/datou_queries.py 1475 791 46% 44, 57, 69, 87, 95-97, 102, 121-127, 131-133, 149-153, 166-170, 186-295, 305-308, 311-316, 319-326, 329-348, 351-359, 364, 369, 391, 394-397, 406-409, 420-461, 481, 484-487, 503-523, 528, 534-541, 551-572, 577, 584, 587, 590, 597, 630, 646, 663, 744, 751, 764, 801, 831, 868, 873-874, 894-897, 901-906, 909-914, 918-921, 960, 964, 968-969, 977, 979, 989-990, 994, 1006, 1011, 1016-1017, 1024-1044, 1083, 1090, 1135, 1144, 1158, 1164, 1179, 1191-1195, 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/home/admin/workarea/git/Velours/python/mtr/database_queries/datou_utils/util_portfolio_hashtag_ids.py 213 95 55% 18-19, 23-24, 29-128, 143, 146-147, 150, 154, 160-161, 169, 217-218, 223-226, 238-239, 276-277, 301, 304-305, 310, 313-314, 328, 331-332, 336, 339-340 /home/admin/workarea/git/Velours/python/mtr/database_queries/descriptor_queries.py 354 238 33% 23-42, 56, 63, 67, 73, 77, 82-103, 106-145, 163, 166, 169, 184, 218, 226-264, 270-301, 304-321, 333, 338, 349-352, 360-387, 390-400, 404-407, 412-435, 444-471, 474-477, 480-495, 499-556 /home/admin/workarea/git/Velours/python/mtr/database_queries/general_queries.py 148 61 59% 12-13, 33-34, 36-37, 45-46, 49, 59-61, 74, 83-95, 103-114, 122-133, 137-140, 151, 163-167, 182 /home/admin/workarea/git/Velours/python/mtr/database_queries/graph_nodes_queries.py 77 60 22% 28-34, 38-54, 59-130 /home/admin/workarea/git/Velours/python/mtr/database_queries/hashtag_queries.py 158 103 35% 46-50, 64-65, 72, 80-91, 94-110, 113-125, 128-133, 136-142, 145-155, 158-165, 168-183, 188, 196-207, 211-218, 221-226, 229-235 /home/admin/workarea/git/Velours/python/mtr/database_queries/mission_queries.py 520 478 8% 26-38, 42-250, 255-272, 275-314, 317-414, 418-430, 433-445, 448-460, 463-475, 479-491, 495-507, 510-522, 525-548, 551-552, 555-567, 570-582, 586-622, 625-644, 647-662, 665-671, 674-681, 697-741, 747-756, 773-799, 803-810, 815-822, 828-838, 841-843, 848-855, 859-873 /home/admin/workarea/git/Velours/python/mtr/database_queries/photo_insert_queries.py 105 81 23% 30-71, 79, 84-91, 94-103, 106-113, 118-138, 141-145, 149-163, 173-192, 203-218 /home/admin/workarea/git/Velours/python/mtr/database_queries/photo_retrieval_queries.py 558 401 28% 12, 51-61, 71-75, 96-101, 107-123, 129-142, 148-161, 180-181, 188, 199-200, 212, 217, 221, 224-226, 229-231, 234-237, 248, 254, 261-266, 269, 271, 274, 277-278, 288-326, 332-348, 351-425, 428-475, 481-492, 495-544, 547-548, 555-605, 608-631, 634-668, 675, 683, 695, 703, 711, 714, 719, 724-742, 750, 756-758, 761, 770, 774-776, 781-787, 790, 796-800, 805-826, 832-849, 852-864, 868-922, 946, 968, 975-986, 1002 /home/admin/workarea/git/Velours/python/mtr/database_queries/portfolio_queries.py 511 265 48% 39, 41, 56-72, 88, 97-114, 122, 130, 134, 140-158, 164, 170, 172-174, 176, 179, 188, 192, 198, 202-212, 215-222, 225-235, 240-255, 261, 266-271, 274-284, 287-299, 302-311, 321, 325, 339, 351, 354, 360-361, 365, 369-375, 378-383, 389, 393-397, 400-410, 425, 441, 447, 473-497, 516-517, 525, 548-571, 576-584, 589, 594, 598-608, 616, 620-622, 630, 637, 642-662, 684, 717-748, 750-759, 780-781, 783-786, 793-794, 796-799 /home/admin/workarea/git/Velours/python/mtr/datou/__init__.py 1 0 100% /home/admin/workarea/git/Velours/python/mtr/datou/calcul_brightness_image.py 76 70 8% 2-9, 13-39, 42-68, 71-78, 81-88, 91-98 /home/admin/workarea/git/Velours/python/mtr/datou/darker_image.py 39 4 90% 15, 19, 24, 60 /home/admin/workarea/git/Velours/python/mtr/datou/data_augmentation_imgaug.py 244 194 20% 16, 19-22, 25, 27-176, 188-193, 203, 241-303 /home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py 1753 982 44% 43-44, 75-101, 108-109, 112-113, 117-118, 153, 158, 188-189, 206-209, 212-213, 227-229, 241-243, 246-247, 277, 302-306, 311, 328-332, 335, 375, 397-398, 434, 462-463, 481-495, 509-516, 522-573, 580-624, 652-653, 660-663, 674-677, 700-702, 721, 729-730, 738-739, 773-776, 810, 818, 821, 823-825, 833-853, 863-870, 886-942, 968-1161, 1165, 1171-1174, 1178-1180, 1185-1186, 1191-1192, 1196-1198, 1201-1281, 1326-1334, 1348, 1351-1353, 1365-1376, 1379-1397, 1401-1450, 1454-1500, 1505-1545, 1550-1556, 1564, 1567, 1570-1571, 1574-1577, 1580, 1583, 1586-1588, 1596, 1605, 1613, 1621, 1635, 1657, 1662-1672, 1675-1678, 1682-1735, 1739-1742, 1747-1785, 1791, 1795-1804, 1811, 1820, 1828-1865, 1878-1894, 1903-1919, 1924-1941, 1945-1957, 1966-1969, 1975-1985, 1993-1996, 2002-2006, 2010, 2016, 2021-2024, 2032-2034, 2037-2041, 2045-2068, 2108, 2119, 2126-2129, 2148-2149, 2154-2203, 2206-2241, 2258-2264, 2267-2277, 2280-2282, 2313, 2316-2328, 2331-2332, 2343-2345, 2355, 2365-2366, 2371, 2376, 2422, 2428, 2432, 2440, 2442, 2448, 2451, 2453, 2455, 2461, 2463, 2465, 2467, 2469, 2473, 2475, 2477, 2479, 2481, 2483, 2485, 2487, 2489, 2491, 2493, 2495, 2497, 2499, 2505, 2511, 2515, 2519, 2521, 2525, 2528, 2534, 2536, 2538, 2540, 2542, 2544, 2548, 2550, 2552, 2555, 2559, 2562, 2564, 2570, 2572, 2574, 2577, 2584, 2586, 2588, 2590, 2592, 2594, 2596, 2598, 2603, 2605, 2607, 2609, 2611, 2617, 2619, 2621, 2635, 2638, 2640, 2642, 2644, 2648, 2650, 2656, 2658, 2660, 2663-2667, 2701-2703, 2718-2720, 2736, 2742-2744, 2746, 2751, 2760-2762, 2771-2774, 2783-2787, 2803, 2808, 2811, 2819-2833, 2837-2843, 2855-2873 /home/admin/workarea/git/Velours/python/mtr/datou/datou_lib_object.py 478 150 69% 16-23, 35-37, 46, 51-62, 101-122, 178, 194, 212, 215, 222-246, 252-290, 317, 335, 363-369, 374, 376, 385, 389, 396, 400, 412, 495, 499-500, 512-513, 522-523, 570, 579, 589, 616, 635-652, 660, 675-679, 688-689, 694, 723-743, 747-771 /home/admin/workarea/git/Velours/python/mtr/datou/datou_lib_step_data_increase.py 204 104 49% 32, 34-35, 93, 102, 125-162, 214-216, 221-294, 297-339 /home/admin/workarea/git/Velours/python/mtr/datou/datou_lib_step_save.py 1287 925 28% 24, 33-38, 45, 49-96, 101-145, 150, 155, 160-178, 183, 200-260, 269-305, 316, 324-325, 339-344, 347, 349, 361, 368-369, 374-436, 445-486, 489-553, 569, 580, 582, 593, 595, 604-608, 613-619, 638-744, 747-761, 764-779, 783-809, 813-864, 873-902, 907-936, 957, 962-965, 971-976, 979, 981, 1006-1008, 1012-1014, 1017-1018, 1047-1078, 1086-1087, 1095, 1098, 1102, 1138-1140, 1155-1157, 1172-1175, 1194-1198, 1223-1253, 1257-1279, 1295-1332, 1338-1357, 1362-1387, 1393-1457, 1472-1500, 1523-1534, 1538-1619, 1625, 1631-1632, 1654-1655, 1667, 1671, 1675, 1677, 1683, 1685, 1687, 1689-1690, 1692, 1694, 1696, 1698, 1700, 1703, 1705, 1708, 1710, 1712, 1716, 1719, 1721, 1730-1739, 1743-1745, 1749-1769, 1775-1783, 1786-1818, 1821-1836, 1840-1875 /home/admin/workarea/git/Velours/python/mtr/datou/datou_local_cache_db.py 157 117 25% 62-70, 73-84, 88-102, 105-113, 117-122, 126-136, 139-143, 167-175, 178-194, 197-201, 204-205, 214-218, 233-257, 287-301, 304-307, 311 /home/admin/workarea/git/Velours/python/mtr/datou/datou_step_finale.py 325 253 22% 9-77, 82-130, 135-351, 370-372, 375-376, 395, 413-426, 430, 435, 439-443, 473 /home/admin/workarea/git/Velours/python/mtr/datou/detect_blur_image.py 109 73 33% 12-15, 18-20, 24-34, 48, 55-64, 77, 87-145 /home/admin/workarea/git/Velours/python/mtr/datou/image_blanchir.py 30 2 93% 27, 31 /home/admin/workarea/git/Velours/python/mtr/datou/image_temperature.py 22 0 100% /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_deprecated.py 0 0 100% /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_end_or_aggreg.py 484 469 3% 17, 19, 21, 24, 27, 34-274, 288-767, 908-918 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_initialisation.py 372 326 12% 15-244, 249-267, 284-289, 304, 313-314, 317-331, 337-346, 358-360, 376-558 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_post_processing.py 1061 486 54% 52, 61-65, 72-77, 83-95, 99, 115-119, 141-142, 149-153, 161, 163, 179, 197-198, 228, 234-235, 256, 259-264, 273-279, 327-328, 356-363, 369, 371-449, 454-458, 481-482, 497-503, 506, 511-513, 538, 541-542, 547, 555, 568, 600-601, 604-605, 610-612, 615, 638-647, 653-655, 665, 675-681, 684-685, 689-694, 700-701, 704-705, 714-721, 724-732, 735-736, 752-757, 763-797, 802-815, 821-823, 843-845, 850-857, 874-924, 932-1006, 1011-1081, 1122-1124, 1128-1129, 1189, 1210-1231, 1243, 1249-1255, 2536-2538, 2541-2542, 2545-2552, 2562, 2569-2581, 2584, 2588-2592, 2599-2606, 2667-2669, 2762-2763, 2777-2778, 2789-2791, 2798-2808, 2816, 2848, 2859 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py 1402 793 43% 34-89, 124, 127, 133, 136-137, 150, 157-161, 172-177, 188-193, 233-235, 260-275, 281, 283, 289, 350, 354, 362-376, 391-399, 408-422, 425-426, 428-430, 432, 438, 440, 447, 485, 490-491, 497, 506, 510-696, 703-838, 843-885, 898-899, 908, 913-920, 928-929, 932-934, 956-960, 1003-1010, 1014-1021, 1024-1026, 1034, 1076-1077, 1087, 1095-1105, 1109-1111, 1119-1133, 1142-1143, 1156, 1174-1176, 1180, 1199-1200, 1204, 1220-1231, 1242, 1245-1246, 1251, 1255, 1259-1306, 1322-1323, 1344-1345, 1362-1459, 1485, 1502, 1508-1551, 1580-1581, 1586, 1596, 1620, 1623-1624, 1663-1666, 1670, 1677-1678, 1683, 1686, 1693-1699, 1703-1708, 1719-1733, 1779, 1812-1815, 1854-1856, 1929-1930, 1933-1934, 1939, 1948, 1954, 1959-1960, 1980-1985, 1989-2177 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_process.py 1963 1272 35% 40, 47-59, 75, 84-86, 89, 98, 104, 139, 143, 149-150, 162-174, 211, 232, 253-257, 280-308, 325-326, 331, 334-335, 338, 350, 386-387, 392-393, 401, 410-411, 415, 427-556, 560-628, 637, 651-652, 663-664, 669, 697, 702, 710, 724, 729, 736, 745, 749, 755-761, 764, 803-807, 816, 819-823, 827, 830, 832-845, 855-889, 917-918, 924, 927-929, 937-943, 970, 982, 992-1000, 1005, 1009, 1016-1026, 1032-1077, 1098, 1103-1106, 1109-1111, 1115, 1118-1137, 1161, 1163, 1166-1187, 1196-1272, 1279-1466, 1470-1499, 1503-1579, 1586-1674, 1678-1855, 1867, 1914, 1921-1924, 1931-1933, 1936, 1967-1968, 1972, 1976-1998, 2016-2017, 2031-2078, 2132, 2165-2168, 2213-2215, 2222-2236, 2239-2248, 2253-2254, 2257-2266, 2269-2290, 2292-2293, 2357-2369, 2373-2418, 2436, 2440-2441, 2452-2476, 2479, 2495, 2506, 2510, 2515-2619, 2626-2814, 3022-3033, 3038, 3041-3042, 3047-3049, 3052, 3076-3078, 3087, 3098-3110, 3121-3122, 3135, 3165, 3181, 3186-3193, 3452-3526, 3530-3569 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_send_or_copy.py 554 434 22% 19-195, 200-268, 273-332, 336-379, 383-488, 493-623, 665-666, 671, 675-676, 680, 689-692, 700-716, 719-720, 728-741, 749, 751-754, 770, 809, 814-816, 833-834, 839 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_sort.py 193 163 16% 12-115, 125-127, 143-144, 161, 178-183, 189-287, 291-305 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_util.py 298 137 54% 16-17, 21, 26, 40, 47-48, 70, 97-98, 106, 125-126, 143-155, 179-183, 194-196, 198-201, 213-219, 224-231, 241-257, 261-284, 289, 293-294, 297-300, 303-305, 307-309, 319-324, 327-333, 366-371, 395, 405, 409-411, 423-467 /home/admin/workarea/git/Velours/python/mtr/datou/merge_rubbia.py 50 46 8% 12-36, 40-86 /home/admin/workarea/git/Velours/python/mtr/lib/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/mtr/lib/fotonower_api/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/mtr/lib/fotonower_api/fotonower_connect.py 322 215 33% 73, 78-85, 88-90, 96-119, 123-184, 187-213, 220-221, 225, 230-231, 233-240, 252-253, 258-261, 267-279, 282, 285, 288-290, 307, 318, 323, 329, 332-335, 338-384, 389-412, 415-433, 436-461 /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py 299 238 20% 35-43, 49-298, 304-342, 359, 373-374, 383-387, 402, 423-429, 444-549 /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_segment.py 67 16 76% 40, 87, 107-117, 173, 190-191, 196-197, 222 /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/prepare_maskdata.py 359 81 77% 28, 51, 62, 78, 83, 120-121, 140-141, 145-146, 148-149, 154-155, 164, 176-177, 187, 195, 198, 202, 218-220, 241-243, 246, 269-270, 290-293, 315, 317-318, 321, 326-332, 335-342, 347-348, 360-369, 391-393, 400-403, 411-414, 424-427, 429, 460-462, 502-504, 513-514, 545 /home/admin/workarea/git/Velours/python/mtr/math_fotonower/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/mtr/math_fotonower/svm_subroutines.py 69 63 9% 21-43, 50-99, 104-136 /home/admin/workarea/git/Velours/python/mtr/math_fotonower/timeseries/__init__.py 1 0 100% /home/admin/workarea/git/Velours/python/mtr/math_fotonower/timeseries/class_split_time_score.py 506 157 69% 48-49, 54, 73, 77, 85, 96, 114, 138-139, 145-146, 155, 237, 261, 267, 270, 283-292, 295, 298, 322, 325, 328, 331-342, 352-356, 367, 380-385, 412, 442, 444, 486, 498, 501, 513, 561-566, 570, 579, 595-599, 604-610, 615-621, 626-642, 645, 648, 651-667, 670-673, 676-679, 682-685, 688-695, 698-732 /home/admin/workarea/git/Velours/python/mtr/math_fotonower/timeseries/lib_split_time_score.py 1938 923 52% 19-36, 42, 78, 84-85, 96-104, 108-115, 125-136, 139-141, 182-185, 207-231, 236-411, 416-647, 654-729, 745-747, 752-776, 784-864, 868-886, 897-1001, 1006-1088, 1103, 1108, 1115, 1121-1134, 1139-1206, 1209-1250, 1255-1264, 1267-1342, 1345-1363, 1368-1405, 1410-1434, 1439-1458, 1686-1691, 1694-1712, 1759-1763, 1812, 1835-1855, 1939-1940, 1990, 2019, 2041-2096, 2166, 2169-2173, 2185, 2208, 2221, 2242-2243, 2265-2269, 2351, 2417, 2422, 2448-2452, 2538-2540, 2575-2576, 2607-2608, 2622-2624, 2641-2668, 2750-2751, 2768, 2815-2817, 2834-2836, 2870-2871, 2879-2892, 2907-2908, 2915, 2937-2938, 2945, 2953-2957, 2963-2967, 2977, 2990-2994, 3005, 3049-3100, 3108-3116, 3143-3145, 3164, 3170-3171, 3180-3182, 3184, 3211-3213, 3219, 3231-3232, 3240-3261, 3268, 3314, 3320-3389, 3398-3456, 3487-3488, 3534-3536, 3570, 3625, 3638, 3671-3716, 3748-3754, 3822-3823, 3848, 3854-3855, 3861, 3874-3875, 3889, 3896, 3911-3929, 3939-3957, 3964, 3968-4002 /home/admin/workarea/git/Velours/python/mtr/mem_info.py 76 30 61% 33-34, 41, 49, 59-63, 72, 95-124 /home/admin/workarea/git/Velours/python/mtr/monitor_sys.py 131 53 60% 40, 44, 47-50, 52, 61, 65-68, 98, 102, 104, 108, 110, 112, 114, 116, 124, 131, 143-144, 150, 162, 164-167, 170-194 /home/admin/workarea/git/Velours/python/mtr/ses_mailer.py 55 34 38% 35-36, 42-44, 47-85 /home/admin/workarea/git/Velours/python/mtr/simple_image_editor/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/mtr/simple_image_editor/flip_images.py 241 88 63% 20-91, 98-105, 111-114, 138-139, 155, 164-171, 177-180, 204-205, 220, 236, 243, 246, 253-254, 263, 268, 306-307, 311, 333, 338, 349, 378 /home/admin/workarea/git/Velours/python/mtr/simple_image_editor/image_utils.py 328 225 31% 21-28, 37-52, 88, 91-113, 121, 129, 142, 144-162, 181-191, 194-236, 242-253, 265-298, 301-314, 343, 348-354, 363-365, 368-381, 385-397, 401-441, 446-465, 470-473, 476-484 /home/admin/workarea/git/Velours/python/mtr/simple_image_editor/rotate_crop_and_images.py 894 306 66% 62, 65, 80-81, 97, 120, 139-140, 150-151, 176, 208, 212, 217-218, 223, 227-230, 239-241, 262, 268, 275, 297-310, 318-319, 333-334, 359-360, 370, 400-401, 412-413, 442, 457, 460, 481-482, 494, 497-498, 501, 521-524, 528, 531, 534, 543-546, 553-554, 571-572, 579-580, 584, 603, 606, 609, 618, 624, 634, 679-681, 690, 712-725, 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2961, 2964, 2979, 3007-3008, 3041-3042, 3080, 3102, 3140-3156, 3164-3189, 3200-3304, 3339, 3359-3360, 3362-3363, 3387, 3409-3417, 3508-3540, 3562, 3579-3590, 3594-3600, 3603-3682, 3685-3688, 3691-3723, 3726-3752, 3757-3819, 3825-3877 /home/admin/workarea/git/Velours/python/mtr/split_time_gps_score.py 723 514 29% 14-26, 36-68, 78-89, 106-107, 119-141, 151-182, 232, 236, 244-256, 299-300, 311, 314, 360-379, 399-401, 451-484, 488-509, 526-554, 558-596, 614, 631-634, 646, 649-650, 658, 665-671, 691-700, 713-721, 732-799, 812-865, 869-877, 881-893, 903-938, 948-987, 999-1034, 1046-1070, 1079, 1092-1093, 1097-1310 /home/admin/workarea/git/Velours/python/mtr/tfhub2/data_ops.py 228 196 14% 18-26, 29-37, 41-49, 52-60, 63-68, 71-82, 85-93, 96-117, 120-129, 132-149, 152-183, 187-189, 193-211, 215-229, 232-249, 271-302 /home/admin/workarea/git/Velours/python/mtr/tfhub2/evaluate.py 162 51 69% 42, 44-52, 86, 99, 110-111, 115, 128-131, 139, 173-181, 186-231, 246, 281-282, 293, 295 /home/admin/workarea/git/Velours/python/mtr/tfhub2/foto_datasets.py 242 131 46% 23-25, 41-51, 64-66, 82, 85, 95-108, 117-119, 122-123, 131, 136-137, 139-140, 153-168, 173-240, 246, 251, 256, 264, 271, 287-322, 341, 343, 366, 379-381, 386, 391, 395-401 /home/admin/workarea/git/Velours/python/mtr/tfhub2/fotonower_data_ops.py 111 94 15% 19-23, 26-30, 33-38, 41-44, 48-84, 91-144, 148-182, 186-192 /home/admin/workarea/git/Velours/python/mtr/tfhub2/ops.py 201 170 15% 29-31, 40, 44, 48, 60, 65-72, 76-129, 139-151, 155-167, 171-177, 182-186, 191-202, 207-210, 219-244, 254-280, 290-319, 324-326, 334-343, 346-348, 351-358, 362-373, 377-394 /home/admin/workarea/git/Velours/python/mtr/utils/MTRMongoClient.py 99 87 12% 21-92, 97-208, 213-241 /home/admin/workarea/git/Velours/python/mtr/utils/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/mtr/utils/cd.py 11 0 100% /home/admin/workarea/git/Velours/python/mtr/utils/cdn/copy_to_ovh.py 14 2 86% 16, 27 /home/admin/workarea/git/Velours/python/mtr/utils/cdn/s3_bucket_manager.py 112 88 21% 33-40, 43-48, 51-54, 57-69, 75-84, 97-104, 119-125, 128-132, 140-159, 162-166, 169-175, 179-182, 185-186, 189-190 /home/admin/workarea/git/Velours/python/mtr/utils/cdn/swift_upload_manager.py 151 73 52% 44, 47-48, 54, 63, 72-73, 76-79, 105, 107, 125-127, 130, 133-142, 145-156, 163, 180-184, 187-193, 197-210, 213, 216-217, 223-239 /home/admin/workarea/git/Velours/python/mtr/utils/general_util.py 57 32 44% 11-12, 20-27, 30, 33-57, 61-63, 69-70, 75, 86-90 /home/admin/workarea/git/Velours/python/mtr/utils/kmean_cloud_storage.py 15 5 67% 19-20, 23, 26, 29 /home/admin/workarea/git/Velours/python/mtr/utils/load_caffe.py 61 26 57% 23, 29, 43, 48, 55, 61-62, 65, 70, 76-94 /home/admin/workarea/git/Velours/python/mtr/utils/prepare_photo_learning.py 201 125 38% 14-15, 62-81, 89, 94-97, 103, 114, 123-124, 131, 137, 140, 154, 156-158, 176, 189-232, 238-365 /home/admin/workarea/git/Velours/python/mtr/utils/upload_batch.py 58 19 67% 37-39, 46-47, 55-58, 68-78 /home/admin/workarea/git/Velours/python/mtr/utils/utils_timer.py 11 3 73% 13-15 /home/admin/workarea/git/Velours/python/prod/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/prod/caffe_vision.py 1390 1154 17% 47, 68-72, 77-81, 110-112, 118-121, 131-132, 143, 149, 156-170, 173-175, 181, 184, 189, 192, 213-214, 220-274, 285, 313-315, 321, 326, 333-337, 340-344, 347-351, 360-367, 381, 394-395, 400, 410-416, 419-421, 431-573, 577-592, 595-602, 606-759, 763-782, 787-810, 814-877, 883-889, 894-901, 907-926, 934-947, 954-958, 964-981, 986-1001, 1008-1028, 1039, 1052, 1074-1076, 1082, 1085, 1095, 1099, 1103, 1116-1121, 1126-1333, 1401-2359 /home/admin/workarea/git/Velours/python/prod/cod/main_cod.py 567 283 50% 16-24, 27-43, 46, 49-50, 54, 60-90, 95-96, 107-108, 129, 134-137, 147-150, 156-159, 168-170, 172-174, 179-181, 187, 201, 209-212, 218, 222-223, 261-262, 272, 319-339, 345-362, 367, 373-375, 378-381, 386-421, 445-455, 476, 488-510, 529-530, 532-534, 538-543, 546-547, 574, 585, 601-602, 612, 624-630, 635-652, 661-662, 671-672, 675-676, 701-806 /home/admin/workarea/git/Velours/python/prod/memo/SLA_RUBBIA.py 546 200 63% 13-14, 115-116, 125-135, 149-164, 185-188, 196-223, 227, 229-230, 234-238, 257-258, 267-268, 270-273, 276, 287-295, 308-310, 317-320, 363, 383-427, 444-450, 452-453, 460-470, 484, 492, 505, 515-517, 525-527, 536, 540, 543-547, 549-550, 553, 561, 568-573, 620-622, 625-628, 643-646, 661-662, 666-667, 671-672, 675, 681-683, 693-695, 719, 725, 727-728, 734, 745, 749, 760-761, 774 /home/admin/workarea/git/Velours/python/prod/memo/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/prod/memo/example_of_unwanted_materials.py 90 58 36% 13-15, 43-62, 86-100, 104-126, 130-163, 167-170, 174-179 /home/admin/workarea/git/Velours/python/prod/memo/lib_sla.py 333 75 77% 19, 49, 68, 75, 79, 99-115, 132, 135, 185, 194-195, 230-231, 234, 240, 249-250, 257-258, 261-262, 280-282, 286-288, 293, 306-308, 368, 376-381, 385-399, 419, 453, 487, 504, 521-525, 544-547, 550-554, 585, 596-601 /home/admin/workarea/git/Velours/python/prod/memo/memo.py 833 286 66% 46, 52, 76, 82, 110, 159, 230-231, 236-238, 245-247, 249-252, 255-257, 260, 285-286, 304, 307, 310-311, 316-318, 321-329, 336-337, 342-343, 349-350, 358-361, 371-372, 407, 433, 441, 443, 455-535, 591-593, 607-610, 613-617, 679-714, 762-764, 778-781, 848-850, 864-874, 915-917, 924-925, 957-963, 986, 1022-1027, 1041, 1060, 1073, 1079, 1082, 1088, 1094, 1099, 1104, 1109, 1111-1112, 1118-1172, 1198-1249, 1254-1261, 1292-1293, 1315-1319, 1322-1336 /home/admin/workarea/git/Velours/python/prod/non_supervised_algorithm.py 131 59 55% 40, 58, 72-73, 155, 160, 165-166, 175-264 /home/admin/workarea/git/Velours/python/prod/vision_faster_rcnn.py 244 171 30% 13-16, 61-89, 98, 133-137, 145-172, 178-219, 223-360, 378-380, 398, 401, 415-458 /home/admin/workarea/git/Velours/python/tests/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/tests/cache_photo_data_test.py 74 20 73% 41, 49-62, 84, 90-94 /home/admin/workarea/git/Velours/python/tests/cod_main_test.py 75 12 84% 32, 57, 92, 98-101, 122, 128, 131, 134, 138 /home/admin/workarea/git/Velours/python/tests/datou_test.py 1923 646 66% 37, 43-45, 51-52, 58-60, 66-70, 101-104, 108, 122-126, 157-159, 186-188, 194-197, 203-205, 213-215, 221-224, 230-232, 241, 271-276, 283, 302-304, 317, 333, 352-354, 360-364, 378-416, 448-450, 457, 464-466, 499-501, 510-513, 540-542, 546, 549, 553, 568-569, 579, 582-583, 588, 626-628, 631, 645-646, 656, 660-661, 674-675, 681, 707-709, 729, 731, 737-739, 743-745, 777-779, 790-791, 814, 816, 822-824, 828-830, 866-868, 886-887, 915-917, 935-936, 962, 968-970, 983-987, 998, 1025, 1031-1033, 1046-1050, 1066, 1071, 1099-1101, 1111, 1118, 1174, 1291, 1298-1301, 1317, 1323, 1333, 1374, 1380-1383, 1807-1809, 1846, 1852-1855, 1874-1878, 1920, 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36-38, 76, 89, 99, 136, 149 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/federation/projects.py 5 0 100% /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/federation/protocols.py 31 16 48% 38-49, 52-54, 72, 90, 105, 123, 141 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/federation/saml.py 16 9 44% 37-40, 56-59, 62-79 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/federation/service_providers.py 22 8 64% 38-40, 52, 65, 75, 89, 102 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/oauth1/__init__.py 1 0 100% /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/oauth1/access_tokens.py 20 9 55% 23-24, 38-51 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/oauth1/consumers.py 17 4 76% 38, 43, 47, 53 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/oauth1/core.py 20 5 75% 28-29, 62-65 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/oauth1/request_tokens.py 33 20 39% 24-25, 30-36, 54-57, 60-73 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117 21% 84-106, 131-205, 279-340, 423-438, 442, 468-495, 499, 525-552, 559-562, 580-586, 590-592, 616-627, 631, 651-661, 681-691, 695-697, 716-729, 739-743 /usr/lib/python3/dist-packages/oauthlib/oauth1/rfc5849/utils.py 40 22 45% 31-32, 40-44, 55-60, 64-66, 72, 78, 83-90 /usr/lib/python3/dist-packages/os_service_types/__init__.py 9 3 67% 39-41 /usr/lib/python3/dist-packages/os_service_types/data/__init__.py 8 0 100% /usr/lib/python3/dist-packages/os_service_types/exc.py 10 2 80% 24-25 /usr/lib/python3/dist-packages/os_service_types/service_types.py 111 69 38% 28-29, 59, 64-71, 75-78, 83, 88, 93, 98, 103, 108, 114, 120, 129-133, 141-144, 152, 160-161, 169, 191-202, 210-211, 221-234, 242-245, 254-258, 269-270, 281-285 /usr/lib/python3/dist-packages/oslo_config/__init__.py 0 0 100% /usr/lib/python3/dist-packages/oslo_config/cfg.py 1258 889 29% 38-39, 77, 80, 87, 94-97, 104-105, 108-109, 116, 119, 126, 129, 136-137, 140-141, 149, 156, 159, 167, 170, 178, 181, 188-189, 192, 211, 237-248, 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0 0 100% /usr/lib/python3/dist-packages/oslo_serialization/__init__.py 0 0 100% /usr/lib/python3/dist-packages/oslo_serialization/jsonutils.py 82 52 37% 85-181, 217, 235-236, 248, 260, 268-270 /usr/lib/python3/dist-packages/oslo_utils/__init__.py 0 0 100% /usr/lib/python3/dist-packages/oslo_utils/_i18n.py 4 0 100% /usr/lib/python3/dist-packages/oslo_utils/encodeutils.py 60 53 12% 38-63, 84-104, 114-119, 135-188 /usr/lib/python3/dist-packages/oslo_utils/importutils.py 40 24 40% 29-34, 44, 60-65, 92-97, 117-122 /usr/lib/python3/dist-packages/oslo_utils/reflection.py 107 83 22% 44-47, 55-58, 63, 78-96, 107-111, 121-153, 158-163, 168-186, 191, 196, 208-214, 219-220 /usr/lib/python3/dist-packages/oslo_utils/strutils.py 183 135 26% 127, 146-165, 177-178, 214-247, 265-272, 333-359, 416-441, 453-456, 470-488, 503-520, 545-569, 579-586 /usr/lib/python3/dist-packages/oslo_utils/timeutils.py 230 155 33% 35, 56-64, 71-74, 95-97, 102, 109, 120-125, 135-140, 151-165, 177-180, 182, 201, 217, 226-231, 240, 249, 258-267, 283-297, 306-307, 318-319, 333-334, 339, 344, 347-349, 379-396, 421-428, 435-441, 446, 450-459, 465-468, 473, 477-486, 490-491, 495-498, 508-516, 520-525, 529, 533, 537-541, 546-553 /usr/lib/python3/dist-packages/paramiko/__init__.py 34 0 100% /usr/lib/python3/dist-packages/paramiko/_version.py 2 0 100% /usr/lib/python3/dist-packages/paramiko/agent.py 223 152 32% 64-72, 75-78, 81-85, 88-96, 105-107, 110-126, 129-150, 153-155, 165, 173-180, 189-190, 193, 210-213, 216, 222-241, 248-252, 263-269, 272, 275-279, 286-290, 299, 302, 328-331, 334, 337, 340-341, 363-368, 370-375, 379, 385, 396-399, 402, 405, 408, 411-419 /usr/lib/python3/dist-packages/paramiko/auth_handler.py 521 373 28% 105-108, 111-118, 132-140, 146-155, 158-167, 170-177, 180-181, 192-198, 201-207, 219-220, 233-236, 239-240, 249, 254-270, 282-284, 290-291, 300-397, 402, 408-428, 432-441, 444-615, 630-632, 634-641, 654-656, 660-678, 681-694, 699-706, 737, 752-753, 756-757, 761, 765, 769, 773, 776, 779-802, 805-826, 829-830, 833-834, 847 /usr/lib/python3/dist-packages/paramiko/ber.py 84 66 21% 34-35, 38, 41, 44, 47, 50-93, 97-104, 108-114, 117-129, 135-138 /usr/lib/python3/dist-packages/paramiko/buffered_pipe.py 93 45 52% 55-59, 64, 77-90, 99-106, 118-124, 155, 162-164, 171-174, 188-196, 208, 218-222 /usr/lib/python3/dist-packages/paramiko/channel.py 597 342 43% 71, 139-142, 148-161, 190-203, 223-230, 275-283, 300-309, 330-335, 355-362, 377, 402-404, 419-425, 474-492, 509-516, 522, 532, 538, 549, 572-584, 612, 632-635, 645, 654-671, 683, 700-701, 706-710, 727, 748-749, 754-758, 775-781, 798-801, 821-825, 845-848, 866-869, 933-944, 959, 967, 979, 997, 1032-1039, 1042-1047, 1050-1060, 1067, 1082-1155, 1157-1163, 1173, 1192-1209, 1223-1226, 1238, 1254, 1267-1274, 1281-1292, 1305-1333, 1358, 1364-1365, 1379-1380 /usr/lib/python3/dist-packages/paramiko/client.py 275 127 54% 100-108, 126-127, 142-148, 161, 170, 191, 215-216, 345-348, 352-360, 368, 385, 387, 389, 394, 401-404, 419-423, 426, 430-433, 459-466, 510, 513, 545-548, 556, 566, 580-581, 596-597, 632, 637-641, 648-653, 656-670, 674-687, 694-707, 727, 730, 745, 749-765, 789, 801, 817-823, 835 /usr/lib/python3/dist-packages/paramiko/common.py 93 4 96% 186-187, 207-211 /usr/lib/python3/dist-packages/paramiko/compress.py 12 4 67% 29, 32, 37, 40 /usr/lib/python3/dist-packages/paramiko/config.py 130 107 18% 50, 58-94, 126-147, 154-157, 160-166, 180-239, 245-248, 257-259, 262-303, 342, 358-361, 372 /usr/lib/python3/dist-packages/paramiko/dsskey.py 115 86 25% 55-81, 84-90, 93, 96, 99, 102, 105, 108-130, 133-159, 162-172, 180-190, 207-219, 224-225, 228-229, 234-247 /usr/lib/python3/dist-packages/paramiko/ecdsakey.py 158 107 32% 77, 80-82, 85-87, 90-92, 119-168, 172, 175-192, 195, 198, 207, 210, 213, 216-223, 226-239, 242, 250, 266-273, 278-279, 282-283, 286-296, 299-302, 305-308 /usr/lib/python3/dist-packages/paramiko/ed25519key.py 122 36 70% 42-47, 68, 79-80, 86, 102, 113-123, 126, 132, 139-154, 160, 165, 184, 198-202, 208, 221, 225-226 /usr/lib/python3/dist-packages/paramiko/file.py 250 156 38% 76-78, 98-111, 125-128, 138, 148, 158, 168-170, 189-229, 255, 257, 268-273, 277-283, 289, 292-293, 298-334, 352-355, 376, 386, 397-422, 433-435, 442, 446, 456, 463, 474, 492, 494-496, 506-508, 512-516, 522-529, 536-545 /usr/lib/python3/dist-packages/paramiko/hostkeys.py 200 138 31% 27, 63, 75-77, 95-110, 125-129, 144-146, 149-150, 153, 156-160, 163-166, 169-180, 183, 191-192, 195, 203-211, 223-229, 235, 238-239, 242, 248, 251-258, 262-273, 277-282, 285-288, 301-310, 315-317, 343-374, 382-388, 391 /usr/lib/python3/dist-packages/paramiko/kex_curve25519.py 82 29 65% 31-32, 39, 47-48, 62, 65, 70-100 /usr/lib/python3/dist-packages/paramiko/kex_ecdh_nist.py 87 59 32% 26-30, 33-47, 50-54, 59-63, 66-106, 109-137 /usr/lib/python3/dist-packages/paramiko/kex_gex.py 181 153 15% 61-68, 71-91, 94-105, 111-125, 128-163, 168-190, 193-210, 213-251, 254-282 /usr/lib/python3/dist-packages/paramiko/kex_group1.py 85 62 27% 51-54, 57-69, 72-77, 89-96, 100-121, 125-154 /usr/lib/python3/dist-packages/paramiko/kex_group14.py 11 0 100% /usr/lib/python3/dist-packages/paramiko/kex_group16.py 9 0 100% /usr/lib/python3/dist-packages/paramiko/kex_gss.py 345 294 15% 84-89, 95-110, 124-135, 148-153, 162-166, 175-189, 199-234, 243-288, 303-307, 342-351, 357-370, 379-394, 400-414, 423-458, 466-486, 499-551, 562-566, 574-588, 596-638, 651-655, 674, 677, 680 /usr/lib/python3/dist-packages/paramiko/message.py 104 24 77% 60, 86-89, 111, 123, 138-142, 156, 164, 241-246, 254-255, 291, 293, 295 /usr/lib/python3/dist-packages/paramiko/packet.py 372 118 68% 59-62, 132, 173-174, 207, 210, 213-214, 217, 220, 223, 226, 242-244, 247, 272, 300-302, 306, 310, 315-328, 331, 333, 344-359, 361-363, 371, 374, 377, 405, 410, 413-417, 421, 437, 451-457, 471-484, 489, 494, 503, 515, 527, 532, 540, 546, 558-566, 573-580, 586, 588, 597-603, 613-616, 624, 626-637, 655, 660 /usr/lib/python3/dist-packages/paramiko/pipe.py 84 60 29% 34-38, 43-46, 49-52, 55, 58-61, 64-67, 70-71, 81-93, 96-99, 102, 105-108, 111-114, 117-118, 123-125, 128-130, 133-135, 144-148 /usr/lib/python3/dist-packages/paramiko/pkey.py 183 97 47% 82, 90, 93, 107-111, 114, 124, 133, 140, 161, 171, 183, 227-228, 242, 255, 287, 289, 297-298, 307-308, 313-338, 362-367, 370-375, 402, 415-426, 447-457, 487-489, 496-498, 505-525, 535-536, 539-542, 546, 549 /usr/lib/python3/dist-packages/paramiko/primes.py 69 58 16% 32-49, 60-61, 64-107, 113-122, 125-148 /usr/lib/python3/dist-packages/paramiko/proxy.py 51 33 35% 53-59, 68-76, 86-109, 112, 116, 121, 124 /usr/lib/python3/dist-packages/paramiko/py3compat.py 101 59 42% 32-102, 124, 132-133, 148-151, 154, 162, 165 /usr/lib/python3/dist-packages/paramiko/rsakey.py 89 34 62% 52-53, 57-67, 73, 80, 94-99, 102, 110, 113, 126-139, 142, 150, 167-170, 179-180, 187-188 /usr/lib/python3/dist-packages/paramiko/server.py 98 60 39% 88, 105, 124, 149, 181, 206, 237, 265-267, 297-299, 310-311, 332, 343, 373, 398, 414, 433, 457-463, 483, 509, 522, 562, 580, 594, 614-621, 633, 665-669, 676, 679-695, 721, 730 /usr/lib/python3/dist-packages/paramiko/sftp.py 89 57 36% 126-128, 133-140, 145-155, 158, 161-168, 171-191, 194-198, 201-213 /usr/lib/python3/dist-packages/paramiko/sftp_attr.py 150 127 15% 54-61, 73-82, 85, 90-96, 99-113, 116-144, 147-159, 163-170, 174-233, 243 /usr/lib/python3/dist-packages/paramiko/sftp_client.py 351 290 17% 78-84, 113-133, 164-170, 173-182, 194-195, 204, 218, 237-260, 276-324, 358-382, 396-398, 420-423, 440-443, 456-460, 468-470, 491-496, 509-514, 523-526, 537-541, 554-558, 574-580, 591-595, 606-616, 630-638, 656-662, 673, 676-685, 714-727, 757-759, 778-781, 801-805, 812-813, 817-838, 842-875, 878-880, 886-898, 905-913 /usr/lib/python3/dist-packages/paramiko/sftp_file.py 225 183 19% 62-73, 76, 82, 92-110, 113-128, 139-147, 157-177, 180-190, 194-212, 225, 234, 246, 256, 264-272, 283-286, 296-301, 313-319, 334-341, 351-356, 404-416, 436, 465-476, 492-515, 520-523, 526-531, 536-541, 544-563, 567-570 /usr/lib/python3/dist-packages/paramiko/sftp_handle.py 67 51 24% 49-53, 67-72, 92-106, 126-144, 157, 168, 178, 185-187, 190, 193 /usr/lib/python3/dist-packages/paramiko/sftp_server.py 322 290 10% 117-126, 129-135, 140-165, 168-177, 189-196, 213-223, 228-243, 246-256, 259-266, 269-277, 280-291, 298-358, 362-376, 379-536 /usr/lib/python3/dist-packages/paramiko/sftp_si.py 42 21 50% 51, 59, 68, 108, 140, 156, 174, 184, 208, 222, 239, 251, 266, 282-289, 302, 316 /usr/lib/python3/dist-packages/paramiko/ssh_exception.py 59 30 49% 65-67, 70, 83-84, 87, 102-104, 107, 122-125, 128-131, 147-149, 152, 185-195, 198 /usr/lib/python3/dist-packages/paramiko/ssh_gss.py 253 198 22% 51-57, 64-68, 100-107, 122-141, 151-152, 161, 175-183, 192-197, 208, 227-236, 253-263, 287-319, 334-346, 360-366, 378-392, 401-403, 416, 421, 438-448, 473-498, 514-526, 540-546, 558-572, 582-584, 596, 612-621, 643-675, 690-702, 715-724, 736-754, 763, 778 /usr/lib/python3/dist-packages/paramiko/transport.py 1294 636 51% 121-122, 401-406, 409-427, 457-458, 557-576, 588-589, 598, 626-632, 672-674, 683-686, 690, 734-756, 770, 787-791, 819-832, 838-843, 859, 921, 935, 947, 994, 1008-1011, 1013-1014, 1028-1031, 1035, 1039-1042, 1077-1096, 1107-1110, 1122, 1135-1140, 1155-1166, 1180-1183, 1202-1220, 1232-1245, 1307-1363, 1399-1403, 1414, 1428-1430, 1441-1443, 1466-1471, 1520-1556, 1595, 1599, 1604, 1650-1658, 1668-1681, 1699-1707, 1724-1730, 1743-1745, 1767, 1778, 1793, 1809-1812, 1815-1835, 1841-1842, 1848, 1854-1855, 1875-1878, 1882-1884, 1910, 1912, 1933-1934, 1940-1946, 1951, 1964-1971, 1975-1982, 1985-1990, 2020-2038, 2049-2050, 2068, 2092, 2095-2096, 2098-2099, 2101-2102, 2109-2112, 2125, 2133-2147, 2155-2170, 2172-2217, 2227, 2241, 2253, 2256-2259, 2264, 2266, 2279, 2283-2284, 2302-2317, 2354, 2371, 2442, 2451, 2459, 2466-2472, 2482, 2487, 2493-2499, 2519, 2529-2532, 2543, 2551-2557, 2580-2582, 2609-2610, 2627, 2637-2638, 2662-2663, 2680, 2691-2692, 2702-2704, 2706-2708, 2719, 2739-2741, 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85-89, 93-122, 148-158, 164-173, 186-217, 244-254, 262-273, 285-306 /usr/lib/python3/dist-packages/pexpect/pty_spawn.py 301 249 17% 22-25, 189-205, 211-237, 255-310, 314, 323-330, 341, 360-371, 379, 413, 436-485, 493, 501-502, 539-546, 554-555, 559-561, 572-574, 586-587, 593-594, 598, 602, 607, 615-647, 661-671, 680-690, 699-700, 705, 713, 758-768, 774-776, 782, 791-827, 832-833 /usr/lib/python3/dist-packages/pexpect/run.py 48 42 12% 95-148, 154-155 /usr/lib/python3/dist-packages/pexpect/spawnbase.py 224 182 19% 17, 21, 35-122, 125-131, 137-139, 142-144, 147, 150-151, 165-180, 183, 216-238, 334-340, 357-369, 389-418, 427-428, 437-457, 471-478, 483, 493-499, 504, 509, 513, 517, 522 /usr/lib/python3/dist-packages/pexpect/utils.py 105 90 14% 10-12, 17, 26-45, 54-66, 76-127, 139-156, 163-187 /usr/lib/python3/dist-packages/pkg_resources/__init__.py 1579 855 46% 48-50, 54-55, 65-67, 76-77, 93, 97-98, 131-132, 144-148, 152-155, 159, 163-164, 168, 172, 194-198, 256, 271, 275, 278, 285-288, 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45% 59, 74-78, 87-89 /usr/lib/python3/dist-packages/stevedore/named.py 34 24 29% 74-89, 123-129, 134-140, 143-146, 154-156 /usr/lib/python3/dist-packages/swiftclient/__init__.py 7 2 71% 31-32 /usr/lib/python3/dist-packages/swiftclient/client.py 959 551 43% 53-63, 71-72, 75-76, 89, 128-135, 146-156, 164-190, 195, 197-208, 214-217, 220-221, 232, 242, 257, 275-276, 279, 282, 285-288, 291, 294, 320-328, 331-368, 411, 417, 421-424, 427-430, 441, 459, 490, 495, 524-526, 536-567, 573-574, 594-600, 604, 611-612, 615, 639-646, 658-659, 694-700, 702, 715, 720, 725-727, 738, 743, 796, 798, 801, 803-813, 817, 819, 821, 823, 825, 836, 838, 857-875, 896-921, 953, 955-970, 975, 977, 981, 983, 985, 987, 990, 992, 1004, 1007, 1027-1048, 1068-1092, 1111-1133, 1155-1180, 1213, 1216, 1221, 1228, 1231-1234, 1236, 1262-1285, 1332, 1339, 1341, 1347, 1349, 1351, 1355, 1357, 1362, 1364, 1367, 1375, 1379-1387, 1397, 1420-1439, 1465-1503, 1529-1557, 1568-1578, 1656, 1660, 1677-1679, 1694-1702, 1722-1727, 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/usr/lib/python3/dist-packages/urllib3/util/__init__.py 10 0 100% /usr/lib/python3/dist-packages/urllib3/util/connection.py 66 18 73% 19, 21, 25-26, 53, 73, 77-86, 91, 118, 130-131 /usr/lib/python3/dist-packages/urllib3/util/queue.py 14 1 93% 7 /usr/lib/python3/dist-packages/urllib3/util/request.py 50 22 56% 13, 63, 65, 71, 74, 77, 80, 85, 96, 98-103, 119-133 /usr/lib/python3/dist-packages/urllib3/util/response.py 35 17 51% 19-35, 55, 71, 83-86 /usr/lib/python3/dist-packages/urllib3/util/retry.py 150 95 37% 186-187, 202-218, 223-232, 240-249, 253-265, 270-275, 278-283, 286-289, 300-305, 311, 317, 339, 350-355, 376-442, 445 /usr/lib/python3/dist-packages/urllib3/util/ssl_.py 148 78 47% 31-34, 43-44, 50-56, 61-63, 104-149, 162-174, 193, 198, 201, 211-217, 332, 337-348, 354, 357-360, 372-383, 395, 401-407 /usr/lib/python3/dist-packages/urllib3/util/timeout.py 63 25 60% 102, 121, 126-153, 192, 204-208, 223-226, 252-254, 256 /usr/lib/python3/dist-packages/urllib3/util/url.py 205 82 60% 102, 112, 117-122, 127-129, 150-169, 172, 193-207, 239, 252, 258-259, 264, 269, 277, 282-294, 299, 304-314, 354, 358, 372, 374-376, 379-381, 391-394, 401-404, 411, 431-432 /usr/lib/python3/dist-packages/urllib3/util/wait.py 76 37 51% 8-9, 48-68, 72-87, 92, 97, 111, 121-122, 135-138, 153 /usr/lib/python3/dist-packages/yaml/__init__.py 184 118 36% 15-16, 31-37, 45, 62-67, 73-78, 85-89, 96-101, 123-132, 142, 152, 162, 172, 182, 192, 201-213, 224-243, 250, 262-283, 290, 298, 306, 316-322, 331-337, 345-350, 359-364, 373, 382, 391-397, 418, 425 /usr/lib/python3/dist-packages/yaml/composer.py 92 31 66% 18-22, 26-27, 40-41, 65-70, 74-75, 82, 96, 100-115, 126 /usr/lib/python3/dist-packages/yaml/constructor.py 479 295 38% 32, 38-39, 44-45, 52, 61, 69, 71-72, 74, 82-98, 102, 107-108, 114, 119, 125-129, 134, 141, 148-157, 175-177, 186-204, 208-209, 213, 221-222, 234-235, 242, 244, 246, 248, 250, 252, 254-261, 271-292, 295-307, 323-350, 356-373, 377-394, 397-400, 406-408, 417-424, 427, 487, 490-492, 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/usr/lib/python3/dist-packages/yaml/events.py 61 6 90% 9-13, 17-19 /usr/lib/python3/dist-packages/yaml/loader.py 47 24 49% 14-19, 34-39, 44-49, 58-63 /usr/lib/python3/dist-packages/yaml/nodes.py 29 7 76% 4-7, 9-23 /usr/lib/python3/dist-packages/yaml/parser.py 352 210 40% 101, 110-111, 157, 163, 167-180, 197-199, 209-215, 218-246, 268, 275-277, 283-291, 293-300, 302-310, 320-323, 333, 338-341, 343-346, 348-351, 357-369, 377-379, 382-398, 403-415, 434-435, 437-438, 453-458, 472-474, 477-500, 503-510, 513-524, 527-529, 538-540, 543-567, 570-581, 584-585, 588 /usr/lib/python3/dist-packages/yaml/reader.py 122 69 43% 27-31, 34-40, 76-85, 90-92, 96, 108-109, 119, 123-135, 141-143, 149-175, 178-185 /usr/lib/python3/dist-packages/yaml/representer.py 248 176 29% 19-24, 27-31, 34-63, 78-83, 86-101, 104-129, 132, 137-142, 145, 148, 151-155, 158-162, 165, 172-189, 199, 207, 210-213, 216-217, 220-221, 224-228, 231, 275-283, 286, 289-290, 293, 313-356, 360-364 /usr/lib/python3/dist-packages/yaml/resolver.py 135 78 42% 30, 33, 51-89, 94-112, 117-118, 122-141, 146, 153, 155-159, 163 /usr/lib/python3/dist-packages/yaml/scanner.py 753 487 35% 119, 129, 133, 138, 177, 181, 185, 195, 199, 203, 207, 211, 215, 219, 227, 231, 235, 239, 243, 251, 258, 290-293, 315-321, 341, 355, 393-400, 403, 406, 411-422, 425, 428, 433-445, 448, 451, 456-468, 473-482, 487-515, 520-543, 572-593, 604-610, 615-621, 626-632, 635, 638, 643-649, 655, 687-688, 693-696, 701-704, 709, 714-719, 725, 773, 779-780, 782-783, 789-804, 808-825, 829-842, 846-855, 859-865, 869-874, 878-883, 887-897, 908-933, 937-974, 979-1049, 1054-1090, 1094-1104, 1108-1119, 1123-1132, 1142, 1151-1152, 1197-1198, 1200-1201, 1203-1223, 1230-1250, 1254-1268, 1288, 1296, 1299, 1308, 1318, 1323-1343, 1345, 1352-1370, 1375-1395, 1399-1414, 1427-1431, 1433-1434 /usr/lib/python3/dist-packages/yaml/serializer.py 85 70 18% 17-25, 28-34, 37-41, 47-58, 61-72, 75-76, 79-110 /usr/lib/python3/dist-packages/yaml/tokens.py 76 17 78% 7-12, 20-23, 78-80, 85-87, 92-94 /usr/local/lib/python3.8/dist-packages/Cython/Shadow.py 292 147 50% 21-26, 29-35, 44-74, 92, 95, 101, 103, 133-135, 142-143, 149-152, 155-158, 164-169, 172, 175, 179, 182-188, 194-198, 201, 203, 215, 230, 232, 236, 239-241, 244-246, 249-254, 257, 262, 268-278, 281-284, 290-305, 308-313, 321-324, 327-331, 334-338, 347-348, 351, 360-377, 382, 458, 461-464, 467 /usr/local/lib/python3.8/dist-packages/Cython/__init__.py 6 2 67% 11-12 /usr/local/lib/python3.8/dist-packages/IPython/__init__.py 32 12 62% 31, 90-98, 125-126, 151-152 /usr/local/lib/python3.8/dist-packages/IPython/core/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/IPython/core/alias.py 107 66 38% 71-88, 101-108, 130-134, 138-160, 163, 166-186, 199-202, 206-209, 213, 218-221, 229-230, 235-236, 240, 243-246, 249-250, 254-258 /usr/local/lib/python3.8/dist-packages/IPython/core/application.py 251 170 32% 35-39, 58-63, 91-100, 122, 125-126, 136, 145-152, 160, 174-180, 187-191, 203, 222-229, 238-243, 247-251, 260-263, 267-287, 308-350, 355-405, 409-433, 440-445, 450-462 /usr/local/lib/python3.8/dist-packages/IPython/core/async_helpers.py 68 51 25% 26-28, 31, 40-42, 46-55, 67-73, 83-92, 102-105, 108-122, 133-138, 152-173 /usr/local/lib/python3.8/dist-packages/IPython/core/autocall.py 16 5 69% 40, 48, 57, 69-70 /usr/local/lib/python3.8/dist-packages/IPython/core/builtin_trap.py 48 32 33% 26-34, 40-44, 47-51, 55-63, 67-70, 75-77, 82-86 /usr/local/lib/python3.8/dist-packages/IPython/core/compilerop.py 44 23 48% 59-63, 74-93, 101, 107, 113, 131-136, 141-150, 157-160 /usr/local/lib/python3.8/dist-packages/IPython/core/completer.py 817 691 15% 151-152, 161, 207-209, 225-230, 235-241, 268-281, 287-290, 302-322, 336-341, 344, 373-383, 386, 399, 404, 438-450, 479-504, 508, 543-544, 549, 554-557, 562-563, 617-631, 640-651, 660-679, 696-733, 738-743, 767-812, 840-843, 873-879, 885, 901-917, 926-944, 966-970, 991, 1001-1004, 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/usr/local/lib/python3.8/dist-packages/IPython/core/excolors.py 22 4 82% 164, 174-178 /usr/local/lib/python3.8/dist-packages/IPython/core/extensions.py 63 41 35% 52-56, 60, 63, 72-90, 102-110, 120-130, 133-135, 138-140, 148 /usr/local/lib/python3.8/dist-packages/IPython/core/formatters.py 361 221 39% 45, 49-53, 58, 63, 71-87, 143-193, 198, 211-214, 223-236, 261, 269-271, 276, 334-348, 352-357, 364-368, 391-395, 413-429, 456-468, 498-507, 528-548, 556-564, 640-670, 675, 679-681, 685, 692-704, 829-845, 906-919, 941-947, 958-973, 1018-1020 /usr/local/lib/python3.8/dist-packages/IPython/core/getipython.py 5 1 80% 24 /usr/local/lib/python3.8/dist-packages/IPython/core/history.py 384 277 28% 13-17, 40, 43, 46, 49, 55-58, 65-70, 86-119, 125, 129, 132, 135, 191-198, 214-229, 242, 247-268, 273, 294-303, 330-331, 340-341, 362-369, 395-411, 441-448, 467-469, 488-491, 536-551, 558-559, 564-570, 574-579, 583-584, 590-599, 628-631, 636-651, 681-685, 707-739, 751-758, 761-763, 767-769, 775-802, 816-819, 824-836, 845-847, 868-899, 904-906 /usr/local/lib/python3.8/dist-packages/IPython/core/hooks.py 59 39 34% 66-82, 86, 97-100, 109-117, 120, 124-125, 132, 142, 155, 165, 170, 176-190 /usr/local/lib/python3.8/dist-packages/IPython/core/inputtransformer2.py 359 284 21% 27-32, 40-47, 74, 77-82, 92-99, 108-117, 124-129, 154-155, 182, 185-186, 199, 207, 215-221, 226-238, 247-260, 265-278, 302-312, 320-323, 330-333, 337-338, 342-343, 347-348, 352-353, 370-380, 385-405, 422-424, 430-437, 442-463, 478-503, 507-513, 525-534, 555-571, 574-579, 584-591, 611-714, 718-721 /usr/local/lib/python3.8/dist-packages/IPython/core/interactiveshell.py 1477 1139 23% 95-97, 116-117, 123-124, 139-163, 210-222, 238-248, 252, 260-262, 272-274, 295-298, 301-304, 320, 324, 328-331, 334-335, 388, 392-403, 455-456, 466-467, 475, 487, 501-505, 553-554, 609-611, 630-703, 707, 714, 720-723, 726, 733-737, 740-743, 747-771, 775, 781-784, 790-791, 795, 799-801, 804, 810-815, 824-825, 833-836, 841, 853-856, 861-863, 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3611-3660, 3680-3699, 3702, 3707 /usr/local/lib/python3.8/dist-packages/IPython/core/latex_symbols.py 2 0 100% /usr/local/lib/python3.8/dist-packages/IPython/core/logger.py 108 92 15% 34-51, 55-57, 60, 70-127, 132-152, 156-165, 182-185, 191-201, 210-215 /usr/local/lib/python3.8/dist-packages/IPython/core/macro.py 28 19 32% 25-36, 39, 42, 46, 49-53 /usr/local/lib/python3.8/dist-packages/IPython/core/magic.py 256 154 40% 55, 64-74, 142, 203, 220-250, 324, 334-339, 343, 351, 363-375, 399-411, 442-445, 469-475, 510-541, 545-546, 552-573, 610-654, 659-661, 675-683, 687-703 /usr/local/lib/python3.8/dist-packages/IPython/core/magic_arguments.py 102 16 84% 130, 135-136, 153, 164, 172, 190, 203-204, 206, 232, 262, 269, 272-274 /usr/local/lib/python3.8/dist-packages/IPython/core/magics/__init__.py 17 0 100% /usr/local/lib/python3.8/dist-packages/IPython/core/magics/auto.py 38 27 29% 29-31, 51-60, 107-128 /usr/local/lib/python3.8/dist-packages/IPython/core/magics/basic.py 249 188 24% 22-23, 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263-291, 294 /usr/local/lib/python3.8/dist-packages/IPython/core/oinspect.py 489 415 15% 50, 86-88, 96-112, 124-132, 154-191, 196, 209-215, 227-231, 238-266, 277-285, 303-319, 338-352, 361-366, 373-376, 380, 384-386, 390-394, 401-415, 453-475, 481-490, 495-512, 531-550, 555-567, 586-656, 680-683, 688-692, 717-905, 915-922, 950-988, 997-1031 /usr/local/lib/python3.8/dist-packages/IPython/core/page.py 174 147 16% 37-43, 51, 62-78, 86-123, 152-234, 248-260, 267-280, 288-302, 311-318, 323-336, 339-343 /usr/local/lib/python3.8/dist-packages/IPython/core/payload.py 19 11 42% 39-49, 52, 55 /usr/local/lib/python3.8/dist-packages/IPython/core/prefilter.py 286 178 38% 67, 121-125, 133-135, 145, 150, 154-156, 160-161, 169-171, 181, 186, 190-192, 196-197, 205-208, 215, 219-221, 225-232, 236, 240, 252-253, 257-262, 266-269, 283-312, 325-337, 355-358, 362, 365, 383-386, 390, 393, 404-407, 415-419, 428-433, 447-451, 464-475, 487-490, 506-524, 540-543, 558-567, 570, 577-580, 590-597, 607-667, 682 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/usr/local/lib/python3.8/dist-packages/IPython/lib/clipboard.py 41 33 20% 17-33, 38-44, 53-67 /usr/local/lib/python3.8/dist-packages/IPython/lib/display.py 254 202 20% 99-115, 119-128, 133-151, 155-173, 178-194, 198-200, 204-210, 213-219, 223-231, 234-237, 240-243, 261-264, 268-276, 308-310, 314-319, 327-328, 343-344, 381-387, 390-391, 399-405, 410, 471-488, 512-544, 550-566, 575-579, 584-592, 597-605, 627-628, 631-639, 642, 645-649, 652-654 /usr/local/lib/python3.8/dist-packages/IPython/lib/pretty.py 500 393 21% 108-111, 116-117, 127-134, 140-144, 151-155, 162-166, 171-175, 186-197, 200-207, 210-214, 218-229, 237-248, 254-261, 271-276, 280-286, 290-295, 299-302, 309-321, 343-354, 358-399, 409-417, 423, 429-430, 433-435, 438-439, 445-450, 453-461, 467-469, 475-477, 480-483, 486-494, 497-500, 508-538, 547-559, 568-586, 596-608, 614-623, 628-648, 659-678, 684-690, 695-703, 708-718, 724-725, 760-761, 778-782, 803-811, 814-819, 822-827, 831-836, 844-856 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280-284, 292-303, 308-323, 331-334, 338-341, 345-348, 351-360, 367-374, 380 /usr/local/lib/python3.8/dist-packages/IPython/terminal/magics.py 89 67 25% 20-35, 41, 46-57, 60-63, 68-78, 83-84, 129-138, 171-195, 199-203 /usr/local/lib/python3.8/dist-packages/IPython/terminal/prompts.py 59 37 37% 15, 18-26, 30, 38, 41-43, 48-49, 54, 62, 67, 72, 75, 80-97, 100-107 /usr/local/lib/python3.8/dist-packages/IPython/terminal/pt_inputhooks/__init__.py 25 15 40% 23, 27, 30, 35-50 /usr/local/lib/python3.8/dist-packages/IPython/terminal/ptutils.py 86 64 26% 38-54, 58-61, 67-70, 74-77, 80-92, 99-133, 140-144, 155-168 /usr/local/lib/python3.8/dist-packages/IPython/terminal/shortcuts.py 140 111 21% 27-28, 34-95, 99-104, 109-152, 161, 170, 174-176, 180-184, 188-191, 194, 200, 203, 215-226, 238-249, 253-254, 258-274 /usr/local/lib/python3.8/dist-packages/IPython/testing/__init__.py 9 5 44% 33-37 /usr/local/lib/python3.8/dist-packages/IPython/testing/skipdoctest.py 3 0 100% /usr/local/lib/python3.8/dist-packages/IPython/utils/PyColorize.py 110 82 25% 143, 186-196, 200-205, 217-281, 286-325, 330 /usr/local/lib/python3.8/dist-packages/IPython/utils/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/IPython/utils/_process_common.py 68 57 16% 34-40, 69-111, 130-133, 151, 171-175, 190-212 /usr/local/lib/python3.8/dist-packages/IPython/utils/_process_posix.py 82 57 30% 37-39, 62-67, 94-97, 115-118, 133-203, 214-224 /usr/local/lib/python3.8/dist-packages/IPython/utils/_sysinfo.py 1 0 100% /usr/local/lib/python3.8/dist-packages/IPython/utils/capture.py 103 70 32% 18-21, 24-25, 29-35, 38, 41, 44, 47, 50, 53, 56, 59, 76-80, 83, 88-90, 95-97, 110, 114-119, 131-134, 137-163, 166-170 /usr/local/lib/python3.8/dist-packages/IPython/utils/colorable.py 7 0 100% /usr/local/lib/python3.8/dist-packages/IPython/utils/coloransi.py 67 12 82% 93-94, 122-124, 149, 156, 161, 172-173, 179-180 /usr/local/lib/python3.8/dist-packages/IPython/utils/contexts.py 26 16 38% 37-38, 42-53, 56-60, 70 /usr/local/lib/python3.8/dist-packages/IPython/utils/data.py 6 3 50% 22-23, 28 /usr/local/lib/python3.8/dist-packages/IPython/utils/decorators.py 14 10 29% 38-49 /usr/local/lib/python3.8/dist-packages/IPython/utils/dir2.py 34 28 18% 16-20, 38-51, 64-84 /usr/local/lib/python3.8/dist-packages/IPython/utils/encoding.py 23 7 70% 30, 53-58, 64-68 /usr/local/lib/python3.8/dist-packages/IPython/utils/frame.py 17 11 35% 50-53, 66-67, 81-82, 91-94 /usr/local/lib/python3.8/dist-packages/IPython/utils/generics.py 9 2 78% 12, 30 /usr/local/lib/python3.8/dist-packages/IPython/utils/importstring.py 12 10 17% 27-39 /usr/local/lib/python3.8/dist-packages/IPython/utils/io.py 130 76 42% 28-31, 41-42, 47-49, 52-64, 68-73, 84, 122-132, 136-139, 143-145, 149-150, 153-154, 170-188, 207-211, 216-218, 223-227, 232-236, 246-248 /usr/local/lib/python3.8/dist-packages/IPython/utils/ipstruct.py 76 56 26% 85-88, 111-123, 146-151, 165-166, 180-182, 196-198, 212-215, 223-229, 232, 245, 263, 271, 360-390 /usr/local/lib/python3.8/dist-packages/IPython/utils/module_paths.py 11 8 27% 61-70 /usr/local/lib/python3.8/dist-packages/IPython/utils/openpy.py 45 35 22% 24-40, 46-58, 75-79, 100-103 /usr/local/lib/python3.8/dist-packages/IPython/utils/path.py 191 148 23% 27, 30-53, 57, 67, 76-81, 87-90, 99-109, 146-162, 190-211, 220-230, 239-249, 254-256, 260-262, 266-268, 272-274, 278-280, 297-302, 307-311, 321-327, 341-351, 362-363, 375-382, 395-419, 429-436 /usr/local/lib/python3.8/dist-packages/IPython/utils/process.py 29 17 41% 15, 17, 47-50, 55-68 /usr/local/lib/python3.8/dist-packages/IPython/utils/py3compat.py 108 72 33% 18-19, 22-23, 27-29, 32-34, 38-40, 45-59, 66-76, 93-140, 147, 156-158, 165-168, 179, 189 /usr/local/lib/python3.8/dist-packages/IPython/utils/sentinel.py 8 1 88% 16 /usr/local/lib/python3.8/dist-packages/IPython/utils/strdispatch.py 33 23 30% 25-26, 31-33, 38-40, 44-52, 55, 58-61, 65-68 /usr/local/lib/python3.8/dist-packages/IPython/utils/sysinfo.py 40 24 40% 54-65, 81-82, 97-99, 119, 123, 128-129, 134, 152-165 /usr/local/lib/python3.8/dist-packages/IPython/utils/syspathcontext.py 32 22 31% 24, 27-31, 34-40, 46, 49-53, 56-62 /usr/local/lib/python3.8/dist-packages/IPython/utils/tempdir.py 23 12 48% 24-26, 29-30, 35, 38, 51-53, 56-57 /usr/local/lib/python3.8/dist-packages/IPython/utils/terminal.py 59 37 37% 27-33, 53, 58, 62, 68-69, 73, 81-105, 110-112, 117-119, 123-125, 129 /usr/local/lib/python3.8/dist-packages/IPython/utils/text.py 255 192 25% 22, 43-47, 52-56, 61, 66-70, 101, 106-110, 115-119, 124-128, 148-165, 186-201, 215-230, 274-285, 306-309, 329-334, 342-346, 354-356, 397-409, 417-425, 460-473, 484, 509-510, 542-569, 593-610, 618-624, 629-635, 644-647, 702-707, 732-739, 763-770 /usr/local/lib/python3.8/dist-packages/IPython/utils/timing.py 35 24 31% 33, 42, 51-52, 58-67, 83-96, 106, 115 /usr/local/lib/python3.8/dist-packages/IPython/utils/wildcard.py 51 31 39% 44-52, 56, 61-73, 78-85, 92-111 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40, 44, 51-106 /usr/local/lib/python3.8/dist-packages/boto/__init__.py 281 191 32% 75, 88-97, 102-111, 125-126, 140-141, 155-156, 170-171, 185-186, 206-207, 223-224, 239-240, 254-255, 270-271, 286-287, 302-303, 317-318, 332-333, 351-352, 366-367, 381-382, 397-398, 414-415, 437-453, 470-471, 494-508, 530-545, 562-563, 577-578, 599-607, 626-627, 643-644, 660-661, 683-684, 702-703, 720-721, 737-738, 747-748, 767-768, 788-789, 811-812, 834-835, 856-857, 878-879, 901-902, 924-925, 947-948, 970-971, 993-994, 1016-1017, 1039-1040, 1062-1063, 1078-1079, 1094-1095, 1143-1197, 1209-1214 /usr/local/lib/python3.8/dist-packages/boto/auth.py 584 467 20% 49-51, 102-105, 108-115, 118-121, 124-128, 132-134, 137-140, 143-144, 155, 158, 167-169, 172-173, 176-193, 203-205, 208-209, 212-221, 232-233, 236-247, 258-259, 266-271, 280-282, 290-298, 309-322, 334-340, 343-350, 357-367, 370-374, 377-383, 388-395, 404-414, 417-419, 422-430, 433-441, 444-451, 454-459, 462, 465-479, 482-487, 490-504, 512-516, 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/usr/local/lib/python3.8/dist-packages/boto/endpoints.py 79 57 28% 44-50, 55-56, 61-78, 81-82, 87-92, 100-103, 118-121, 126, 130, 149, 163-166, 177, 186, 197, 210-222, 227-232, 237-239 /usr/local/lib/python3.8/dist-packages/boto/exception.py 287 166 42% 42-43, 46, 49, 79-135, 138-142, 145-148, 151, 155, 159, 162-170, 173-176, 181-185, 188, 191-196, 204-205, 208-211, 254-256, 259, 262-267, 270-272, 280-281, 284, 287, 295-296, 299, 303-306, 310-312, 334-340, 343-347, 350-353, 356-359, 376-383, 403-405, 408, 411-416, 458-459, 466-467, 474-475, 482-483, 490-491, 532-534, 537, 549-551, 554, 565-566, 574-575, 578, 592-593 /usr/local/lib/python3.8/dist-packages/boto/gs/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/boto/gs/acl.py 187 133 29% 58-59, 63, 67-75, 80-82, 87-88, 91-93, 96-97, 100-107, 110-115, 118-126, 132-135, 138-141, 144-149, 152-155, 158-164, 172-175, 178, 181-205, 208-216, 219-223, 243-250, 254-264, 267-271, 274-284, 287-308 /usr/local/lib/python3.8/dist-packages/boto/gs/user.py 26 20 23% 25-29, 32, 35, 38-43, 46-54 /usr/local/lib/python3.8/dist-packages/boto/handler.py 29 19 34% 30-32, 35-38, 41-46, 49, 54-57, 60 /usr/local/lib/python3.8/dist-packages/boto/https_connection.py 49 34 31% 41-44, 47, 59-62, 75-83, 105-114, 118-135 /usr/local/lib/python3.8/dist-packages/boto/jsonresponse.py 108 89 18% 30-32, 35-41, 44-47, 50, 53-55, 64-74, 77-86, 89-91, 94-109, 112-119, 127-132, 135-137, 140-155, 158-168 /usr/local/lib/python3.8/dist-packages/boto/plugin.py 38 22 42% 53-56, 60-66, 70-78, 86, 91-93 /usr/local/lib/python3.8/dist-packages/boto/provider.py 247 178 28% 183-214, 217-219, 222, 227-229, 232, 237-239, 242, 247-263, 267-378, 383-402, 413-434, 437-441, 444-465, 468-473, 476, 479, 484 /usr/local/lib/python3.8/dist-packages/boto/pyami/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/boto/pyami/config.py 158 108 32% 42, 47-49, 59, 61, 65-69, 78, 88-93, 96-103, 111-121, 124, 127, 130-134, 137-141, 144-148, 151, 166-169, 172-180, 183-186, 189-191, 194-202, 205-217, 220-235 /usr/local/lib/python3.8/dist-packages/boto/regioninfo.py 89 66 26% 44, 56-57, 77-82, 100-115, 121-134, 161-182, 208-220, 226-229, 235-239, 247-249, 259-262, 265, 268, 271-276, 289-290 /usr/local/lib/python3.8/dist-packages/boto/resultset.py 111 98 12% 47-62, 65-76, 79-82, 85-134, 140-142, 145-148, 151, 154, 157-160, 163-176 /usr/local/lib/python3.8/dist-packages/boto/s3/__init__.py 17 11 35% 43-44, 54-55, 63-74 /usr/local/lib/python3.8/dist-packages/boto/s3/acl.py 111 89 20% 34-36, 39-51, 54-64, 67-72, 75-82, 88-89, 92, 95-97, 100-101, 104-108, 111-114, 117-121, 130-135, 138-140, 143-156, 159-171 /usr/local/lib/python3.8/dist-packages/boto/s3/bucket.py 700 576 18% 71, 95-97, 100, 103, 106, 109, 112-117, 131, 143, 175-194, 197-231, 282, 328, 363, 369-390, 394-411, 424-426, 469-472, 521-522, 535, 606-609, 623-625, 630, 662-730, 757-759, 766-788, 847-889, 894-908, 912-922, 926-936, 940-944, 948-963, 989-1002, 1028-1040, 1043-1046, 1072-1080, 1110-1119, 1123-1124, 1134-1146, 1162-1171, 1193-1197, 1206-1207, 1216-1227, 1235-1240, 1243-1249, 1253-1260, 1288-1308, 1323-1339, 1350-1366, 1377-1389, 1396-1404, 1438-1441, 1448, 1454-1461, 1483, 1489-1493, 1522-1526, 1530-1538, 1544-1551, 1560-1563, 1570-1576, 1586-1594, 1598-1606, 1618-1632, 1644, 1651-1658, 1669-1673, 1679-1687, 1736-1767, 1775-1806, 1815-1822, 1826, 1829-1835, 1838-1845, 1849-1864, 1867, 1870-1878 /usr/local/lib/python3.8/dist-packages/boto/s3/bucketlistresultset.py 67 54 19% 29-41, 54-59, 62, 73-86, 99-105, 108, 121-134, 147-151, 154 /usr/local/lib/python3.8/dist-packages/boto/s3/bucketlogging.py 50 41 18% 28-33, 36-47, 50, 53-57, 60-65, 69-83 /usr/local/lib/python3.8/dist-packages/boto/s3/connection.py 282 212 25% 58-62, 67-69, 76, 79-82, 85-88, 91-95, 98-99, 106, 113, 119, 122-126, 132-135, 176-199, 205-208, 211-212, 215, 226, 232-237, 298-355, 361-380, 386-438, 443-453, 468-469, 508-511, 528-555, 577-581, 606-627, 644-647, 653-667 /usr/local/lib/python3.8/dist-packages/boto/s3/cors.py 80 69 14% 65-78, 81, 84, 87-100, 103-117, 126-130, 133, 140-144, 194-210 /usr/local/lib/python3.8/dist-packages/boto/s3/deletemarker.py 28 23 18% 26-31, 34-38, 41-55 /usr/local/lib/python3.8/dist-packages/boto/s3/key.py 690 590 14% 106-135, 138-147, 150, 154-157, 160, 163, 168-169, 172-175, 180-184, 187-192, 197-207, 210, 219-223, 226-231, 234-242, 246-259, 262-273, 280, 304-334, 348, 352-361, 381-385, 397-402, 408-415, 441-451, 501-507, 515-519, 522-542, 551, 557, 561, 566-573, 576, 580-581, 584-585, 588-589, 592-593, 596, 605-610, 624-635, 639, 695-713, 760, 767-966, 969-1021, 1036-1045, 1108-1132, 1214-1311, 1374-1375, 1437-1444, 1493, 1503-1575, 1602, 1658-1664, 1722-1739, 1795-1804, 1829-1831, 1853-1856, 1859-1867, 1875-1889, 1893-1912, 1929-1935 /usr/local/lib/python3.8/dist-packages/boto/s3/keyfile.py 74 53 28% 35-44, 47-49, 52-85, 88-89, 92-94, 97, 102, 107, 110, 113, 116, 119, 122, 125, 128, 131, 134 /usr/local/lib/python3.8/dist-packages/boto/s3/lifecycle.py 148 113 24% 48-65, 68, 71-76, 79-86, 89-99, 111-112, 115, 118-121, 124-128, 131-137, 152-154, 157-161, 164-171, 178-182, 185, 188-203, 210-213, 230-231, 234-236, 242, 246, 250, 259-263, 266, 273-278, 310-311 /usr/local/lib/python3.8/dist-packages/boto/s3/multidelete.py 64 48 25% 41-44, 47-50, 53, 56-66, 82-85, 88-92, 95, 98-107, 121-123, 126-134, 137 /usr/local/lib/python3.8/dist-packages/boto/s3/multipart.py 160 133 17% 46-52, 55, 59, 62-71, 86-90, 93-96, 99, 102-111, 118-125, 134-146, 149, 152, 155-162, 165-175, 178-200, 211-226, 253-261, 290-301, 317-318, 330 /usr/local/lib/python3.8/dist-packages/boto/s3/prefix.py 16 10 38% 24-25, 28, 31-34, 38-41 /usr/local/lib/python3.8/dist-packages/boto/s3/tagging.py 52 34 35% 7-8, 11, 14-17, 20, 24, 29-33, 36, 39-40, 43-47, 54-58, 61, 64-68, 71 /usr/local/lib/python3.8/dist-packages/boto/s3/user.py 23 18 22% 24-28, 31, 34-39, 42-49 /usr/local/lib/python3.8/dist-packages/boto/s3/website.py 122 85 30% 24-26, 57-63, 66-72, 75, 78-89, 94-98, 101, 104-106, 109-114, 131-133, 136, 152-153, 156-159, 162, 165, 168-171, 191-192, 195-198, 201, 204-209, 213, 218-223, 245-247, 250, 283-288, 291 /usr/local/lib/python3.8/dist-packages/boto/storage_uri.py 488 377 23% 57, 62, 66, 69-70, 77-78, 82-83, 87-89, 103-149, 152, 158-160, 165-172, 176-177, 180-184, 187-191, 194-196, 199-203, 209-218, 224-227, 231-234, 237-240, 288-299, 302-318, 321, 328-332, 335-344, 348-355, 365-366, 379-390, 402-413, 417-421, 425-429, 433-438, 441-443, 446-453, 457-464, 468-470, 475-491, 496-504, 508-515, 518-520, 524, 528, 536, 540, 544, 548, 552, 556, 560, 564, 568-576, 579-581, 584-585, 588-591, 596-605, 610-619, 624-625, 630-631, 636-640, 646-649, 653-655, 661-675, 680-696, 700-706, 713-724, 733-735, 738-740, 743-745, 749-754, 757-759, 762-764, 767-769, 773, 779-787, 791-795, 800-802, 805-811, 816-822, 826-833, 838-840, 845-849, 875-880, 889, 893, 897, 901, 905, 909-911, 915, 919, 923, 927, 932, 937, 944 /usr/local/lib/python3.8/dist-packages/boto/utils.py 575 467 19% 108-111, 119-169, 173-183, 187-202, 212-237, 241, 246-266, 269-270, 273-337, 340-343, 346-347, 350-351, 354-355, 358-359, 383, 399-405, 413-427, 432-441, 454-460, 464-466, 470-481, 485-498, 505-508, 518-543, 549-554, 557-576, 579, 582, 588, 616-619, 629-646, 689-691, 694, 697-700, 703, 706-709, 712, 715-717, 720-728, 731, 734-741, 744-750, 753-765, 780-782, 785-787, 790, 793-797, 800-803, 808-859, 863-872, 876-881, 897-899, 920-944, 959-972, 1000, 1004-1029, 1038, 1048-1049, 1060, 1070-1083, 1093-1098 /usr/local/lib/python3.8/dist-packages/boto/vendored/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/boto/vendored/regions/__init__.py 3 0 100% /usr/local/lib/python3.8/dist-packages/boto/vendored/regions/exceptions.py 3 0 100% /usr/local/lib/python3.8/dist-packages/boto/vendored/regions/regions.py 81 60 26% 58, 65, 85, 94-96, 99-102, 106-116, 120-124, 128-152, 156-160, 163-177, 180-182, 186 /usr/local/lib/python3.8/dist-packages/boto/vendored/six.py 444 208 53% 49-72, 98-99, 112, 120-121, 131-133, 145, 154-157, 192-193, 222-223, 304, 480, 488, 493-499, 511-517, 522-524, 530-532, 537, 542, 546-560, 575, 578, 581, 584, 592-608, 620, 623, 636-637, 642-661, 667, 671, 675, 682-701, 707, 717-718, 723-775, 777-784, 789-795, 805-809, 814-825, 836-843, 864-865 /usr/local/lib/python3.8/dist-packages/cachetools/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/cachetools/abc.py 25 14 44% 21-24, 29-36, 39-43 /usr/local/lib/python3.8/dist-packages/cachetools/cache.py 60 38 37% 6, 9, 12, 21-27, 30, 38-41, 44-57, 60-62, 65, 68, 71, 74, 79, 84, 89 /usr/local/lib/python3.8/dist-packages/cachetools/decorators.py 73 69 5% 11-44, 52-88 /usr/local/lib/python3.8/dist-packages/cachetools/keys.py 24 14 42% 17-20, 23, 26, 29, 40-43, 49-52 /usr/local/lib/python3.8/dist-packages/cachetools/lfu.py 22 14 36% 10-11, 14-16, 19-20, 23-24, 28-33 /usr/local/lib/python3.8/dist-packages/cachetools/lru.py 27 18 33% 10-11, 14-16, 19-20, 23-24, 28-33, 36-39 /usr/local/lib/python3.8/dist-packages/cachetools/rr.py 19 11 42% 8, 15-20, 25, 29-34 /usr/local/lib/python3.8/dist-packages/cachetools/ttl.py 156 118 24% 12-13, 16, 19-22, 28-29, 32-35, 38-43, 46, 49, 52, 59-64, 67-72, 75-84, 87-99, 102-106, 109-116, 119-126, 129-136, 139-141, 145-147, 152, 157, 161-172, 175-177, 180-181, 184-185, 188-189, 196-203, 206-208 /usr/local/lib/python3.8/dist-packages/cycler.py 177 107 40% 73, 110, 118, 122, 127, 131, 157-178, 185-189, 218-223, 229, 240-243, 255-262, 265, 268-273, 284-292, 303-311, 317-322, 325-333, 337-347, 396-397, 425, 454-465, 509, 513-516, 519-526, 548-556 /usr/local/lib/python3.8/dist-packages/cython.py 10 6 40% 9-17 /usr/local/lib/python3.8/dist-packages/decorator.py 270 120 56% 49-60, 64-67, 70-73, 100, 114-115, 117, 119-120, 133, 139, 143, 155-156, 168, 174, 186-189, 217, 233-235, 241, 246, 271, 279, 282-283, 291, 299-300, 306, 314-316, 318, 321, 329, 339-348, 357-454 /usr/local/lib/python3.8/dist-packages/defusedxml/ElementTree.py 64 25 61% 21-23, 52, 79-105, 108, 113, 120 /usr/local/lib/python3.8/dist-packages/defusedxml/__init__.py 21 15 29% 25-51 /usr/local/lib/python3.8/dist-packages/defusedxml/common.py 65 42 35% 23, 31-34, 37-38, 46-52, 55-56, 64-68, 71-72, 81-90, 98-105, 115-122, 125-132 /usr/local/lib/python3.8/dist-packages/gast/__init__.py 2 0 100% /usr/local/lib/python3.8/dist-packages/gast/ast3.py 192 145 24% 10-160, 174, 189-194, 200-207, 214-232, 239, 260-264, 270-306, 310-376, 391 /usr/local/lib/python3.8/dist-packages/gast/astn.py 24 1 96% 21 /usr/local/lib/python3.8/dist-packages/gast/gast.py 78 46 41% 9-11, 292, 302-304, 308-316, 327-331, 342-366, 375-380 /usr/local/lib/python3.8/dist-packages/h5py/__init__.py 57 23 60% 27-32, 37, 89-90, 97-113 /usr/local/lib/python3.8/dist-packages/h5py/_hl/__init__.py 2 0 100% /usr/local/lib/python3.8/dist-packages/h5py/_hl/attrs.py 133 92 31% 63, 76-78, 90, 100, 105, 122-221, 232-247, 253, 257-275, 284-286 /usr/local/lib/python3.8/dist-packages/h5py/_hl/base.py 216 108 50% 23-24, 40-45, 53-63, 88, 112, 126-128, 131, 134, 139-141, 144, 155-162, 185, 188-193, 197-199, 204-207, 219-221, 227, 237-239, 251, 265, 281, 285-287, 291, 294-295, 308, 312, 326, 340-344, 347-349, 359-363, 366-368, 381-404, 409, 413, 417, 421, 447, 450-452, 455 /usr/local/lib/python3.8/dist-packages/h5py/_hl/compat.py 70 44 37% 12-41, 51, 56-57, 67-72, 80-85, 94-95, 99-100, 113-115, 127-134 /usr/local/lib/python3.8/dist-packages/h5py/_hl/dataset.py 474 340 28% 47-54, 68-172, 183-205, 216-217, 221, 225, 229-244, 260, 263-267, 272-274, 280, 291, 297-299, 311-313, 319-322, 328-331, 337, 343, 349, 358-361, 369-376, 383-385, 391-393, 400, 423-438, 447-450, 458-462, 470-474, 488-582, 592-708, 720, 724, 730, 743-758, 770, 777-790, 800, 811, 817, 821-824, 841 /usr/local/lib/python3.8/dist-packages/h5py/_hl/datatype.py 24 11 54% 37, 43-45, 49-56 /usr/local/lib/python3.8/dist-packages/h5py/_hl/files.py 238 113 53% 46-48, 52, 78, 89, 95, 103-107, 115, 117, 119, 125-127, 130-137, 143-146, 158-167, 172, 174-206, 210-215, 239, 245-253, 259, 266-268, 274-275, 281-282, 287-298, 304, 310-314, 379, 382-383, 386-393, 400-402, 411, 418, 438-439, 451-452, 465-478 /usr/local/lib/python3.8/dist-packages/h5py/_hl/filters.py 175 141 19% 78-84, 88-101, 113-244, 263-283, 302-342 /usr/local/lib/python3.8/dist-packages/h5py/_hl/group.py 234 168 28% 41, 62-69, 132-140, 158-174, 189-206, 223-238, 247-253, 260-262, 271-274, 301-342, 368-393, 399, 404, 409-410, 415, 455-494, 504-507, 530-534, 560-565, 569-579, 603, 606, 609, 622, 627, 630-631, 634 /usr/local/lib/python3.8/dist-packages/h5py/_hl/selections.py 295 221 25% 58-95, 111, 117-118, 150-151, 171, 176, 180-182, 185, 197-207, 211-218, 222, 226, 230, 252-269, 279-283, 293, 299, 304, 315-320, 337, 340-341, 345-414, 417-419, 424-442, 453-475, 482-488, 495-508, 519-598 /usr/local/lib/python3.8/dist-packages/h5py/_hl/selections2.py 43 33 23% 26-45, 57-74, 83-91, 94-95, 102-105 /usr/local/lib/python3.8/dist-packages/h5py/_hl/vds.py 52 33 37% 56-90, 94, 97-99, 120-123, 126-127 /usr/local/lib/python3.8/dist-packages/h5py/h5py_warnings.py 19 6 68% 16-17, 34-36, 39 /usr/local/lib/python3.8/dist-packages/h5py/version.py 21 3 86% 32, 34, 36 /usr/local/lib/python3.8/dist-packages/imagecodecs/__init__.py 5 0 100% /usr/local/lib/python3.8/dist-packages/imagecodecs/imagecodecs.py 300 226 25% 330, 350-351, 356, 371, 375-383, 387, 390, 395, 401-402, 408-479, 484, 489-510, 515-603, 608-641, 646-666, 675, 684, 689, 698, 703-706, 711-722, 727-734, 745-788, 796-802, 814 /usr/local/lib/python3.8/dist-packages/imageio/__init__.py 13 0 100% /usr/local/lib/python3.8/dist-packages/imageio/core/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/imageio/core/fetching.py 105 88 16% 62-114, 150-184, 210-225, 230-232, 237-247 /usr/local/lib/python3.8/dist-packages/imageio/core/findlib.py 74 65 12% 23-29, 37-81, 99-160 /usr/local/lib/python3.8/dist-packages/imageio/core/format.py 276 178 36% 94, 103, 108, 111, 115, 118, 126, 142, 149, 155, 164-170, 179-185, 192, 199, 216-221, 228, 235, 238-239, 242-244, 247-248, 256-261, 267, 272-275, 289, 300, 331, 343-349, 359, 367-370, 386-392, 401-414, 419, 422-425, 437, 447, 458, 484-502, 517-521, 527, 531, 551, 557, 560-565, 569-609, 633, 635, 655, 657, 659-665, 678-697, 705-725, 735 /usr/local/lib/python3.8/dist-packages/imageio/core/functions.py 157 124 21% 100-121, 139-142, 172-186, 213-231, 259-267, 291-308, 354-374, 397-427, 453-455, 479-496, 542-561, 586-615 /usr/local/lib/python3.8/dist-packages/imageio/core/request.py 319 274 14% 19-20, 89-128, 133-262, 271, 279, 289, 295, 310-350, 359-372, 381-421, 427-428, 435-437, 440-467, 476-482, 492-496, 501-530, 533, 539-561, 564-565, 568, 571 /usr/local/lib/python3.8/dist-packages/imageio/core/util.py 263 210 20% 30-34, 38-42, 55-108, 122-134, 139-143, 149, 155-158, 164-169, 180-185, 205-211, 214-225, 228-230, 252-257, 265-273, 281, 290-309, 316, 324-328, 335-339, 346-350, 355, 358, 361, 364, 376-383, 387-395, 398-400, 404-408, 423-466, 479-491, 506-520, 531-542, 548-555 /usr/local/lib/python3.8/dist-packages/imageio/plugins/__init__.py 22 0 100% /usr/local/lib/python3.8/dist-packages/imageio/plugins/_freeimage.py 603 405 33% 63-67, 74-87, 422, 429-432, 439-447, 450-454, 461-480, 485-514, 518-521, 526-527, 530-531, 537, 544-549, 555-557, 564, 573-603, 609, 615, 620-625, 628, 631-640, 645-652, 660-723, 728-797, 807-839, 842-856, 876-895, 941-975, 980-1031, 1041-1083, 1089-1110, 1113-1163, 1170-1187, 1220-1245, 1271-1295, 1298-1299, 1305-1321, 1326-1328 /usr/local/lib/python3.8/dist-packages/imageio/plugins/bsdf.py 140 113 19% 14-52, 62-63, 66-73, 76, 126-130, 133-135, 143-180, 185, 188-194, 198-231, 240-249, 256-257, 261-289 /usr/local/lib/python3.8/dist-packages/imageio/plugins/dicom.py 147 122 17% 31-33, 41-56, 89-100, 105, 111-155, 159-161, 165-168, 171-199, 202-231, 239-266 /usr/local/lib/python3.8/dist-packages/imageio/plugins/example.py 43 23 47% 54-56, 67-69, 82-84, 89, 93, 97-106, 111, 124, 129, 133, 138 /usr/local/lib/python3.8/dist-packages/imageio/plugins/feisem.py 41 32 22% 27, 38-41, 55-84 /usr/local/lib/python3.8/dist-packages/imageio/plugins/ffmpeg.py 304 258 15% 27, 30-31, 57-66, 178-189, 192-194, 204-239, 257-327, 339-344, 357-358, 361, 370-386, 389, 394-468, 472-474, 478-502, 523-527, 530-532, 537-572, 575, 582-617, 629-636, 639-641, 646-649, 653-661, 667-698 /usr/local/lib/python3.8/dist-packages/imageio/plugins/fits.py 40 24 40% 15-23, 80, 84, 90-102, 105, 108, 112-116, 120 /usr/local/lib/python3.8/dist-packages/imageio/plugins/freeimage.py 177 122 31% 48, 52-59, 63-70, 76, 79-80, 83, 86-88, 91-93, 99-102, 106-109, 113-132, 135, 168-174, 177-178, 215-219, 225-240, 243-259, 303-309, 312-314, 323-340, 349-362, 365-368, 393-397, 485-510 /usr/local/lib/python3.8/dist-packages/imageio/plugins/freeimagemulti.py 144 104 28% 27-32, 35, 38, 41-45, 48-55, 62-67, 71, 75-86, 90-94, 97, 137-140, 197-200, 203-205, 225-254, 263-299, 308-322 /usr/local/lib/python3.8/dist-packages/imageio/plugins/gdal.py 35 19 46% 15-23, 40-43, 46, 52-54, 57, 60, 63-65, 68 /usr/local/lib/python3.8/dist-packages/imageio/plugins/grab.py 63 37 41% 25, 28-40, 44, 47, 50, 66-70, 73-79, 95-99, 102-111 /usr/local/lib/python3.8/dist-packages/imageio/plugins/lytro.py 304 225 26% 63, 69, 74, 78, 83, 101-103, 109-136, 142-143, 148, 152, 157-171, 177-195, 212-214, 220-280, 285, 289, 295-302, 308-312, 319-325, 348-371, 375-383, 388-391, 410-412, 418-435, 441-442, 447, 451, 456-470, 476-494, 511-513, 519-559, 564, 568, 574-582, 588-592, 599-607, 630-653, 657-665, 670-673 /usr/local/lib/python3.8/dist-packages/imageio/plugins/npz.py 37 17 54% 40, 44, 51-55, 58, 61, 65-69, 73, 81, 85, 88, 91 /usr/local/lib/python3.8/dist-packages/imageio/plugins/pillow.py 365 285 22% 76, 79-99, 102-108, 111-115, 119-146, 149-150, 153-155, 159, 162-165, 168-181, 184-186, 190-197, 200, 203-218, 221, 298, 301-315, 323-357, 360-364, 429, 433-440, 443-455, 461-478, 486-496, 499-503, 564, 568-575, 578-590, 596-613, 621-639, 642-648, 653-655, 667-680, 684-695, 705-792, 797-835 /usr/local/lib/python3.8/dist-packages/imageio/plugins/pillow_info.py 5 1 80% 100 /usr/local/lib/python3.8/dist-packages/imageio/plugins/pillowmulti.py 164 134 18% 60, 74-101, 106, 109-118, 138-151, 156-177, 181-186, 189, 193-223, 228-232, 245-262, 268-279, 297-305, 317-337, 347-364 /usr/local/lib/python3.8/dist-packages/imageio/plugins/simpleitk.py 62 38 39% 15-37, 95-98, 101-104, 110-112, 115, 118, 122-127, 130-131, 136-137, 140, 143-144, 147-148 /usr/local/lib/python3.8/dist-packages/imageio/plugins/spe.py 126 96 24% 255, 260, 264-295, 298-303, 307, 310-370, 373-399, 402-405, 408-411, 414-438, 456-465 /usr/local/lib/python3.8/dist-packages/imageio/plugins/swf.py 179 147 18% 25-27, 68-71, 74-76, 82-138, 141, 144, 147-150, 154-179, 188-215, 218, 224-239, 242-267, 270-288, 292-298, 302-320, 323 /usr/local/lib/python3.8/dist-packages/imageio/plugins/tifffile.py 91 65 29% 19-23, 208, 212, 218-229, 232-234, 237-240, 243-256, 259-276, 281-297, 300, 303-311, 314-322 /usr/local/lib/python3.8/dist-packages/ipykernel/__init__.py 2 0 100% /usr/local/lib/python3.8/dist-packages/ipykernel/_version.py 11 5 55% 7-11, 13 /usr/local/lib/python3.8/dist-packages/ipykernel/comm/__init__.py 2 0 100% /usr/local/lib/python3.8/dist-packages/ipykernel/comm/comm.py 86 52 40% 21-22, 28, 40, 51-59, 63-66, 76, 82-99, 103-118, 122, 135, 144, 150-152, 156-163 /usr/local/lib/python3.8/dist-packages/ipykernel/comm/manager.py 72 52 28% 37-40, 44, 48-51, 56, 66-72, 77-99, 104-113, 117-129 /usr/local/lib/python3.8/dist-packages/ipykernel/connect.py 58 41 29% 31-37, 58-81, 91-103, 128-137, 163-178 /usr/local/lib/python3.8/dist-packages/ipykernel/jsonutil.py 81 59 27% 73-106, 133-197 /usr/local/lib/python3.8/dist-packages/ipykernel/kernelbase.py 441 316 28% 20-22, 61-63, 80, 163-171, 176-209, 216-223, 228-282, 287, 291, 295-331, 343-349, 358-365, 377-383, 393, 397-408, 412-441, 450, 459, 466, 482-483, 495, 505, 514, 520-569, 575, 579-585, 591, 599-611, 616, 620-627, 633, 636-643, 647, 657-661, 664-679, 683-693, 699, 703-710, 715, 723-742, 747, 755-767, 771-773, 778, 786-788, 794-798, 805-807, 811-817, 825, 835-843, 856-860, 868-904, 909-912 /usr/local/lib/python3.8/dist-packages/ipython_genutils/__init__.py 1 0 100% /usr/local/lib/python3.8/dist-packages/ipython_genutils/_version.py 2 0 100% /usr/local/lib/python3.8/dist-packages/ipython_genutils/encoding.py 23 7 70% 30, 53-58, 64-68 /usr/local/lib/python3.8/dist-packages/ipython_genutils/importstring.py 12 10 17% 27-39 /usr/local/lib/python3.8/dist-packages/ipython_genutils/path.py 70 55 21% 55-71, 90-95, 100-101, 110-117, 130-154, 165-172 /usr/local/lib/python3.8/dist-packages/ipython_genutils/py3compat.py 196 141 28% 16-17, 20-21, 25-27, 30-32, 36-40, 45-57, 64-79, 96-143, 158-167, 175, 183-185, 195-198, 203-204, 212, 220, 224-293, 298-307 /usr/local/lib/python3.8/dist-packages/ipython_genutils/text.py 68 51 25% 19, 49-60, 74-87, 101-113, 125, 134-135, 140-146, 155-158, 215-217, 238-243 /usr/local/lib/python3.8/dist-packages/ipywidgets/__init__.py 21 7 67% 31-33, 38-40, 50 /usr/local/lib/python3.8/dist-packages/ipywidgets/_version.py 8 0 100% /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/__init__.py 24 0 100% /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/docutils.py 6 0 100% /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/domwidget.py 27 14 48% 26-28, 36-38, 41-50 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/interaction.py 289 226 22% 11-12, 17-18, 33-34, 51-62, 73-85, 90-93, 99-128, 132-152, 177-232, 245-268, 272, 278-290, 295-307, 312-343, 348-359, 364-380, 388-393, 444, 507-538, 555-556, 570, 576 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/trait_types.py 78 33 58% 45-52, 84-87, 100-103, 125-128, 137-140, 162-165, 168, 195-206, 220 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/util.py 8 0 100% /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/valuewidget.py 12 5 58% 20, 24-27 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget.py 403 283 30% 13-15, 32-39, 42-49, 59, 65-71, 80-116, 129-131, 141-162, 173-174, 183-195, 208-211, 216-223, 243-256, 259-265, 281-283, 302-303, 312, 317-318, 323-339, 349-354, 357-369, 372, 398, 411-415, 419, 427-438, 443-448, 455, 467-471, 481-489, 506-523, 526, 529-533, 540-545, 557, 571, 586, 590-594, 600-606, 609, 624-628, 633-642, 646-662, 668-689, 693, 697, 702, 707, 712-732, 736-737, 740-755, 758-763 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_bool.py 31 3 90% 22-24 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_box.py 37 5 86% 63-65, 68-69 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_button.py 41 12 71% 61-63, 68-73, 86, 94, 104-105 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_color.py 14 0 100% /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_controller.py 29 0 100% /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_core.py 9 0 100% /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_date.py 13 0 100% /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_description.py 23 6 74% 28-34 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_float.py 168 62 63% 24-26, 36-39, 44-49, 54-59, 70-73, 78-83, 88-93, 262, 266, 270, 274, 278-281, 290-294, 298-308, 312-315 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_int.py 185 67 64% 42-44, 53-61, 73-75, 85-93, 98-101, 106-111, 116-121, 202, 206, 210, 214, 218-221, 243-247, 251-261, 265-268 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_layout.py 61 7 89% 82-85, 93-96 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_link.py 36 15 58% 24-34, 50-52, 56, 75, 105 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_media.py 102 46 55% 44-51, 71-75, 86-88, 92-96, 101-111, 116-133, 159, 163, 166, 194, 197, 223, 226 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_output.py 64 33 48% 76-77, 97-105, 109-113, 117-127, 131-132, 136, 142, 146, 157-159 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_selection.py 295 148 50% 11-12, 119-132, 136-139, 175-191, 196-200, 205-218, 222-225, 230-235, 239-243, 247-254, 258-260, 264-271, 274-280, 316-327, 331-335, 340-344, 349-352, 357-363, 368-371, 375-377, 381-383, 387-389, 392-395, 529-531, 535-540, 544-547, 553-555, 559-565, 615-619, 624-629 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_selectioncontainer.py 36 14 61% 27-30, 44-46, 57-61, 65-68 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_string.py 68 15 78% 30-32, 79-81, 91-92, 106-108, 120-123 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_style.py 9 0 100% /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_templates.py 198 138 30% 80-85, 89-91, 95-96, 100-106, 157-158, 162-167, 172, 176-242, 247, 281-289, 293-295, 300-312, 315-330, 333-345, 349-355, 397-398, 403-450, 454 /usr/local/lib/python3.8/dist-packages/ipywidgets/widgets/widget_upload.py 39 11 72% 24-26, 58-64, 68 /usr/local/lib/python3.8/dist-packages/jedi/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/jedi/_compatibility.py 339 252 26% 18-19, 34-45, 52-53, 56, 59, 63-88, 92-111, 115-150, 158-162, 169-205, 223-224, 230-233, 246-248, 266, 273-275, 285, 311-312, 319, 324-325, 329-330, 334-335, 339-340, 350-352, 360-370, 376, 387-396, 404-410, 414-426, 432-440, 445-451, 456-466, 483-530, 536-582, 591-624 /usr/local/lib/python3.8/dist-packages/jedi/api/__init__.py 341 241 29% 58-62, 127-203, 209-248, 251, 254, 275, 278-283, 286-291, 310-311, 314-319, 322-342, 345-350, 370-371, 375-408, 422, 425, 429-431, 454, 471-480, 483-488, 502-514, 517-522, 541-558, 569-600, 603-634, 648-649, 657, 661-671, 683, 686-687, 715, 719-727, 765, 769-777, 800-801, 830-845, 849-855, 863-869, 884-886, 898-901 /usr/local/lib/python3.8/dist-packages/jedi/api/classes.py 297 193 35% 37, 47-49, 53, 81-86, 93, 98-104, 115, 175-187, 202, 208-211, 216-219, 224-227, 260-270, 273, 276, 311-329, 355-368, 374-377, 384-387, 402-403, 406-411, 416-427, 447-448, 451-466, 472-489, 497-522, 525, 542-552, 555-561, 570, 582, 594, 604-613, 616-624, 647-649, 664, 670-675, 678-684, 687-693, 696-697, 709-716, 719, 728, 732-738, 747-748, 758-761, 764, 770, 773, 782-783, 793, 803, 812-814, 824, 836, 839, 853, 861, 870, 879-883 /usr/local/lib/python3.8/dist-packages/jedi/api/completion.py 348 296 15% 30, 35-40, 44-68, 72-73, 80-81, 85-89, 96, 102-114, 117-151, 174-282, 285-295, 298-317, 320-323, 326-337, 340-355, 358-360, 363-365, 371-389, 401-421, 424-431, 442-448, 455-499, 503-516, 539-577, 583-619 /usr/local/lib/python3.8/dist-packages/jedi/api/completion_cache.py 19 11 42% 5-9, 14-19 /usr/local/lib/python3.8/dist-packages/jedi/api/environment.py 219 166 24% 36-37, 41-45, 49, 65-67, 70-107, 110-111, 114, 129, 134-136, 145, 148, 157-169, 173-177, 190-198, 202-238, 242-252, 257-264, 284-321, 334-338, 351-363, 374-377, 385-393, 398-420, 424-425, 432-454, 458-473, 477-480 /usr/local/lib/python3.8/dist-packages/jedi/api/errors.py 19 7 63% 8, 16, 21, 26, 31, 36, 39 /usr/local/lib/python3.8/dist-packages/jedi/api/exceptions.py 5 0 100% /usr/local/lib/python3.8/dist-packages/jedi/api/file_name.py 115 103 10% 17-54, 64-81, 85-99, 103-156 /usr/local/lib/python3.8/dist-packages/jedi/api/helpers.py 319 272 15% 26, 30-35, 39-42, 47, 51-61, 66-71, 77, 83-117, 124-156, 163-179, 183-201, 206-209, 213, 217, 220-268, 272-336, 343-357, 361-371, 375-421, 427-439, 449-465, 474-493, 497-500 /usr/local/lib/python3.8/dist-packages/jedi/api/interpreter.py 23 12 48% 12, 19, 24-25, 28, 34-41 /usr/local/lib/python3.8/dist-packages/jedi/api/keywords.py 34 25 26% 8-15, 22, 30-57 /usr/local/lib/python3.8/dist-packages/jedi/api/project.py 214 164 23% 40-51, 56-61, 65, 78, 82, 92-98, 106-118, 139-151, 156-161, 169-205, 208-213, 236, 248, 251, 256-343, 346, 350-353, 358-362, 375-411, 415 /usr/local/lib/python3.8/dist-packages/jedi/api/refactoring/__init__.py 133 110 17% 19-23, 26-36, 39, 42-48, 51, 56-58, 64-73, 89, 92-98, 104-108, 112-118, 122-138, 142-218, 225 /usr/local/lib/python3.8/dist-packages/jedi/api/refactoring/extract.py 239 210 12% 20-29, 36-41, 49-93, 100-126, 130, 134-138, 147-149, 153, 160-164, 172-200, 204, 209-292, 296-306, 310-316, 320-337, 341-353, 357-363, 371-379, 383-386 /usr/local/lib/python3.8/dist-packages/jedi/api/strings.py 64 47 27% 27-50, 54-58, 68-77, 81-86, 90-93, 97-98, 102-109 /usr/local/lib/python3.8/dist-packages/jedi/cache.py 65 40 38% 32-43, 60-73, 84-93, 105-113 /usr/local/lib/python3.8/dist-packages/jedi/common/__init__.py 1 0 100% /usr/local/lib/python3.8/dist-packages/jedi/common/utils.py 24 18 25% 6-13, 21-26, 31-36 /usr/local/lib/python3.8/dist-packages/jedi/common/value.py 54 31 43% 3-4, 7-11, 48, 55, 59-61, 68-74, 77, 80, 83-84, 87, 90, 93, 96, 99-104, 107, 110, 113 /usr/local/lib/python3.8/dist-packages/jedi/debug.py 80 50 38% 22, 36-56, 74-75, 81-82, 89-97, 103-109, 113-120, 124-127, 136-140 /usr/local/lib/python3.8/dist-packages/jedi/file_io.py 54 30 44% 8, 11, 14, 17, 20, 23, 28, 31, 34, 37, 40-57, 62, 68-69, 72-75 /usr/local/lib/python3.8/dist-packages/jedi/inference/__init__.py 107 76 29% 86-108, 111, 117-121, 126-130, 135-136, 139-140, 144, 147-179, 183-194, 197 /usr/local/lib/python3.8/dist-packages/jedi/inference/analysis.py 126 101 20% 32-37, 41, 45, 50-51, 54, 58, 61, 65, 68, 71, 81-91, 98-109, 116-127, 138-217 /usr/local/lib/python3.8/dist-packages/jedi/inference/arguments.py 228 156 32% 19-31, 53-68, 76-108, 135, 138, 148-172, 180-183, 188, 191-231, 234-239, 242-247, 250, 253-279, 284, 287-288, 291, 296, 300, 304, 308, 311, 314, 317, 321-333, 337-349 /usr/local/lib/python3.8/dist-packages/jedi/inference/base_value.py 285 179 37% 27-34, 39, 42, 45-47, 50, 53, 56, 62-70, 73-77, 84-98, 101-104, 107-120, 123-126, 130-132, 136, 152, 155-163, 166, 169-176, 179, 182, 185, 188, 191, 194, 197, 200, 203, 210, 213-218, 221-223, 226-227, 230-231, 234-235, 241, 244-245, 249, 253, 256, 260, 263, 266, 274, 283-289, 294, 297-298, 305-306, 309, 312, 317, 320, 325-326, 329, 334-335, 338, 341, 344, 349-371, 376, 379-382, 387, 390, 393, 396, 399, 402-410, 413, 416, 419-436, 440-448, 456 /usr/local/lib/python3.8/dist-packages/jedi/inference/cache.py 72 44 39% 25-45, 80, 90-121 /usr/local/lib/python3.8/dist-packages/jedi/inference/compiled/__init__.py 38 26 32% 8-16, 25-26, 29-32, 35-37, 40, 48-53, 57, 63-68 /usr/local/lib/python3.8/dist-packages/jedi/inference/compiled/access.py 327 243 26% 82-98, 109-112, 117, 121-140, 145, 151, 154, 158-159, 167-175, 180-181, 184, 187, 190, 193, 196-199, 202, 205-219, 222, 225-227, 230-234, 237-250, 253, 256, 259-265, 270-285, 288, 291, 294, 297, 300, 303-313, 316, 319-323, 327-351, 354-396, 399-401, 404, 407-409, 412-421, 424-425, 428-456, 459-461, 467-482, 485, 488-490, 493, 507-516, 519-538, 541, 548-552, 557-564 /usr/local/lib/python3.8/dist-packages/jedi/inference/compiled/getattr_static.py 97 81 16% 16-21, 25-31, 35-39, 43-54, 58-65, 73-127, 131, 135, 152-184 /usr/local/lib/python3.8/dist-packages/jedi/inference/compiled/mixed.py 155 108 30% 47-49, 52, 58, 63-66, 69-72, 75-78, 81-83, 86, 96, 108-109, 113-117, 121-129, 134-135, 138, 146, 156-175, 179-249, 256-291 /usr/local/lib/python3.8/dist-packages/jedi/inference/compiled/subprocess/__init__.py 236 176 25% 20-21, 37-38, 45-50, 54, 58-70, 75-77, 80-87, 90, 93, 103, 108-110, 113-129, 132-147, 150-151, 160-162, 165-166, 176-206, 211-219, 222, 225-226, 229-273, 283, 288-292, 295-308, 311-327, 330-357, 362-364, 367, 370-374, 377, 380, 383-388, 396-398, 402 /usr/local/lib/python3.8/dist-packages/jedi/inference/compiled/subprocess/functions.py 66 45 32% 15, 19, 23-24, 28, 35-43, 47, 54, 61-66, 74-78, 82, 86, 91-115 /usr/local/lib/python3.8/dist-packages/jedi/inference/compiled/value.py 394 269 32% 36-41, 46-47, 50-69, 73, 77, 84, 90, 93, 96, 99, 102, 105, 108, 111, 114, 118-133, 136-137, 140, 144-148, 152, 155, 159, 162-170, 173-178, 188-198, 201, 205-208, 211-228, 231-236, 239-245, 248-267, 270, 273, 276, 280, 283, 289-291, 298, 301-304, 307, 312-315, 318, 323-326, 329-330, 333-336, 339-343, 346-350, 354-358, 362, 365, 370-371, 375, 378-383, 386, 389-397, 402-404, 407, 410-413, 416, 421-423, 433-434, 437, 442-444, 447-448, 460-478, 482-485, 488-507, 510, 517, 537-587, 591-600, 606, 611-618, 624-629 /usr/local/lib/python3.8/dist-packages/jedi/inference/context.py 294 199 32% 20-21, 25, 28-34, 41-86, 89-106, 109-112, 115, 118, 121, 124, 127, 130, 133, 137, 140, 144, 147, 150, 154-159, 167-168, 172, 176, 179, 182, 185, 188, 191, 194, 197, 200, 204, 207, 210, 213, 216, 221-222, 225-248, 251-287, 290-297, 302, 312, 315-327, 330, 334, 338, 346, 351, 354, 358, 361, 366, 369, 378-380, 383, 386, 389, 392, 397, 404, 408, 411, 418-432, 483-500 /usr/local/lib/python3.8/dist-packages/jedi/inference/docstrings.py 144 116 19% 52-56, 61-75, 82-100, 108-133, 154-161, 179-183, 187-235, 244-245, 256-268, 273-290, 296-307 /usr/local/lib/python3.8/dist-packages/jedi/inference/filters.py 215 115 47% 26-28, 32, 36, 43, 46, 49, 52, 56-68, 75-78, 81, 86, 89, 98, 110-115, 118-120, 123-127, 130-141, 146-151, 154, 158-166, 171-172, 175, 180, 185-189, 193-195, 198, 206, 209-214, 217-223, 226, 229-230, 235, 238, 241, 244, 252-254, 258, 270-278, 281-291, 296-299, 307, 331-334, 340 /usr/local/lib/python3.8/dist-packages/jedi/inference/flow_analysis.py 84 65 23% 15-20, 23-26, 29, 39-42, 46-83, 87-110, 114-123 /usr/local/lib/python3.8/dist-packages/jedi/inference/gradual/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/jedi/inference/gradual/annotation.py 228 193 15% 34-45, 49-59, 63-76, 88-107, 112-132, 139-182, 186-195, 204-230, 247-272, 276-282, 295-304, 308-313, 351-370, 374, 378-381, 385, 389-408, 414-425, 429-433, 437-443 /usr/local/lib/python3.8/dist-packages/jedi/inference/gradual/base.py 217 149 31% 18-20, 23-32, 35, 38, 53-54, 57-63, 68, 73-81, 86, 89, 93, 96-117, 122-137, 147, 162-163, 166, 169-178, 181, 184-185, 188, 192-193, 196, 199-201, 205-242, 247-248, 252-261, 264-279, 284-293, 296, 310-314, 318, 322-332, 338, 342, 345, 348, 353-355, 359, 362, 365, 370-373, 376, 379 /usr/local/lib/python3.8/dist-packages/jedi/inference/gradual/conversion.py 138 122 12% 11-47, 51-59, 64-92, 96-98, 109-142, 146-153, 158-167, 175-208 /usr/local/lib/python3.8/dist-packages/jedi/inference/gradual/generics.py 67 38 43% 15-23, 28-32, 35, 40-41, 45, 48, 53-63, 70-71, 74-78, 81, 86, 89, 92, 95, 98, 101 /usr/local/lib/python3.8/dist-packages/jedi/inference/gradual/stub_value.py 69 43 38% 13-14, 17, 25-34, 37, 43-50, 53, 60, 65-70, 73, 78-81, 88-101 /usr/local/lib/python3.8/dist-packages/jedi/inference/gradual/type_var.py 84 65 23% 9-18, 27-48, 53-71, 74, 77, 80-85, 89, 93, 98-105, 108, 111-114, 117 /usr/local/lib/python3.8/dist-packages/jedi/inference/gradual/typeshed.py 158 130 18% 23-26, 33-53, 57-69, 81-89, 95-124, 130-143, 154-229, 233-249, 258-264, 271, 281-295 /usr/local/lib/python3.8/dist-packages/jedi/inference/gradual/typing.py 236 154 35% 40, 43-96, 105-130, 137, 140, 151, 159, 174, 179, 183, 189-228, 237-240, 244, 247, 250, 253-266, 269, 278-286, 293, 296-303, 306-310, 313-316, 321-323, 327-355, 368-369, 376, 381-386, 397-399, 402, 406-407, 413, 426-429, 433, 436-442, 445-449, 455-457 /usr/local/lib/python3.8/dist-packages/jedi/inference/gradual/utils.py 17 14 18% 11-30 /usr/local/lib/python3.8/dist-packages/jedi/inference/helpers.py 122 97 20% 17-21, 29-43, 65-109, 113-121, 125-129, 133, 137-139, 143, 147, 151, 160-163, 167-192, 196, 200-207 /usr/local/lib/python3.8/dist-packages/jedi/inference/imports.py 284 237 17% 39, 42-43, 46, 53-70, 75-96, 100-118, 122-125, 134-152, 169-224, 229, 235-238, 247-260, 269-273, 284-326, 331-356, 365-427, 432-440, 450-464, 473-510, 514-519, 523-548, 558-563 /usr/local/lib/python3.8/dist-packages/jedi/inference/lazy_value.py 37 18 51% 7-9, 12, 15, 21, 27, 32, 35, 40-44, 47-48, 52-55, 61 /usr/local/lib/python3.8/dist-packages/jedi/inference/names.py 450 314 30% 16-23, 38, 44, 47-54, 58, 61, 64, 67-69, 73, 76, 80, 87, 99-101, 104, 109-110, 113-126, 129-132, 135-139, 142-211, 214-215, 219, 223, 228, 231-237, 240, 243-245, 248-251, 255, 260-261, 264, 278-279, 287-290, 307-331, 334-346, 351-354, 357-360, 363-368, 371, 378, 381, 392, 396-401, 409-416, 419-424, 427, 432-434, 437, 441, 444-450, 453-456, 460, 463-488, 491-496, 502, 506-525, 530-531, 534-538, 541-543, 548, 551, 554, 562-563, 566-574, 578-584, 588-590, 593, 597, 600, 609, 612, 615, 620-634, 640-644, 651-652, 656 /usr/local/lib/python3.8/dist-packages/jedi/inference/param.py 130 113 13% 14-18, 23-26, 29, 32-47, 50, 73-225, 246, 250-257 /usr/local/lib/python3.8/dist-packages/jedi/inference/parser_cache.py 4 1 75% 6 /usr/local/lib/python3.8/dist-packages/jedi/inference/recursion.py 67 47 30% 55, 64-75, 81-90, 100-105, 108-109, 112-153 /usr/local/lib/python3.8/dist-packages/jedi/inference/references.py 182 157 14% 29-42, 46, 53-69, 73-77, 81-96, 100-113, 117-160, 164-175, 179-193, 197-218, 222-224, 228-245, 257-270, 274-291 /usr/local/lib/python3.8/dist-packages/jedi/inference/signature.py 108 72 33% 9-34, 39-40, 44, 48, 51-54, 57, 60, 63-65, 70-71, 74, 80-82, 86-89, 93-97, 100-117, 122-124, 128, 132-134, 137, 146, 149 /usr/local/lib/python3.8/dist-packages/jedi/inference/syntax_tree.py 545 485 11% 45-63, 69-137, 144-150, 155, 161-237, 241-261, 270-352, 357-366, 385-444, 448-469, 477-487, 493-502, 506-518, 526-538, 542, 546, 550, 554-567, 571-642, 647-730, 741-782, 789-809, 814, 821-846 /usr/local/lib/python3.8/dist-packages/jedi/inference/sys_path.py 148 125 16% 18-29, 43-72, 79-97, 105-135, 139-147, 151-170, 174-177, 189-207, 211-215, 230-271 /usr/local/lib/python3.8/dist-packages/jedi/inference/utils.py 55 23 58% 13, 20, 26, 32, 74-78, 84-86, 89, 92, 96, 99-103, 112-115 /usr/local/lib/python3.8/dist-packages/jedi/inference/value/__init__.py 4 0 100% /usr/local/lib/python3.8/dist-packages/jedi/inference/value/decorator.py 7 3 57% 11-12, 15 /usr/local/lib/python3.8/dist-packages/jedi/inference/value/dynamic_arrays.py 114 87 24% 36-40, 52-123, 128-130, 144-145, 148-149, 152-165, 168, 173-175, 178, 181-187, 192-194, 197, 202-204 /usr/local/lib/python3.8/dist-packages/jedi/inference/value/function.py 305 223 27% 32-33, 37, 40, 45-54, 61-64, 67-71, 74, 79-81, 84, 87, 90-114, 117-118, 121-123, 126, 132-161, 164-165, 168, 171, 176-177, 180, 185-186, 189, 194-197, 201, 206, 211-248, 251-263, 268-312, 315, 321, 327-360, 365-366, 369, 377-378, 381, 391, 394, 401, 406-407, 410-421, 424, 427, 431-470 /usr/local/lib/python3.8/dist-packages/jedi/inference/value/instance.py 353 227 36% 28-30, 33, 36, 41-42, 45-58, 63-64, 67, 74-81, 86-87, 94-97, 100, 103, 106, 109, 113, 117, 120-121, 125, 128, 134, 137, 144-146, 149-155, 159, 162, 168-172, 176, 179-199, 203-215, 223-239, 242-250, 253-275, 278-283, 291-297, 303-307, 314-322, 328-349, 352, 355-370, 373-393, 396, 406-414, 418-422, 427-428, 431, 434, 437-438, 446-448, 451, 455, 461-462, 465-466, 469-473, 476-480, 483, 489, 492, 497, 500, 508-510, 514, 517, 522-523, 527-529, 532, 535, 545-546, 549, 552, 555, 561, 569-575, 578-580, 583-592, 595-597, 605, 608, 613-614, 617-619 /usr/local/lib/python3.8/dist-packages/jedi/inference/value/iterable.py 404 270 33% 27, 37-40, 49-52, 55, 58, 62, 68, 71, 75, 81-82, 85, 88, 91, 95-122, 133, 136-163, 168-170, 173-174, 177, 182, 190, 193, 196-203, 206, 210, 213-215, 220-224, 231-237, 251, 255, 262-267, 270-271, 274-280, 283, 286, 290-291, 295-306, 311, 321-329, 332-334, 338-343, 350-358, 362, 365-407, 414-417, 420, 427-429, 433-439, 447-453, 457-458, 462-470, 473, 479, 490-491, 494-499, 502, 505, 508, 523-524, 527-528, 531-548, 552, 558, 561, 564, 567, 572-574, 577-579, 582, 589-620, 625-630, 633-635, 642-658 /usr/local/lib/python3.8/dist-packages/jedi/inference/value/klass.py 204 151 26% 59-61, 66-75, 81-87, 90, 100-105, 112-126, 130-131, 136, 139-144, 147, 151, 154, 158-187, 190-221, 227-229, 232, 235-237, 243-267, 275-289, 292-296, 300-309, 314-317, 329-330, 336-356, 360-361, 365-379 /usr/local/lib/python3.8/dist-packages/jedi/inference/value/module.py 129 85 34% 22-24, 27-35, 45-56, 63-73, 76-77, 80, 83, 88, 92-98, 101-104, 111-128, 136, 144-156, 159-164, 167-169, 175-178, 181, 184-186, 194-219, 222, 225 /usr/local/lib/python3.8/dist-packages/jedi/parser_utils.py 194 159 18% 26-56, 60-69, 79, 83-94, 99-109, 113-124, 128-142, 158-175, 182-188, 196-219, 223-228, 235-244, 252-269, 280, 287-292, 299-311, 322-326 /usr/local/lib/python3.8/dist-packages/jedi/plugins/__init__.py 31 1 97% 21 /usr/local/lib/python3.8/dist-packages/jedi/plugins/flask.py 11 8 27% 7-20 /usr/local/lib/python3.8/dist-packages/jedi/plugins/pytest.py 99 71 28% 21-25, 31-41, 44-61, 67-77, 83-90, 95-98, 108-112, 117, 123-142, 147-153, 156-164 /usr/local/lib/python3.8/dist-packages/jedi/plugins/registry.py 5 0 100% /usr/local/lib/python3.8/dist-packages/jedi/plugins/stdlib.py 440 292 34% 106-132, 138-143, 157-173, 181-188, 194, 200-208, 213-217, 223-224, 227, 230-235, 238-241, 246-253, 258-259, 263, 268, 278-289, 294-328, 336, 341, 346-347, 350, 358-360, 363, 366, 371-372, 375-377, 382, 391-392, 395-397, 403, 408, 423-470, 475-478, 481-485, 488-502, 505-509, 514, 519, 524-526, 529-530, 535-537, 540-549, 553, 560, 568, 573, 581-586, 591-612, 617-618, 621, 626-628, 631, 634-637, 642-643, 647-661, 666, 675, 680-681, 685, 688, 693, 702-711, 717-734, 801-808, 814-817, 821, 824-825, 828-833, 838-842 /usr/local/lib/python3.8/dist-packages/jedi/settings.py 19 2 89% 72, 75 /usr/local/lib/python3.8/dist-packages/joblib/__init__.py 18 0 100% /usr/local/lib/python3.8/dist-packages/joblib/_compat.py 15 3 80% 11, 24-25 /usr/local/lib/python3.8/dist-packages/joblib/_memmapping_reducer.py 180 132 27% 28, 38-39, 70, 73-78, 81-95, 98, 107-119, 152-178, 183, 189-202, 213-236, 243-252, 281-286, 293-298, 301-361, 374-434 /usr/local/lib/python3.8/dist-packages/joblib/_memory_helpers.py 65 63 3% 5-105 /usr/local/lib/python3.8/dist-packages/joblib/_multiprocessing_helpers.py 34 11 68% 20-21, 34-37, 51-53, 61-64 /usr/local/lib/python3.8/dist-packages/joblib/_parallel_backends.py 271 174 36% 38-39, 78-79, 92, 99, 123, 132-136, 153, 163-184, 188, 203-205, 209-212, 216-220, 230-238, 242-245, 249, 253, 258-260, 282-284, 288-344, 348-360, 367-368, 392-399, 407-409, 432-462, 467-489, 493-497, 509-519, 523-547, 551-555, 561-564, 567-574, 579-583, 590, 593, 604, 607-624, 631 /usr/local/lib/python3.8/dist-packages/joblib/_store_backends.py 196 137 30% 26-31, 152-174, 179-193, 198-200, 205-208, 212, 217-223, 227-238, 242-243, 247-249, 253-260, 264-270, 274, 278, 282-294, 298-322, 326-328, 332, 345-348, 352, 356-388, 395-415 /usr/local/lib/python3.8/dist-packages/joblib/backports.py 48 37 23% 22-30, 37-76, 80-81 /usr/local/lib/python3.8/dist-packages/joblib/compressor.py 315 209 34% 12-13, 17-18, 22-23, 27-28, 61, 65, 73, 78, 107-110, 115, 127, 130-131, 136-140, 145-152, 164, 168-172, 178-186, 202, 206-209, 220, 225-235, 239-243, 248-249, 289-321, 330-348, 353, 357-358, 362, 366-367, 371-372, 377-383, 386-388, 391-393, 396-401, 406-424, 430-440, 446-470, 478-485, 492-493, 502-511, 515-520, 537-562, 566-568 /usr/local/lib/python3.8/dist-packages/joblib/disk.py 59 42 29% 27-38, 44-52, 59-63, 90-101, 106-124 /usr/local/lib/python3.8/dist-packages/joblib/executor.py 32 21 34% 28-50, 58-59, 63-65, 68-69, 72-73 /usr/local/lib/python3.8/dist-packages/joblib/externals/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/joblib/externals/cloudpickle/__init__.py 7 0 100% /usr/local/lib/python3.8/dist-packages/joblib/externals/cloudpickle/cloudpickle.py 623 480 23% 65-66, 85, 88-95, 109-115, 119-124, 128-139, 151-164, 169-202, 209-227, 257-274, 334-339, 343-384, 388, 406, 410-432, 440-443, 448-465, 473-477, 480-488, 491, 496-499, 505-509, 517-541, 551-556, 579-582, 591-608, 617-692, 706-760, 767-812, 820-847, 850-851, 854, 865-879, 886-892, 900-941, 944, 948, 953-954, 961-967, 974-989, 996-1033, 1036, 1039, 1050, 1055, 1060, 1066, 1073, 1083-1089, 1093-1094, 1109, 1122-1128, 1138-1139, 1143-1145, 1149, 1153, 1157-1161, 1186, 1194-1251, 1260, 1271-1281, 1296-1297, 1305-1315, 1335-1348, 1357-1397 /usr/local/lib/python3.8/dist-packages/joblib/externals/cloudpickle/cloudpickle_fast.py 227 169 26% 47, 60-63, 70-78, 83-84, 91, 103-132, 136-158, 162-174, 190-198, 203-208, 212-213, 218-260, 264, 268, 272, 276-279, 283, 287, 291, 295, 306-312, 320-330, 346-370, 374-385, 419-431, 463-475, 481-483, 498-501, 504-534, 537-547 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/__init__.py 11 0 100% /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/_base.py 287 271 6% 34-615, 623-627 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/backend/__init__.py 10 0 100% /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/backend/_posix_reduction.py 41 21 49% 20, 29-31, 36-43, 51-52, 55-58, 67-68, 71-74 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/backend/compat.py 18 8 56% 14, 19, 23, 29-38 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/backend/compat_posix.py 4 1 75% 11 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/backend/context.py 135 95 30% 37-85, 91-97, 101, 118-153, 164-165, 170-171, 175-206, 214-215, 219-220, 224-225, 229-230, 234-235, 239-240 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/backend/process.py 57 42 26% 20-31, 35-39, 42-64, 67-81, 89, 100-108 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/backend/queues.py 131 102 22% 36-62, 66-67, 72-75, 79-111, 121-175, 182-183, 187-189, 195-210, 214-215, 219, 225-229, 234-240 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/backend/reduction.py 126 59 53% 27-30, 63-66, 79-82, 87, 91, 101, 109, 113, 121, 127-129, 146, 149, 154-165, 176-177, 185-197, 202-210, 218, 223, 232-234, 240, 246-250, 256 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/backend/utils.py 94 75 20% 11-12, 20-21, 25-28, 32-46, 52-60, 67-116, 125-138, 143-145, 149-172 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/cloudpickle_wrapper.py 60 44 27% 7-8, 16-17, 20-24, 29-31, 38, 42-44, 48-49, 55-83, 95-113 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/process_executor.py 507 411 19% 88-89, 94, 132-138, 143, 146-147, 150-155, 158-159, 171-174, 177-179, 182-184, 189-197, 214, 217, 223-229, 232, 236-237, 245-248, 254-256, 262-268, 271-272, 275, 283-286, 289-312, 317-325, 337, 342-347, 372-465, 487-505, 542-757, 766-785, 794-797, 803-810, 882-933, 939-951, 955-994, 998-1014, 1019-1022, 1025-1048, 1073-1081, 1084-1117 /usr/local/lib/python3.8/dist-packages/joblib/externals/loky/reusable_executor.py 91 70 23% 34-37, 84-142, 150-155, 158-159, 163-194, 199-207, 212-213 /usr/local/lib/python3.8/dist-packages/joblib/format_stack.py 209 188 10% 34-35, 45-68, 72, 88-94, 104-116, 120-147, 151-176, 181-322, 337-365, 371-401 /usr/local/lib/python3.8/dist-packages/joblib/func_inspect.py 176 154 12% 47-79, 84-93, 110-162, 173-177, 190-193, 198-203, 228-318, 322-325, 330-349, 356-359 /usr/local/lib/python3.8/dist-packages/joblib/hashing.py 117 85 27% 24, 33-42, 49, 58-64, 67-75, 78-94, 101-103, 111-127, 141-150, 155, 174-182, 189-242, 258-267 /usr/local/lib/python3.8/dist-packages/joblib/logger.py 76 55 28% 28-31, 35-36, 40-44, 48-57, 77, 81, 85, 96-124, 136-156 /usr/local/lib/python3.8/dist-packages/joblib/memory.py 374 270 28% 57-63, 92-100, 106, 109, 112, 114-133, 135, 146-148, 153-160, 166-182, 225-244, 248-253, 257-277, 281, 284, 293-295, 306-307, 310-313, 316-317, 320-325, 329, 332-333, 358, 361, 365, 415-453, 483-545, 562-563, 568, 574-576, 583, 588-590, 594-595, 605-625, 636-713, 717-724, 730-745, 764-795, 804, 884, 887-901, 905, 914-921, 952, 956-962, 971-974, 978-979, 990-992, 999, 1008-1010 /usr/local/lib/python3.8/dist-packages/joblib/my_exceptions.py 53 20 62% 24, 27-33, 46-48, 51-59, 75, 80, 84, 89, 94-99, 112-113 /usr/local/lib/python3.8/dist-packages/joblib/numpy_pickle.py 204 161 21% 13-14, 78-82, 91-104, 112-161, 165-178, 195-209, 234-249, 253-260, 272-295, 320-332, 342-355, 361, 415-515, 526-548, 588-607 /usr/local/lib/python3.8/dist-packages/joblib/numpy_pickle_compat.py 105 75 29% 21-25, 38-61, 71-75, 90-92, 96-120, 140-142, 148-154, 164-173, 176, 185-192, 198, 227-247 /usr/local/lib/python3.8/dist-packages/joblib/numpy_pickle_utils.py 92 65 29% 22-23, 27-28, 36-37, 45-49, 54-56, 73-90, 95-100, 105-112, 144-182, 187-197, 229-245 /usr/local/lib/python3.8/dist-packages/joblib/parallel.py 362 293 19% 40-41, 65-73, 83-124, 181-209, 212, 215, 218-222, 234, 241-249, 254-255, 259, 267-270, 282-291, 297-311, 327-329, 332-340, 360-363, 388-389, 620-696, 699-701, 704-705, 709-725, 728-730, 733-734, 744-759, 769-771, 783-836, 842-849, 855-887, 895-940, 943-1032, 1035 /usr/local/lib/python3.8/dist-packages/joblib/pool.py 116 83 28% 42-43, 75-87, 91-99, 120-127, 130-131, 135-137, 140, 143-177, 199-207, 210-216, 296-313, 316-329 /usr/local/lib/python3.8/dist-packages/jupyter_client/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/jupyter_client/_version.py 4 0 100% /usr/local/lib/python3.8/dist-packages/jupyter_client/adapter.py 256 210 18% 17-25, 38-52, 64, 67, 70-74, 81, 84-96, 103-109, 125-127, 132-146, 149-151, 154-157, 160-170, 173-179, 182-190, 194-195, 200-202, 205-214, 219-220, 231-234, 239-258, 261-266, 269-282, 285-290, 297-307, 310-317, 321-339, 344-346, 349-358, 363-364, 386-398 /usr/local/lib/python3.8/dist-packages/jupyter_client/asynchronous/__init__.py 1 0 100% /usr/local/lib/python3.8/dist-packages/jupyter_client/asynchronous/channels.py 45 28 38% 29-32, 35-37, 41-48, 52-58, 62, 65-70, 74, 79, 82 /usr/local/lib/python3.8/dist-packages/jupyter_client/asynchronous/client.py 188 138 27% 23-29, 34, 69, 77, 81, 85, 89, 94-101, 112-150, 162-177, 194-212, 216-224, 231-235, 239-253, 311-388 /usr/local/lib/python3.8/dist-packages/jupyter_client/blocking/__init__.py 1 0 100% /usr/local/lib/python3.8/dist-packages/jupyter_client/blocking/channels.py 50 32 36% 11-12, 35-38, 41-43, 47-57, 61-67, 71, 74-79, 83, 88, 91 /usr/local/lib/python3.8/dist-packages/jupyter_client/blocking/client.py 161 121 25% 25-31, 36, 77-115, 127-142, 159-179, 183-191, 198-202, 262-339 /usr/local/lib/python3.8/dist-packages/jupyter_client/channels.py 119 82 31% 61-80, 87-88, 91-99, 109-132, 136-170, 174, 178, 182-185, 189-192, 195-200, 210 /usr/local/lib/python3.8/dist-packages/jupyter_client/channelsabc.py 25 7 72% 16, 20, 24, 37, 41, 45, 49 /usr/local/lib/python3.8/dist-packages/jupyter_client/client.py 172 120 30% 26-30, 53, 78, 82, 86, 90, 105-118, 125-134, 139, 148-155, 160-167, 172-179, 184-190, 195-202, 206-218, 258-277, 295-300, 322-329, 363-370, 379-381, 390-396, 404-406, 410-412, 420-422, 441-443 /usr/local/lib/python3.8/dist-packages/jupyter_client/clientabc.py 45 14 69% 32, 36, 40, 44, 48, 52, 60, 64, 68, 72, 76, 80, 84, 88 /usr/local/lib/python3.8/dist-packages/jupyter_client/connect.py 247 186 25% 79-167, 191-224, 253-274, 296, 319-325, 329-330, 350, 355-356, 377-396, 402-406, 413-419, 423-430, 438-446, 455-461, 465-481, 492-497, 511-523, 531-538, 542-551, 555-557, 561, 565, 569, 573 /usr/local/lib/python3.8/dist-packages/jupyter_client/jsonutil.py 50 34 32% 38-44, 53-59, 63-72, 76-84, 88-92 /usr/local/lib/python3.8/dist-packages/jupyter_client/kernelspec.py 196 139 29% 44-47, 50-58, 65, 73, 82, 90-103, 108, 111, 130, 134, 146-159, 163-183, 190-200, 204-222, 229-237, 252-270, 277-289, 292-297, 315-347, 351-354, 359, 366, 370, 376 /usr/local/lib/python3.8/dist-packages/jupyter_client/launcher.py 59 51 14% 56-158 /usr/local/lib/python3.8/dist-packages/jupyter_client/localinterfaces.py 170 129 24% 29-30, 34-42, 48-52, 58-59, 68-89, 96-108, 113-121, 127-135, 140-164, 173-196, 201-203, 216-248, 254, 259, 264, 269, 274 /usr/local/lib/python3.8/dist-packages/jupyter_client/manager.py 349 261 25% 42, 48, 52, 61, 64, 75-77, 83-85, 102, 109, 113, 126-127, 134, 137, 141-143, 147-149, 157-166, 174-205, 212, 217-219, 222-225, 239-267, 274-283, 286-287, 301-306, 311-315, 323-338, 342-347, 368-379, 406-418, 423, 430-456, 464-478, 488-498, 502-509, 523-524, 538-543, 551-562, 583-594, 621-634, 641-675, 683-697, 707-717, 721-728, 735-736, 744-755, 760-771, 784-789 /usr/local/lib/python3.8/dist-packages/jupyter_client/managerabc.py 27 8 70% 21, 29, 33, 37, 41, 45, 49, 53 /usr/local/lib/python3.8/dist-packages/jupyter_client/multikernelmanager.py 185 104 44% 31-39, 60-63, 67, 73, 76-90, 94-105, 109, 119, 123, 126, 130-147, 157-160, 174-188, 198, 212, 216-222, 233, 247, 258, 275-276, 286-287, 402, 422-428, 442-456, 461-463, 473-475, 488-490, 500-502, 506-512 /usr/local/lib/python3.8/dist-packages/jupyter_client/session.py 442 311 30% 27, 65-75, 148-153, 157, 172, 177, 184, 187-191, 201-205, 209, 212, 215, 218, 221, 226-228, 232-247, 305-315, 323-333, 338-340, 344, 364, 368, 376-384, 388, 393-396, 411-412, 423-425, 432-434, 488-496, 508-514, 519-521, 525-568, 571, 580-590, 600-605, 630-664, 711-766, 784-794, 810-828, 853-865, 869-876, 883-889, 916-954, 957-961, 965-978 /usr/local/lib/python3.8/dist-packages/jupyter_core/__init__.py 1 0 100% /usr/local/lib/python3.8/dist-packages/jupyter_core/paths.py 194 155 20% 33-38, 47-51, 59-68, 78-98, 109-114, 118-122, 147-166, 170-174, 186-202, 209-213, 232-247, 266-287, 291, 316-344, 361-377, 394, 415-448, 452-456 /usr/local/lib/python3.8/dist-packages/jupyter_core/version.py 2 0 100% /usr/local/lib/python3.8/dist-packages/keras_preprocessing/__init__.py 18 5 72% 22, 37-40 /usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/affine_transformations.py 107 77 28% 16-17, 22-24, 28-31, 55-59, 84-90, 114-118, 145-156, 171-180, 194-195, 212-219, 236-242, 246-251, 281, 285-289, 292-298, 301-308, 311-317, 320-335 /usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/dataframe_iterator.py 120 97 19% 93-99, 124-173, 180-223, 227-233, 237-261, 273-284, 288, 292-295, 299 /usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/directory_iterator.py 65 4 94% 72-73, 106, 162 /usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/image_data_generator.py 213 111 48% 17-18, 301, 308-310, 316, 327-331, 335-342, 347-349, 354-356, 361-363, 421, 649-666, 708, 712, 714, 717-720, 725-728, 734-739, 761, 764, 771-778, 783-790, 795, 804, 814, 819, 877, 882, 885, 888, 902-903, 933-988 /usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/iterator.py 146 51 65% 50, 54, 59, 74, 78-95, 101, 104, 112-116, 127, 175, 180-183, 188-193, 201, 205-209, 243-250, 253, 255-257, 263-268, 272, 277, 285, 292 /usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/numpy_array_iterator.py 87 75 14% 46-52, 68-150, 156-183 /usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/utils.py 121 54 55% 16-18, 47, 71-76, 107-109, 111, 118-119, 121-122, 125-127, 132, 153-154, 179, 217, 251-286, 305, 312-319 /usr/local/lib/python3.8/dist-packages/keras_preprocessing/sequence.py 155 135 13% 55-110, 143-149, 197-240, 254-259, 334-354, 360, 364-378, 386-402, 427-432, 446-454 /usr/local/lib/python3.8/dist-packages/keras_preprocessing/text.py 198 166 16% 21, 42-63, 88, 128-138, 179-197, 212-251, 263-267, 281, 298-324, 338, 355-370, 382-383, 400-438, 449-455, 482-487, 500-519 /usr/local/lib/python3.8/dist-packages/parso/__init__.py 8 3 62% 56-58 /usr/local/lib/python3.8/dist-packages/parso/_compatibility.py 36 15 58% 27-29, 38-43, 49-51, 60-64, 69 /usr/local/lib/python3.8/dist-packages/parso/cache.py 103 67 35% 66, 68, 89-94, 101-111, 120-144, 148-160, 164-174, 178-179, 183-186, 190-193, 197-202 /usr/local/lib/python3.8/dist-packages/parso/file_io.py 20 11 45% 6, 12-13, 19-23, 26, 31-32, 35 /usr/local/lib/python3.8/dist-packages/parso/grammar.py 127 89 30% 33-40, 77-79, 90-155, 158-161, 169-172, 175, 178-183, 190-191, 194-196, 199-201, 210-216, 219, 223, 234-260 /usr/local/lib/python3.8/dist-packages/parso/normalizer.py 137 74 46% 19-24, 27-33, 36-39, 42-48, 52-53, 56-57, 60-65, 68, 71, 74-77, 101, 117-120, 125-138, 141, 144, 147, 150, 158, 161, 164, 167-171, 174-181, 184-186, 191, 194-197, 200-203 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126-144, 148, 153-172, 176-178, 182-280, 283-286, 289-290, 293-341, 344-375, 378-519, 522-537, 545-629, 632-685, 688-700, 727 /usr/local/lib/python3.8/dist-packages/parso/python/prefix.py 56 35 38% 11-16, 20-25, 28-29, 35, 69-94 /usr/local/lib/python3.8/dist-packages/parso/python/token.py 12 1 92% 10 /usr/local/lib/python3.8/dist-packages/parso/python/tokenize.py 458 395 14% 60-61, 70, 75, 80-111, 119-124, 136-265, 274-278, 283, 289-295, 298, 301-304, 307, 310, 313, 317-331, 335-371, 376-377, 384-389, 401-672, 676-705, 709-722 /usr/local/lib/python3.8/dist-packages/parso/python/tree.py 642 403 37% 48-49, 79-97, 111-119, 126, 134-143, 154, 180, 192, 204, 211, 221-249, 267, 270-275, 311-314, 318, 321, 343, 349, 355, 361, 364-372, 378, 381-386, 400-401, 412-417, 426-429, 436-453, 469, 475-485, 496, 503-509, 523-566, 586-588, 591, 597, 601, 607-624, 630-639, 645-654, 660, 667-673, 692-694, 701, 704, 711, 714, 734-736, 744-752, 758-763, 779, 782, 794-798, 810-815, 818-821, 833-842, 845, 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81, 92, 95, 98, 101, 104, 107 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/clipboard/in_memory.py 22 13 41% 23-29, 32-35, 38-41, 44-46 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/completion/__init__.py 6 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/completion/base.py 116 71 39% 48-62, 65-72, 80-82, 90, 95-97, 102-104, 109-111, 120-122, 147-153, 156, 185, 196-197, 212, 217, 225-228, 231, 242, 245, 256, 261-262, 267-272, 275, 284, 290-292, 299-301, 308, 318-333, 338-349 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/completion/filesystem.py 46 36 22% 34-38, 43-98, 107 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/completion/fuzzy_completer.py 70 52 26% 54-60, 65-68, 71-75, 81-116, 131-159, 180-188, 193 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/completion/nested.py 40 28 30% 32-33, 36, 63-75, 81-109 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/completion/word_completer.py 33 26 21% 41-49, 55-83 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/data_structures.py 4 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/document.py 525 407 22% 52, 68-71, 98-121, 130, 133-136, 145, 150, 155, 160, 165, 169, 173, 178-179, 184-185, 193-196, 205-224, 231, 237, 243, 248-250, 256-259, 266, 273, 280-281, 291-292, 301-304, 312-315, 324-340, 345, 350, 356, 372-397, 404-405, 420-434, 446-453, 458-461, 475-496, 510-536, 546-547, 556-572, 581-604, 613-625, 634-652, 661-671, 680-690, 696-699, 705-708, 720-725, 742-747, 761-783, 794-816, 828-834, 838, 842, 846-854, 858, 864, 872-876, 890-897, 908-947, 958-997, 1005-1033, 1048-1098, 1104-1111, 1118-1129, 1136-1145, 1154, 1165-1174 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/enums.py 7 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/eventloop/__init__.py 4 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/eventloop/async_generator.py 26 18 31% 32-67 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/eventloop/inputhook.py 65 42 35% 50-52, 61-63, 78-80, 83, 86, 89, 94-143, 149-154, 157, 166-167, 170 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/eventloop/utils.py 37 25 32% 9-10, 30-33, 57-83, 90-100 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/filters/__init__.py 4 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/filters/app.py 162 97 40% 13, 54-98, 106, 114, 122-123, 131-132, 140, 148, 154, 160, 168, 182, 191-195, 200, 205, 213-225, 234-248, 253-267, 272-286, 291-295, 300-304, 309-313, 319-323, 329, 334-341, 346-347, 354-355, 364-365, 371-375, 383 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/filters/base.py 92 37 60% 20, 26, 38, 49, 67-77, 88, 90, 101-103, 117-123, 126, 129, 142, 147, 150, 159, 162, 165, 174, 177, 186, 189, 210, 213 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/filters/cli.py 27 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/filters/utils.py 14 2 86% 32, 41 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/formatted_text/__init__.py 6 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/formatted_text/ansi.py 152 133 12% 30-47, 53-109, 115-187, 193-211, 214, 217, 225-228, 246 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/formatted_text/base.py 66 49 26% 6, 30-37, 68-99, 108-114, 126, 129, 144-145, 148-160, 168-174 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/formatted_text/html.py 70 59 16% 30-96, 99, 102, 110-113, 119-123, 129-132 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/formatted_text/pygments.py 14 6 57% 8, 22, 25-30 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/formatted_text/utils.py 24 16 33% 28-29, 40-41, 56-57, 68-85 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/history.py 95 61 36% 33-34, 64-74, 80, 84-85, 101, 120-123, 126-139, 142, 145, 150, 153, 156, 165, 168, 177, 180, 184, 193-194, 197-221, 225-232 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/input/__init__.py 3 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/input/ansi_escape_sequences.py 12 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/input/base.py 53 14 74% 48, 52, 60, 65, 95, 104, 107, 110, 114, 117, 120, 123, 126, 131 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/input/defaults.py 24 17 29% 26-43, 51-58 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/input/typeahead.py 17 8 53% 54-55, 64-67, 75-76 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/input/vt100_parser.py 98 73 26% 48-61, 87-88, 91-92, 98-99, 108-118, 124-168, 176-188, 199-226, 240, 246-247 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/__init__.py 3 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/auto_suggest.py 30 22 27% 26-62 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/basic.py 157 147 6% 27, 31-248 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/completion.py 96 79 18% 21-22, 37-43, 61-79, 90-171, 178-203 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/cpr.py 12 6 50% 14-28 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/emacs.py 270 255 6% 41-335, 339-401, 409-558 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/focus.py 7 2 71% 16, 24 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/mouse.py 63 54 14% 21-146 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/named_commands.py 279 156 44% 56-59, 73-74, 82-83, 91-92, 102-103, 111-112, 118-119, 128-132, 141-145, 153, 162, 176, 184, 192, 200, 208-210, 219-223, 236, 244-246, 254-262, 270, 281-289, 297-302, 310-315, 323-328, 337, 354-364, 373-382, 391-411, 420, 428-436, 444-452, 460, 471-472, 481-482, 491-498, 511, 520, 528, 541, 550, 566-569, 578-586, 599, 609-627, 635, 643, 657, 666-678, 686-687 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/open_in_editor.py 14 7 50% 20, 29-35, 42-46 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/page_navigation.py 26 19 27% 38, 51-59, 67-79 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/scroll.py 80 69 14% 26-50, 57-80, 87, 94, 101-113, 120-144, 151-160, 169-187 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/bindings/vi.py 949 904 5% 74-76, 80-85, 91-94, 105-126, 133-141, 147-166, 181-289, 304-369, 388-2161, 2165-2210 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/defaults.py 11 2 82% 35-49 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/digraphs.py 4 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/emacs_state.py 17 7 59% 18-19, 22, 27, 31, 35-36 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/key_bindings.py 215 138 36% 57, 101, 104, 126, 137, 149, 158, 189-196, 199-201, 205, 209, 238-281, 297-325, 340-364, 376-389, 397-417, 461-462, 469, 475-476, 480-481, 484-485, 488-489, 514-517, 521-541, 555-556, 563-572, 583, 596-599, 602-607, 617-618, 625-635 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/key_processor.py 238 184 23% 23-24, 44-47, 53, 56-58, 91-98, 101-117, 124-127, 134-145, 152-204, 213-216, 222-225, 236-292, 298-303, 306-354, 362-375, 382-387, 397-420, 443-451, 454, 462, 466-469, 476, 483, 490-499, 506, 514-525, 530 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/key_binding/vi_state.py 47 27 43% 7-8, 28-29, 40-76, 81, 86-91, 98-106 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/keys.py 165 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/__init__.py 7 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/containers.py 956 776 19% 62-64, 140, 148, 155, 160-166, 174, 215-227, 230, 233, 236, 289-308, 311-318, 321-327, 330-331, 339-364, 381-414, 428-474, 526-545, 548-555, 558-579, 582-583, 591-616, 623-667, 684-730, 769-775, 778-781, 784, 792, 803-841, 867-986, 1000-1011, 1014, 1017, 1020-1022, 1069-1090, 1093-1095, 1098-1100, 1103, 1149-1162, 1166, 1177-1185, 1195-1202, 1221, 1230-1236, 1243-1246, 1252-1255, 1263, 1277, 1284, 1294, 1301, 1309-1312, 1319-1324, 1342-1345, 1349, 1353, 1357, 1361, 1364, 1378-1379, 1490-1524, 1527, 1530-1543, 1551-1558, 1564, 1573-1593, 1604-1620, 1637-1671, 1680-1684, 1688-1695, 1710-1726, 1738-1898, 1924-2140, 2150-2162, 2169-2181, 2188-2191, 2203-2214, 2224-2262, 2277-2281, 2287-2292, 2303-2413, 2424-2507, 2525-2528, 2532-2541, 2545-2558, 2561, 2564, 2578-2579, 2582, 2585, 2588-2591, 2594-2597, 2608-2609, 2614, 2626, 2635-2636, 2639, 2642, 2645, 2648, 2651, 2656, 2663, 2670-2675, 2682-2687, 2695-2699 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/controls.py 311 237 24% 51-58, 88, 91, 100, 106, 126, 154, 179-186, 190-193, 216-266, 323-341, 344, 347, 350, 358, 367-369, 379-380, 384-430, 442-469, 472, 475, 488-491, 496, 545-574, 577, 583-589, 593-596, 606-610, 613, 626, 638-657, 666-670, 681-722, 730-819, 825-883, 886-887, 890-891, 897, 904-908, 929-939 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/dimension.py 91 53 42% 44, 56, 58, 60, 71, 75, 78, 94, 98, 101-111, 118-122, 130-167, 184-193, 201-207 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/dummy.py 17 7 59% 26-37 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/layout.py 188 143 24% 43-70, 73, 79-81, 84-85, 101-166, 175-193, 200, 207-212, 217, 222, 227, 236-241, 248-250, 258-259, 266-269, 276-280, 289-290, 297-300, 306-307, 313-323, 329-339, 345-346, 355-360, 366-375, 382-384, 391-394, 406-417 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/margins.py 119 90 24% 18, 43, 63, 80-81, 84-85, 90-132, 141-142, 145-148, 153-156, 173-175, 178, 183-243, 276-277, 282-283, 288-305 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/menus.py 281 228 19% 43-45, 71, 74-81, 91-95, 101-132, 138, 144, 159-167, 173-181, 190-205, 218-232, 245-265, 281-284, 327-340, 343, 346, 353-371, 383-390, 396-507, 513, 519-557, 564-607, 626-664, 680-685, 694, 697-702, 705-720 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/mouse_handlers.py 12 4 67% 18-24, 39-40 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/processors.py 378 291 23% 38, 80, 109-115, 122, 155-157, 168, 187, 193-243, 264-267, 278-312, 323, 326-334, 354-357, 368-398, 404-439, 451-489, 502-503, 509-522, 529, 541, 544-550, 557, 570-571, 575-580, 583, 593, 597-607, 622-629, 632-645, 660-667, 670-684, 707-710, 713-764, 790-798, 803-855, 858-903, 930-931, 937-940, 943, 958, 961-962, 969-975, 985, 988-1029 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/screen.py 100 71 29% 9, 107-120, 123, 128, 131, 152-192, 198, 204, 211-214, 221-227, 234, 242-249, 256-263, 272-293, 300-307, 310 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/layout/utils.py 32 17 47% 23, 26, 29, 35, 39, 48-53, 67-76 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/lexers/__init__.py 3 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/lexers/base.py 31 15 52% 38, 50, 53-62, 73-74, 77-78, 81-82 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/lexers/pygments.py 112 79 29% 29, 69, 86, 94-110, 117-129, 141-143, 193-202, 214-222, 229-335 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/mouse_events.py 14 3 79% 41-42, 45 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/output/__init__.py 4 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/output/base.py 130 33 75% 164, 174, 177, 180, 183, 186, 189, 192, 195, 198, 201, 204, 207, 210, 213, 216, 219, 222, 225, 228, 231, 234, 237, 240, 243, 246, 249, 252, 255, 258, 261, 264, 267 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/output/color_depth.py 29 12 59% 52-74 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/output/defaults.py 27 20 26% 31-62 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/output/vt100.py 289 192 34% 123-145, 169-175, 181-190, 237-256, 273, 276-300, 304-312, 321-369, 383-396, 420-432, 449-473, 476, 480, 484, 490, 497, 503-507, 512, 519, 522, 525, 528-534, 540-542, 548, 555, 558, 567-570, 573, 576, 579, 582, 588, 591-596, 599-606, 609-614, 617-622, 625, 628, 634-673, 679-680, 684-685 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/patch_stdout.py 61 43 30% 52-68, 81-93, 100-116, 128-139, 142-144, 147-150, 156-157, 164, 167 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/renderer.py 299 255 15% 27-28, 70-243, 262-263, 266-270, 303-326, 331-369, 377, 386, 395-402, 417-457, 464-480, 488, 494-514, 525-637, 648-657, 664-673, 686-716 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/search.py 86 66 23% 16-17, 56-58, 61, 73-78, 94-119, 126-150, 157-181, 190-217, 226 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/selection.py 19 5 74% 48-50, 53, 56 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/shortcuts/__init__.py 5 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/shortcuts/dialogs.py 89 60 33% 53-69, 86-99, 116-140, 152-159, 176-196, 213-231, 246-285, 290-294, 305 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/shortcuts/progress_bar/__init__.py 3 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/shortcuts/progress_bar/base.py 177 119 33% 58-59, 74-85, 128-148, 152-233, 237-247, 265-269, 272, 281-283, 286-300, 303, 306, 326-342, 345-358, 366-367, 379, 383-387, 405, 409-415, 419-422, 429-432, 439-444 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/shortcuts/progress_bar/formatters.py 158 91 42% 22, 52, 55, 64, 72, 75, 89-90, 93-94, 103-113, 116-124, 141, 144, 164-172, 180-206, 211, 228, 233-237, 244-247, 262-263, 268-273, 291-297, 300-306, 325-326, 329-335, 352-353, 358, 391, 402-413, 416, 423 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/shortcuts/prompt.py 449 368 18% 133, 159-184, 193, 406-458, 470-475, 481-490, 516, 522-685, 693-761, 767-824, 912-994, 1010-1040, 1091-1173, 1178-1189, 1193, 1197, 1202-1219, 1222, 1235-1249, 1262-1270, 1274-1282, 1286-1292, 1303, 1307, 1359-1361, 1412-1435, 1442-1443 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/shortcuts/utils.py 59 41 31% 27, 96-147, 160-173, 180-183, 190-191, 198 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/styles/__init__.py 7 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/styles/base.py 37 10 73% 129, 148, 151, 155, 166-167, 172-174, 177, 181 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/styles/defaults.py 15 2 87% 213, 223 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/styles/named_colors.py 3 0 100% /usr/local/lib/python3.8/dist-packages/prompt_toolkit/styles/pygments.py 18 11 39% 14-15, 39-43, 51-56, 66-67 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/styles/style.py 165 126 24% 39-74, 97-103, 112-167, 201, 227-242, 246, 256-264, 272-313, 316, 329-336, 352-353, 373-374, 380-383, 387-390, 395, 398 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/styles/style_transformation.py 124 76 39% 54, 80-83, 94, 111-112, 115-121, 124, 159-160, 163-189, 196-205, 220, 223, 236, 240, 256, 259-262, 265-268, 280-281, 284-286, 289, 294, 297-299, 302, 311, 349-375 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/utils.py 115 73 37% 64-68, 72-73, 77, 86, 92-93, 99-100, 106-107, 116, 119, 141-160, 170, 178, 185, 193-195, 202, 209, 214, 235-271, 276-279, 284-287, 295-298, 308-311 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/validation.py 66 34 48% 32-34, 37, 65, 73-76, 100, 112-114, 117, 120-126, 137, 140, 147-150, 159, 169-170, 174-175, 186, 189-190, 193-194 /usr/local/lib/python3.8/dist-packages/prompt_toolkit/widgets/__init__.py 5 0 100% 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438-447, 456-465, 499-501, 515-528, 536-549, 552-555, 562, 573-590, 602, 608, 614, 622-654, 663-683, 692-760, 771-772, 777-780, 790, 802, 805-808, 818-819, 827-828, 835-836 /usr/local/lib/python3.8/dist-packages/ptyprocess/util.py 35 32 9% 3-67 /usr/local/lib/python3.8/dist-packages/pyasn1/__init__.py 4 1 75% 7 /usr/local/lib/python3.8/dist-packages/pyasn1/codec/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/pyasn1/codec/ber/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/pyasn1/codec/ber/decoder.py 817 685 16% 33, 39, 45, 48-55, 65-79, 85-98, 112-122, 129, 141-190, 197-226, 237-263, 269-293, 304-314, 324-371, 381-478, 490, 493, 496-534, 540-737, 743-946, 983-1023, 1029-1074, 1084-1109, 1115-1171, 1312-1626 /usr/local/lib/python3.8/dist-packages/pyasn1/codec/ber/eoo.py 12 0 100% /usr/local/lib/python3.8/dist-packages/pyasn1/codec/cer/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/pyasn1/codec/cer/decoder.py 32 11 66% 22-35, 57 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137-139, 173-185 /usr/local/lib/python3.8/dist-packages/pywt/data/_wavelab_signals.py 180 175 3% 69-259 /usr/local/lib/python3.8/dist-packages/pywt/version.py 7 1 86% 10 /usr/local/lib/python3.8/dist-packages/rsa/__init__.py 10 2 80% 34-36 /usr/local/lib/python3.8/dist-packages/rsa/common.py 57 46 19% 22-25, 50-53, 76-78, 99-102, 112-127, 139-144, 167-179, 183-185 /usr/local/lib/python3.8/dist-packages/rsa/core.py 20 16 20% 23-26, 32-42, 48-53 /usr/local/lib/python3.8/dist-packages/rsa/key.py 242 170 30% 55-56, 110-116, 124-128, 140-146, 163, 177, 207, 210, 214, 218, 221-227, 230, 233, 256-260, 269-277, 291-292, 301-302, 320-321, 332-341, 371-379, 382, 385, 389, 393, 396-402, 412, 415, 418-422, 434-438, 450-453, 477-511, 520-548, 563-564, 573-574, 610-654, 670-684, 697, 721-728, 760-781, 790-803 /usr/local/lib/python3.8/dist-packages/rsa/pem.py 50 42 16% 29-32, 39-78, 97-105, 120-132 /usr/local/lib/python3.8/dist-packages/rsa/pkcs1.py 124 99 20% 40, 95-120, 145-154, 182-189, 243-264, 284-297, 318-319, 337-357, 371-376, 388-397, 411-425, 436-440, 447-458 /usr/local/lib/python3.8/dist-packages/rsa/prime.py 63 52 17% 34-36, 53-62, 82-115, 130-141, 160-167, 182-183, 187-198 /usr/local/lib/python3.8/dist-packages/rsa/randnum.py 30 22 27% 32-43, 50-57, 67-70, 81-96 /usr/local/lib/python3.8/dist-packages/rsa/transform.py 14 9 36% 34, 58-66, 70-72 /usr/local/lib/python3.8/dist-packages/scipy/__config__.py 28 14 50% 12-13, 24-25, 28-37 /usr/local/lib/python3.8/dist-packages/scipy/__init__.py 62 9 85% 65, 126-128, 132-136, 141-142 /usr/local/lib/python3.8/dist-packages/scipy/_distributor_init.py 0 0 100% /usr/local/lib/python3.8/dist-packages/scipy/_lib/__init__.py 4 0 100% /usr/local/lib/python3.8/dist-packages/scipy/_lib/_ccallback.py 98 71 28% 15-23, 87-88, 91, 95, 99, 103, 106, 125-131, 135-159, 168-180, 184-202, 207, 216-222, 227 /usr/local/lib/python3.8/dist-packages/scipy/_lib/_numpy_compat.py 275 254 8% 18-50, 58-87, 92-102, 109-197, 203-289, 294-568, 573-781 /usr/local/lib/python3.8/dist-packages/scipy/_lib/_testutils.py 77 62 19% 31-73, 81-82, 89-104, 108-119, 126-145 /usr/local/lib/python3.8/dist-packages/scipy/_lib/_threadsafety.py 33 9 73% 33-37, 40-41, 45-46 /usr/local/lib/python3.8/dist-packages/scipy/_lib/_uarray/__init__.py 2 0 100% /usr/local/lib/python3.8/dist-packages/scipy/_lib/_uarray/_backend.py 93 47 49% 48-57, 61-74, 96-99, 194, 213, 275, 306, 338-340, 343, 346, 363, 379-392, 404-417 /usr/local/lib/python3.8/dist-packages/scipy/_lib/_util.py 166 107 36% 19-24, 42-60, 90-100, 111-126, 134-136, 164, 167-170, 186-196, 238-241, 244, 249, 251-252, 320-347, 367-389, 393, 396-397, 400-401, 404-405, 408-409, 412-414, 418-422 /usr/local/lib/python3.8/dist-packages/scipy/_lib/_version.py 76 33 57% 59, 72, 82-87, 91-95, 101-112, 116, 124-132, 140, 143, 146, 155 /usr/local/lib/python3.8/dist-packages/scipy/_lib/decorator.py 252 115 54% 51-68, 77-78, 102, 114, 121-122, 124, 126-127, 140, 146, 150, 162-163, 175, 181, 192-195, 244, 253, 259-261, 275-276, 282, 290-292, 294, 297, 310-319, 328-424 /usr/local/lib/python3.8/dist-packages/scipy/_lib/deprecation.py 15 4 73% 11-14, 18-20 /usr/local/lib/python3.8/dist-packages/scipy/_lib/doccer.py 97 21 78% 53, 116-125, 140, 145, 165, 171, 200, 250, 268-274 /usr/local/lib/python3.8/dist-packages/scipy/_lib/six.py 177 112 37% 43-65, 75-76, 87-92, 106-114, 119-121, 127, 134-142, 155, 160, 165, 170, 173, 176-177, 185-192, 202-204, 210-270, 277 /usr/local/lib/python3.8/dist-packages/scipy/_lib/uarray.py 13 5 62% 17-20, 24-25 /usr/local/lib/python3.8/dist-packages/scipy/cluster/__init__.py 6 0 100% /usr/local/lib/python3.8/dist-packages/scipy/cluster/hierarchy.py 780 667 14% 155, 162-167, 177-178, 195-200, 278, 360, 442, 527, 629, 731, 1040, 1045-1046, 1049, 1052-1053, 1058, 1061, 1068, 1072, 1075, 1113, 1115, 1118, 1121, 1130, 1133-1136, 1139-1142, 1145-1148, 1164, 1178, 1191, 1204, 1216, 1250-1278, 1299-1310, 1357-1391, 1452-1488, 1529-1551, 1555-1559, 1566, 1675-1700, 1758-1774, 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/usr/local/lib/python3.8/dist-packages/scipy/fft/_basic.py 64 23 64% 9-13, 154, 252, 339, 434, 510, 570, 668, 764, 857, 947, 1040, 1083, 1183, 1226, 1333, 1375, 1463, 1506 /usr/local/lib/python3.8/dist-packages/scipy/fft/_helper.py 10 2 80% 62, 101 /usr/local/lib/python3.8/dist-packages/scipy/fft/_pocketfft/__init__.py 6 0 100% /usr/local/lib/python3.8/dist-packages/scipy/fft/_pocketfft/basic.py 133 87 35% 16-30, 44-58, 72-90, 103, 110, 117, 124, 131, 138, 146-161, 172-186, 198-223, 234-251 /usr/local/lib/python3.8/dist-packages/scipy/fft/_pocketfft/helper.py 106 84 21% 28-38, 43-77, 86-95, 102-106, 111-133, 137-141, 147-153, 158-170, 190-195, 210 /usr/local/lib/python3.8/dist-packages/scipy/fft/_pocketfft/realtransforms.py 64 42 34% 19-46, 71-99 /usr/local/lib/python3.8/dist-packages/scipy/fft/_realtransforms.py 28 8 71% 63, 121, 179, 237, 387, 451, 568, 618 /usr/local/lib/python3.8/dist-packages/scipy/integrate/__init__.py 12 0 100% /usr/local/lib/python3.8/dist-packages/scipy/integrate/_bvp.py 378 352 7% 29-57, 75-116, 124-142, 152-158, 243-276, 310-317, 322-347, 418-502, 506, 513, 556-577, 590-602, 632, 642-710, 1001-1159 /usr/local/lib/python3.8/dist-packages/scipy/integrate/_ivp/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/scipy/integrate/_ivp/base.py 99 80 19% 7-23, 118-151, 155-158, 170-191, 201-209, 212, 215, 231-234, 250-253, 256, 266-267, 270-275 /usr/local/lib/python3.8/dist-packages/scipy/integrate/_ivp/bdf.py 245 222 9% 21-26, 31-34, 39-70, 188-242, 245-295, 298-438, 441, 447-451, 454-467 /usr/local/lib/python3.8/dist-packages/scipy/integrate/_ivp/common.py 214 189 12% 13-17, 22-24, 39-40, 46-57, 62, 100-120, 153-176, 181-190, 206-238, 292-320, 325-363, 367-432 /usr/local/lib/python3.8/dist-packages/scipy/integrate/_ivp/dop853_coefficients.py 153 0 100% /usr/local/lib/python3.8/dist-packages/scipy/integrate/_ivp/ivp.py 162 143 12% 31-51, 77-78, 109-128, 146-154, 504-662 /usr/local/lib/python3.8/dist-packages/scipy/integrate/_ivp/lsoda.py 57 46 19% 108-138, 141-161, 164-172, 177-180, 183-188 /usr/local/lib/python3.8/dist-packages/scipy/integrate/_ivp/radau.py 262 230 12% 88-137, 169-177, 286-334, 337-387, 390-529, 532-533, 536, 541-545, 548-562 /usr/local/lib/python3.8/dist-packages/scipy/integrate/_ivp/rk.py 190 127 33% 62-72, 89-104, 107, 110, 113-177, 180-181, 480-485, 488-494, 497-503, 506-524, 529-533, 536-549, 554-557, 560-576 /usr/local/lib/python3.8/dist-packages/scipy/integrate/_ode.py 507 401 21% 348-353, 357, 361-369, 382-394, 422-437, 441-445, 532-536, 540-541, 545-546, 562-567, 584-587, 620-625, 628-633, 637-656, 660, 673-686, 690-694, 722-723, 739-742, 751-754, 765-769, 786-787, 790-791, 804, 809, 814, 826-831, 862-881, 912-939, 942-987, 990-1014, 1017-1021, 1024-1028, 1044-1100, 1132-1143, 1146-1151, 1154-1168, 1171-1179, 1182-1187, 1210, 1216-1230, 1267-1283, 1287-1333, 1336-1353, 1356-1360, 1363-1367 /usr/local/lib/python3.8/dist-packages/scipy/integrate/_quad_vec.py 262 227 13% 16, 19-24, 28, 36-41, 44-48, 51-56, 64-67, 70-71, 74-79, 83, 87-93, 98-99, 102, 202-400, 404-429, 436-449, 461-504, 512-569, 580-622 /usr/local/lib/python3.8/dist-packages/scipy/integrate/odepack.py 32 22 31% 229-260 /usr/local/lib/python3.8/dist-packages/scipy/integrate/quadpack.py 199 172 14% 41, 334-432, 436-465, 469-516, 581-585, 665-674, 799-810, 815, 823, 828, 832, 837-844, 847-883 /usr/local/lib/python3.8/dist-packages/scipy/integrate/quadrature.py 312 274 12% 45-49, 117-123, 151-168, 235-252, 256-258, 315-350, 354-381, 454-506, 568-623, 650-660, 668-669, 674-686, 773-806, 934-975 /usr/local/lib/python3.8/dist-packages/scipy/interpolate/__init__.py 15 0 100% /usr/local/lib/python3.8/dist-packages/scipy/interpolate/_bsplines.py 324 291 10% 20-22, 27-30, 38-43, 182-226, 235-239, 245, 303-308, 332-355, 358, 367-370, 391-397, 425-437, 488-571, 581-588, 593, 597-604, 608-617, 735-861, 969-1022 /usr/local/lib/python3.8/dist-packages/scipy/interpolate/_cubic.py 259 230 11% 28-72, 142-158, 235-240, 245-255, 268-304, 343-350, 405-435, 438, 445, 450, 619-770, 784-837 /usr/local/lib/python3.8/dist-packages/scipy/interpolate/_fitpack_impl.py 413 388 6% 44-48, 215-311, 443-524, 580-607, 654-668, 710-733, 773-791, 890-988, 1039-1057, 1079-1080, 1128-1146, 1196-1229, 1288-1311 /usr/local/lib/python3.8/dist-packages/scipy/interpolate/_pade.py 27 22 19% 46-67 /usr/local/lib/python3.8/dist-packages/scipy/interpolate/fitpack.py 65 49 25% 156-158, 289-290, 353-368, 417-429, 477-491, 531-534, 586-601, 654-657, 719-722 /usr/local/lib/python3.8/dist-packages/scipy/interpolate/fitpack2.py 366 304 17% 171-196, 201-208, 211-232, 235-241, 244-256, 265-276, 303-317, 324-326, 330-332, 342, 380, 405-408, 415-421, 468-471, 524-525, 602-618, 741-770, 793, 801, 805, 841-880, 955-961, 983, 1002-1004, 1048-1069, 1110-1136, 1172-1198, 1273-1281, 1304, 1385-1396, 1486-1504, 1670-1727 /usr/local/lib/python3.8/dist-packages/scipy/interpolate/interpolate.py 920 819 11% 32-34, 84-94, 201-252, 279-313, 318-328, 335, 431-540, 547, 552-581, 585, 591-614, 623-631, 637-646, 649, 652-654, 660-669, 687-700, 708-751, 754-758, 770-777, 784-787, 808-870, 902-923, 986, 1013-1031, 1063-1085, 1108-1167, 1217-1239, 1268, 1284-1296, 1313-1332, 1422, 1443-1477, 1502-1533, 1558-1597, 1600-1603, 1621-1639, 1705-1757, 1814-1843, 1873-1883, 1946-1965, 1978-1984, 1987-1991, 1994-1997, 2028-2062, 2069-2096, 2103-2136, 2163-2169, 2197-2203, 2236-2264, 2287-2312, 2415-2452, 2468-2501, 2505-2516, 2519-2521, 2525-2541, 2601-2676, 2689-2704, 2707, 2710-2712, 2717-2724 /usr/local/lib/python3.8/dist-packages/scipy/interpolate/ndgriddata.py 47 38 19% 59-65, 77-81, 193-228 /usr/local/lib/python3.8/dist-packages/scipy/interpolate/polyint.py 203 169 17% 18, 56-60, 78-80, 86, 90-92, 96-103, 106-111, 114-131, 134-139, 177-188, 216-218, 293-316, 319-326, 329-355, 400-406, 448-461, 502-513, 532-537, 559-577, 599, 602-617, 666 /usr/local/lib/python3.8/dist-packages/scipy/interpolate/rbf.py 105 83 21% 145, 148, 151, 154, 157, 160, 163, 167-216, 223-268, 274-275, 278, 281-290 /usr/local/lib/python3.8/dist-packages/scipy/io/__init__.py 12 0 100% /usr/local/lib/python3.8/dist-packages/scipy/io/_fortran.py 79 61 23% 111-126, 129-136, 161-169, 245-294, 317, 340, 349, 352, 355 /usr/local/lib/python3.8/dist-packages/scipy/io/harwell_boeing/__init__.py 2 0 100% /usr/local/lib/python3.8/dist-packages/scipy/io/harwell_boeing/_fortran_format_parser.py 165 124 25% 34, 62-66, 69-71, 74-80, 84-90, 94, 123-132, 141-144, 147-153, 157-163, 167, 172-174, 177, 180, 185-186, 189-191, 194-205, 234, 237-250, 253-257, 260-261, 264-305, 308-312 /usr/local/lib/python3.8/dist-packages/scipy/io/harwell_boeing/hb.py 265 215 19% 45, 70-120, 141-205, 217-281, 285-299, 303-308, 313-332, 336-360, 391-400, 403-412, 416, 421, 437-443, 447, 451, 455, 459, 463, 466, 469, 496-504, 534-547 /usr/local/lib/python3.8/dist-packages/scipy/io/idl.py 429 382 11% 81-84, 89-90, 95, 100, 105, 110, 115, 120, 125, 130, 135, 140, 145, 152-153, 163-170, 175-182, 187-224, 233-269, 278-316, 322-425, 431-445, 451-492, 498-546, 552-565, 570-631, 652, 655, 658, 705-873 /usr/local/lib/python3.8/dist-packages/scipy/io/matlab/__init__.py 7 0 100% /usr/local/lib/python3.8/dist-packages/scipy/io/matlab/byteordercodes.py 19 12 37% 57-69 /usr/local/lib/python3.8/dist-packages/scipy/io/matlab/mio.py 65 47 28% 19-22, 32-47, 71-80, 215-225, 266-279, 314-317 /usr/local/lib/python3.8/dist-packages/scipy/io/matlab/mio4.py 281 222 21% 91-95, 102-106, 110-127, 135-149, 168-185, 202-207, 221-223, 254-267, 273-301, 313-314, 317-326, 333-334, 351-357, 375, 386-406, 410-422, 442-446, 451-452, 455, 458, 478-490, 504-519, 522-541, 544-560, 567-584, 590-594, 616-618 /usr/local/lib/python3.8/dist-packages/scipy/io/matlab/mio5.py 371 312 16% 151-167, 172-175, 179-186, 196-198, 217-233, 252, 261-307, 311-331, 375-400, 422-455, 471-477, 480, 483, 487-496, 500-504, 508-516, 536-559, 562-570, 587-590, 601-630, 633-655, 660-698, 703-718, 721-726, 729-733, 736-738, 742-755, 761-765, 789-798, 802-809, 829-849 /usr/local/lib/python3.8/dist-packages/scipy/io/matlab/mio5_params.py 77 11 86% 195-197, 227-231, 235, 242-243, 249-250 /usr/local/lib/python3.8/dist-packages/scipy/io/matlab/miobase.py 108 70 35% 20, 179-184, 221-241, 305-318, 324, 328, 332, 363-377, 381-383, 387, 390-393, 398, 403-415 /usr/local/lib/python3.8/dist-packages/scipy/io/mmio.py 444 375 16% 54, 75, 101, 115, 119, 123, 127, 131, 135, 139, 150-151, 164-165, 178-179, 191, 196, 226-269, 294-327, 332-384, 389, 398, 417-425, 451-460, 469-479, 483-485, 490-657, 662-802, 812-828, 833-839 /usr/local/lib/python3.8/dist-packages/scipy/io/netcdf.py 486 393 19% 239-284, 289-293, 297-319, 323, 326, 348-352, 385-397, 408-409, 413-421, 425-428, 431-439, 442, 445-452, 455-479, 482-512, 515-553, 556-558, 561-602, 606-616, 619, 622-631, 634-635, 638-647, 650-733, 736-758, 761-776, 779-782, 785, 789, 793, 796, 799-802, 805-808, 867-876, 881-885, 896, 905, 919, 938-946, 958, 970, 973-988, 991-1021, 1027-1028, 1037-1045, 1058-1065, 1077-1093 /usr/local/lib/python3.8/dist-packages/scipy/linalg/__init__.py 36 4 89% 222-223, 227-228 /usr/local/lib/python3.8/dist-packages/scipy/linalg/_decomp_ldl.py 85 74 13% 123-156, 207-241, 268-297, 335-354 /usr/local/lib/python3.8/dist-packages/scipy/linalg/_decomp_polar.py 16 11 31% 98-112 /usr/local/lib/python3.8/dist-packages/scipy/linalg/_decomp_qz.py 127 110 13% 19-34, 38-43, 47-52, 56-61, 65-71, 76-145, 262-265, 358-405 /usr/local/lib/python3.8/dist-packages/scipy/linalg/_expm_frechet.py 153 138 10% 91-114, 122-127, 166-173, 177-187, 191-203, 207-222, 226-278, 298, 334-350, 393-411 /usr/local/lib/python3.8/dist-packages/scipy/linalg/_matfuncs_sqrtm.py 85 74 13% 52-116, 163-196 /usr/local/lib/python3.8/dist-packages/scipy/linalg/_procrustes.py 18 13 28% 76-91 /usr/local/lib/python3.8/dist-packages/scipy/linalg/_sketches.py 15 8 47% 49-54, 167-168 /usr/local/lib/python3.8/dist-packages/scipy/linalg/_solvers.py 216 194 10% 86-107, 159-199, 214-218, 228-233, 306-324, 446-528, 652-736, 778-844 /usr/local/lib/python3.8/dist-packages/scipy/linalg/basic.py 385 346 10% 27-37, 137-258, 330-359, 433-472, 568-596, 669-702, 706-711, 862-907, 952, 979, 981, 1034-1043, 1157-1246, 1304-1318, 1373-1391, 1451-1470, 1575-1619 /usr/local/lib/python3.8/dist-packages/scipy/linalg/blas.py 86 12 86% 301-310, 341, 352, 381-384 /usr/local/lib/python3.8/dist-packages/scipy/linalg/decomp.py 364 338 7% 41-47, 51-73, 78-115, 214-267, 374-489, 503-530, 640-695, 767, 858, 951, 1031, 1124-1194, 1199-1203, 1252-1283, 1368-1431 /usr/local/lib/python3.8/dist-packages/scipy/linalg/decomp_cholesky.py 72 61 15% 19-44, 90-92, 154-156, 194-213, 274-286, 334-353 /usr/local/lib/python3.8/dist-packages/scipy/linalg/decomp_lu.py 48 38 21% 71-86, 135-148, 209-223 /usr/local/lib/python3.8/dist-packages/scipy/linalg/decomp_qr.py 130 121 7% 16-25, 121-173, 251-320, 386-424 /usr/local/lib/python3.8/dist-packages/scipy/linalg/decomp_schur.py 104 85 18% 119-178, 191-197, 201-210, 266-295 /usr/local/lib/python3.8/dist-packages/scipy/linalg/decomp_svd.py 88 60 32% 111, 116, 118, 132, 134, 139, 225-232, 273-281, 323-330, 384-391, 459-496 /usr/local/lib/python3.8/dist-packages/scipy/linalg/flinalg.py 30 23 23% 14-19, 23, 32-58 /usr/local/lib/python3.8/dist-packages/scipy/linalg/lapack.py 45 4 91% 808, 814, 826, 830 /usr/local/lib/python3.8/dist-packages/scipy/linalg/linalg_version.py 5 0 100% /usr/local/lib/python3.8/dist-packages/scipy/linalg/matfuncs.py 130 103 21% 52-55, 84-89, 136-138, 195-208, 255-256, 291-295, 330-334, 371-372, 409-410, 447-448, 485-486, 551-590, 626-670 /usr/local/lib/python3.8/dist-packages/scipy/linalg/misc.py 42 30 29% 141-181, 192-194 /usr/local/lib/python3.8/dist-packages/scipy/linalg/special_matrices.py 223 197 12% 62-73, 104-106, 138-140, 193-203, 239-244, 290-301, 344-358, 413-430, 465-471, 535-553, 600-617, 654-662, 698-700, 759-777, 840-863, 938-973, 1033-1043, 1109-1119, 1172-1196 /usr/local/lib/python3.8/dist-packages/scipy/misc/__init__.py 10 0 100% /usr/local/lib/python3.8/dist-packages/scipy/misc/common.py 73 65 11% 35-47, 85-120, 154-159, 195-204, 297-303 /usr/local/lib/python3.8/dist-packages/scipy/misc/doccer.py 29 8 72% 15, 21, 27, 33, 39, 44, 49, 54 /usr/local/lib/python3.8/dist-packages/scipy/ndimage/__init__.py 11 0 100% /usr/local/lib/python3.8/dist-packages/scipy/ndimage/_ni_docstrings.py 17 0 100% /usr/local/lib/python3.8/dist-packages/scipy/ndimage/_ni_support.py 43 13 70% 42, 44, 46, 48, 52, 64-65, 78, 80-81, 83, 89, 91 /usr/local/lib/python3.8/dist-packages/scipy/ndimage/filters.py 399 298 25% 81, 85, 90, 129-133, 141, 156-164, 332-340, 369-377, 404-419, 447-449, 487-495, 525-544, 583-591, 598-623, 648, 754, 783-795, 842-857, 897-909, 954-966, 971-1033, 1069, 1106, 1113-1162, 1201-1202, 1240, 1280, 1348-1364, 1421-1448 /usr/local/lib/python3.8/dist-packages/scipy/ndimage/fourier.py 69 58 16% 42-55, 59-70, 120-129, 179-187, 241-249, 298-306 /usr/local/lib/python3.8/dist-packages/scipy/ndimage/interpolation.py 210 182 13% 93-105, 127-139, 245-263, 329-351, 433-487, 520-539, 589-616, 677-746 /usr/local/lib/python3.8/dist-packages/scipy/ndimage/measurements.py 315 288 9% 178-236, 298-305, 377-458, 463-466, 500-573, 617-618, 669-670, 721-722, 773, 782-884, 946, 1025, 1086, 1155-1164, 1210-1219, 1275-1293, 1355-1364, 1419-1424, 1459-1498 /usr/local/lib/python3.8/dist-packages/scipy/ndimage/morphology.py 403 368 9% 50-53, 106-122, 208, 210, 218-285, 381, 501-513, 629-636, 775-782, 871-892, 1022, 1097-1107, 1213-1216, 1338-1364, 1443-1447, 1526-1530, 1636-1643, 1681-1695, 1739-1752, 1797-1810, 1872-1947, 1986-2063, 2175-2230 /usr/local/lib/python3.8/dist-packages/scipy/optimize/__init__.py 26 0 100% /usr/local/lib/python3.8/dist-packages/scipy/optimize/_basinhopping.py 219 182 17% 20, 23-24, 27-31, 34, 61-92, 102-146, 151-173, 177-178, 208-216, 219, 222-232, 238-242, 246-247, 264-265, 268-270, 278-280, 283-286, 304-305, 313-315, 321, 626-701, 705-707, 711-716, 720-736 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_constraints.py 180 157 13% 94-101, 136-139, 168-170, 173-176, 215-251, 267-274, 284-294, 304-307, 312-317, 324-411, 419-450 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_differentiable_functions.py 351 317 10% 31-160, 163-165, 168-170, 173-175, 178-181, 184-187, 190-193, 196-200, 223-420, 423-425, 428-429, 432-434, 437-439, 442-444, 447-449, 452-454, 458-461, 472-489, 492-494, 497-501, 504-505, 508-510, 521-528 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_differentialevolution.py 364 310 15% 294-308, 475-599, 607-637, 644-652, 666-687, 694, 702-704, 711, 730-849, 869-889, 894-908, 928, 948-959, 962, 965, 969-970, 974-975, 1011-1020, 1035-1144, 1150, 1154, 1158-1159, 1163-1195, 1199-1200, 1205-1206, 1211-1216, 1220-1224, 1228-1233, 1237-1242, 1249-1253, 1261-1262, 1265, 1294-1322, 1325, 1341-1346 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_dual_annealing.py 285 250 12% 55-71, 79-111, 115-127, 153-159, 166-195, 199-205, 209-210, 240-256, 259-277, 280-306, 315-355, 362-370, 373-374, 388-405, 409-425, 602-689 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_hessian_update_strategy.py 134 94 30% 52, 70, 87, 100, 136-145, 151-159, 162, 180-201, 217-220, 231-237, 279, 282-288, 311-312, 329-330, 334-375, 407-408, 412-430 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_linprog.py 78 65 17% 78-110, 155-161, 510-581 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_linprog_ip.py 247 217 12% 84-119, 189-329, 345-349, 368-375, 399-412, 427-432, 447-453, 471-502, 534-544, 698-822, 1083-1127 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_linprog_rs.py 190 171 10% 47-99, 108-134, 161-237, 249-269, 277, 285-288, 295-310, 327-402, 522-558 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_linprog_simplex.py 107 98 8% 89-95, 154-166, 212-229, 355-435, 591-659 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_linprog_util.py 489 470 4% 57-68, 92-99, 118-121, 183-386, 497-778, 873-881, 971-1085, 1092, 1100-1130, 1138-1145, 1170-1173, 1241-1293, 1350-1396, 1473-1485 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_lsap.py 20 17 15% 79-105 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_lsq/__init__.py 4 0 100% /usr/local/lib/python3.8/dist-packages/scipy/optimize/_lsq/bvls.py 116 109 6% 13-16, 20-177 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_lsq/common.py 295 261 12% 36-56, 108-170, 196-221, 235-247, 284-301, 316-324, 350-363, 371, 392-400, 418-439, 448-466, 499-510, 515-541, 548, 555-565, 571, 578-588, 597-600, 605-615, 620-631, 637-648, 660-671, 679-689, 697-707, 712-722, 730-736 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_lsq/dogbox.py 149 138 7% 65-77, 94-106, 125-149, 154-330 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_lsq/least_squares.py 255 229 10% 43-92, 98-105, 109-126, 130-149, 153-162, 169-177, 181-186, 190-195, 199-204, 212-237, 748-940 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_lsq/lsq_linear.py 82 70 15% 16-24, 218-317 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_lsq/trf.py 290 278 4% 121-126, 133-205, 210-402, 410-564 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_lsq/trf_linear.py 144 132 8% 53-69, 74-90, 95-142, 147-248 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_minimize.py 176 155 12% 479-636, 756-794, 799-806, 811-829 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_numdiff.py 254 237 7% 46-91, 100-103, 107-114, 147-175, 330-398, 404-441, 445-481, 486-561, 625-639 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_remove_redundancy.py 147 136 7% 30-31, 53-54, 83-92, 96-104, 139-230, 266-357, 393-449 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_root.py 89 69 22% 153-203, 207-208, 246-257, 266-305, 369, 434, 476, 513, 550, 590, 654 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_root_scalar.py 124 104 16% 30-33, 38-43, 47-49, 53-55, 58, 181-287, 306, 325, 343, 366, 392, 423, 442, 461 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_shgo.py 657 595 9% 417-447, 456-655, 673-707, 721-737, 744-757, 762-778, 782-789, 793-795, 799-800, 803-804, 814-835, 838-845, 855-868, 871-879, 888-899, 907-910, 917-955, 974-1020, 1024-1028, 1031-1034, 1044-1052, 1070-1086, 1102-1104, 1124-1182, 1190-1199, 1203-1206, 1225-1240, 1245-1282, 1290-1292, 1302-1357, 1366-1375, 1384-1390, 1395-1403, 1407-1409, 1415-1421, 1431-1458, 1466-1472, 1476-1508, 1514-1531, 1534-1542, 1550, 1555-1568, 1574-1596, 1601-1605, 1610-1617, 1620-1628, 1631-1645, 1651-1671 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_shgo_lib/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/scipy/optimize/_shgo_lib/sobol_seq.py 122 114 7% 30-40, 53-58, 97-102, 140-145, 197-372 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_shgo_lib/triangulation.py 359 321 11% 8-46, 49, 56-85, 89-115, 119-141, 146-159, 163-174, 182, 195-225, 231-243, 258-298, 315-362, 372-451, 456-464, 467, 470-471, 477-480, 487-490, 497, 503-504, 513-517, 528-530, 536-569, 572, 575-585, 588-592, 596-600, 603-609, 616-626, 629-661 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_spectral.py 106 93 12% 66-164, 207-238, 245-251, 255, 259 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trlib/__init__.py 6 3 50% 7-12 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion.py 135 114 16% 25-35, 38, 43-45, 50-52, 57-59, 62-65, 70-72, 80-95, 98, 133-266 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_constr/__init__.py 2 0 100% /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_constr/canonical_constraint.py 253 234 8% 43-48, 53-69, 78-91, 101-149, 153-181, 185-221, 225-261, 265-327, 337-390 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_constr/equality_constrained_sqp.py 105 96 9% 14-15, 50-218 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_constr/minimize_trustregion_constr.py 175 152 13% 29-30, 33-36, 46-48, 51-57, 62-100, 107-112, 314-544 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_constr/projections.py 164 145 12% 10, 41-55, 62-90, 96-172, 179-233, 240-287, 364-406 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_constr/qp_subproblem.py 215 201 7% 45-63, 99-149, 189-234, 286-303, 308, 313, 364-409, 492-638 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_constr/report.py 32 10 69% 11-16, 23-28, 32 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_constr/tr_interior_point.py 148 124 16% 38-57, 60-61, 64, 67, 80-86, 93-96, 100, 108-114, 130-136, 140, 143-163, 179-195, 199-205, 209-221, 226-240, 251-264, 287-347 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_dogleg.py 40 30 25% 31-35, 47-51, 57-62, 98-124 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_exact.py 139 124 11% 35-41, 80-122, 137-143, 173-185, 218-254, 264-285, 290-432 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_krylov.py 11 7 36% 22-59 /usr/local/lib/python3.8/dist-packages/scipy/optimize/_trustregion_ncg.py 51 42 18% 33-39, 71-128 /usr/local/lib/python3.8/dist-packages/scipy/optimize/cobyla.py 72 60 17% 139-170, 196-258 /usr/local/lib/python3.8/dist-packages/scipy/optimize/lbfgsb.py 136 123 10% 174-208, 265-380, 412-422, 440-456, 468-478 /usr/local/lib/python3.8/dist-packages/scipy/optimize/linesearch.py 320 299 7% 69-103, 150-186, 267-322, 384-468, 481-502, 512-523, 532-603, 644-659, 666-668, 685-726, 773-802, 852-883 /usr/local/lib/python3.8/dist-packages/scipy/optimize/minpack.py 284 255 10% 26-45, 139-165, 206-259, 384-457, 461-478, 482-491, 495-508, 683-813, 821-844, 848, 852, 856-870, 914-916 /usr/local/lib/python3.8/dist-packages/scipy/optimize/nnls.py 21 16 24% 60-82 /usr/local/lib/python3.8/dist-packages/scipy/optimize/nonlin.py 628 491 22% 139, 144-147, 152-154, 158-160, 269-367, 375-415, 434-453, 456-472, 521-530, 533, 536, 539, 542-547, 552-558, 562, 566, 573-658, 667-678, 681, 684-688, 703-708, 712-718, 723-746, 750-752, 756-758, 762-764, 768-770, 773-781, 784-790, 794-797, 803-808, 814-819, 850-884, 951-973, 977-978, 981, 984-988, 991, 994, 997, 1000-1006, 1046-1051, 1115-1121, 1124-1144, 1147-1167, 1170-1192, 1225-1226, 1229-1230, 1233, 1236, 1239, 1242, 1245, 1248, 1275-1276, 1279, 1282, 1285, 1288, 1291, 1294, 1325-1328, 1331-1332, 1335, 1338, 1341, 1344, 1347, 1350-1353, 1438-1476, 1479-1481, 1484-1491, 1494-1498, 1501-1508, 1511-1524 /usr/local/lib/python3.8/dist-packages/scipy/optimize/optimize.py 1239 1166 6% 59-61, 64-67, 70-74, 115-118, 124-129, 132, 140-145, 152, 159-164, 197-200, 229-238, 270-277, 310-317, 321-329, 435-453, 498-682, 690-707, 765, 809-813, 818-820, 841-869, 945-964, 990-1098, 1253-1271, 1297-1406, 1500-1519, 1545-1672, 1742-1750, 1771-1894, 1901-1910, 1914, 1918-1945, 1949-2053, 2056-2059, 2132-2138, 2158-2171, 2234-2239, 2253-2315, 2352-2417, 2426-2430, 2550-2570, 2599-2712, 2716-2728, 2903-2985, 2993-2994, 2998, 3069-3166, 3170-3242, 3246 /usr/local/lib/python3.8/dist-packages/scipy/optimize/slsqp.py 190 178 6% 57-66, 181-212, 237-475, 483-531 /usr/local/lib/python3.8/dist-packages/scipy/optimize/tnc.py 102 76 25% 243-277, 342-413, 420-441 /usr/local/lib/python3.8/dist-packages/scipy/optimize/zeros.py 471 417 11% 54-62, 65-68, 73-81, 86-93, 266-365, 377-469, 546-554, 643-651, 773-781, 878-886, 896-899, 904-908, 919-927, 932-937, 949-972, 980-992, 1002, 1013-1037, 1048-1064, 1067-1077, 1081-1085, 1089, 1092, 1096-1123, 1127-1132, 1139-1213, 1218-1244, 1353-1375 /usr/local/lib/python3.8/dist-packages/scipy/signal/__init__.py 44 2 95% 330, 343 /usr/local/lib/python3.8/dist-packages/scipy/signal/_arraytools.py 49 41 16% 43-46, 54, 92-106, 143-155, 196-209, 237-243 /usr/local/lib/python3.8/dist-packages/scipy/signal/_max_len_seq.py 31 25 19% 104-137 /usr/local/lib/python3.8/dist-packages/scipy/signal/_peak_finding.py 225 201 11% 66-81, 138, 194, 248-250, 264-267, 281-293, 307-319, 459-462, 584-590, 625-640, 673-678, 713-723, 935-1006, 1055-1126, 1164-1190, 1283-1299 /usr/local/lib/python3.8/dist-packages/scipy/signal/_savitzky_golay.py 81 70 14% 98-141, 153-165, 179-209, 219-223, 328-353 /usr/local/lib/python3.8/dist-packages/scipy/signal/_upfirdn.py 40 30 25% 59-63, 67-69, 75-86, 90-100, 207-210 /usr/local/lib/python3.8/dist-packages/scipy/signal/bsplines.py 202 177 12% 19, 28-43, 60-114, 125-129, 148-149, 157-167, 175-185, 189-193, 197, 202-206, 210-237, 241-252, 256-267, 292-295, 319-322, 337-358, 373-394 /usr/local/lib/python3.8/dist-packages/scipy/signal/filter_design.py 1094 1014 7% 47-56, 94-117, 180-193, 255-272, 424-477, 562-583, 662-693, 698-706, 821-828, 881-932, 987-1000, 1064-1071, 1095-1130, 1168, 1193-1200, 1230-1240, 1245-1250, 1421-1515, 1539-1561, 1592-1632, 1691-1704, 1765-1787, 1851-1876, 1938-1965, 2017-2046, 2155-2175, 2294-2386, 2393-2398, 2457-2474, 2520-2534, 2583-2600, 2652-2679, 2731-2759, 2866, 2983, 3094, 3218, 3380, 3385, 3389, 3421-3445, 3525-3615, 3693-3753, 3833-3915, 3993-4054, 4067-4074, 4091-4112, 4129-4154, 4161-4163, 4167-4179, 4201-4263, 4285-4288, 4318-4332, 4340-4357, 4371-4396, 4404-4435, 4449-4463, 4540-4568, 4648, 4728, 4764-4803 /usr/local/lib/python3.8/dist-packages/scipy/signal/fir_filter_design.py 272 250 8% 26-32, 79-85, 127-128, 250-261, 389-482, 593-684, 836-855, 968-1068, 1082-1090, 1215-1265 /usr/local/lib/python3.8/dist-packages/scipy/signal/lti_conversion.py 160 142 11% 76-114, 118-121, 125-126, 130-133, 137-139, 143-148, 176-195, 256-284, 304, 334, 405-504 /usr/local/lib/python3.8/dist-packages/scipy/signal/ltisys.py 919 757 18% 54-58, 66-70, 75, 79-82, 87, 92, 103-106, 117-120, 131-134, 206-221, 229, 236, 243, 250, 274, 284, 295, 383-398, 406-409, 414, 418, 425, 432, 439, 468, 479, 561-578, 583-592, 596, 606, 610-617, 622, 626, 638-639, 651, 663, 676, 697-702, 722-727, 800, 940-958, 963-972, 976, 987, 991-998, 1003, 1007, 1012, 1016, 1028-1030, 1042, 1055, 1067, 1131, 1207-1208, 1304-1317, 1322-1333, 1337, 1347, 1365-1404, 1411-1421, 1428, 1434-1473, 1479-1482, 1485-1488, 1491-1494, 1501-1508, 1513, 1517, 1522, 1526-1527, 1532, 1536-1537, 1542, 1546, 1558-1561, 1578, 1596, 1609, 1677, 1799-1853, 1861-1867, 1926-2032, 2058-2064, 2114-2133, 2200-2222, 2277-2292, 2358-2373, 2432-2437, 2494-2522, 2529, 2540-2580, 2590-2600, 2613-2636, 2655-2710, 2720-2763, 2777-2886, 2896-2912, 3095-3263, 3322-3379, 3431-3465, 3516-3550, 3615-3648, 3712-3722 /usr/local/lib/python3.8/dist-packages/scipy/signal/signaltools.py 1148 1072 7% 27, 47-50, 55-58, 77-93, 197-259, 265-270, 305-331, 365-391, 419-428, 523-544, 572-655, 736-860, 876-881, 889-892, 904-935, 963-977, 984-985, 996-1002, 1019-1037, 1146-1174, 1267-1296, 1353-1359, 1394-1409, 1437-1460, 1537-1549, 1627-1644, 1681-1692, 1817-1885, 1928-1953, 1997-2009, 2098-2120, 2145-2180, 2208-2210, 2265-2297, 2356-2372, 2377-2397, 2401-2424, 2503-2539, 2598-2644, 2648-2675, 2733-2749, 2832-2924, 3054-3134, 3184-3212, 3254-3297, 3391-3433, 3489-3505, 3557-3684, 3844-3885, 3890-3920, 3924-3927, 4000-4039, 4130-4151, 4202-4245 /usr/local/lib/python3.8/dist-packages/scipy/signal/spectral.py 363 339 7% 142-158, 268-289, 452-457, 584-601, 734-771, 870-895, 996-1022, 1172-1178, 1348-1456, 1566-1576, 1669-1870, 1896-1920, 1959-1981, 2001-2002 /usr/local/lib/python3.8/dist-packages/scipy/signal/waveforms.py 120 107 11% 58-88, 139-162, 224-262, 427-430, 440-483, 577-580, 591-593, 669-681 /usr/local/lib/python3.8/dist-packages/scipy/signal/wavelets.py 136 123 10% 29-76, 90-92, 127-198, 253-261, 301-308, 384-388, 462-473 /usr/local/lib/python3.8/dist-packages/scipy/signal/windows/__init__.py 2 0 100% /usr/local/lib/python3.8/dist-packages/scipy/signal/windows/windows.py 289 243 16% 21-23, 28-31, 36-39, 112-121, 168-174, 226-238, 290-302, 349-357, 442, 501, 548, 609-610, 700-708, 790, 795, 856-878, 925-933, 1020, 1098, 1207-1216, 1271-1279, 1342-1349, 1438-1476, 1545-1563, 1616-1622, 1698-1710, 1876-1970, 1975-1982, 2095-2124 /usr/local/lib/python3.8/dist-packages/scipy/sparse/__init__.py 19 0 100% /usr/local/lib/python3.8/dist-packages/scipy/sparse/_index.py 221 190 14% 24-27, 35-75, 78-126, 129-150, 157-180, 185-191, 196-202, 205, 208, 211, 214, 217, 220, 223, 226, 229, 232, 235, 238, 242-244, 252-283, 288-322, 326-328 /usr/local/lib/python3.8/dist-packages/scipy/sparse/_matrix_io.py 42 32 24% 16, 63-80, 131-156 /usr/local/lib/python3.8/dist-packages/scipy/sparse/base.py 455 344 24% 71-75, 81-82, 86, 123-131, 157, 182-189, 194-203, 207-208, 212, 223, 239, 250, 254, 257-258, 263-281, 284-287, 295, 313-328, 340, 344, 348, 363, 367, 370, 373, 376, 379, 382, 385, 388, 391, 394, 397, 400, 403, 407, 410-424, 427, 430-443, 446-455, 466-530, 534, 537, 540, 543, 546-554, 561-564, 567-570, 577-617, 620, 624, 628, 632, 635, 638, 641, 644, 647, 650, 653-675, 678-691, 718, 736-741, 744, 756, 759, 762, 780-782, 791-799, 808-816, 851, 883, 894, 902, 910, 918, 926, 937, 945, 953, 993-1025, 1064-1097, 1124, 1146-1149, 1152-1176, 1179-1189 /usr/local/lib/python3.8/dist-packages/scipy/sparse/bsr.py 315 266 16% 123-214, 225-271, 279, 283-287, 292-293, 299-308, 317, 320, 330, 336, 339, 342-351, 354-364, 367-421, 436-441, 444-463, 468, 479-505, 508, 513-534, 546-561, 568-594, 599-607, 613-627, 635-676, 684-688, 722 /usr/local/lib/python3.8/dist-packages/scipy/sparse/compressed.py 737 654 11% 31-108, 111-123, 130-136, 148-195, 212-215, 219-248, 252-279, 283-313, 316, 322, 328, 334, 344-352, 355, 358, 365-458, 465-475, 478-489, 492-528, 531-539, 548-568, 571, 577, 592-611, 630-635, 642-647, 650-653, 657-668, 672-673, 678-698, 704-730, 736-758, 764-775, 782-793, 797-798, 801-802, 806-823, 826-853, 856-872, 880-911, 918-931, 942-1003, 1010-1017, 1023-1037, 1050-1053, 1068-1074, 1077-1079, 1089-1098, 1110-1113, 1116, 1123-1125, 1135-1138, 1143-1153, 1156-1187, 1201-1207, 1212-1242, 1248-1269, 1273-1290 /usr/local/lib/python3.8/dist-packages/scipy/sparse/construct.py 232 206 11% 62, 138-188, 218, 252-273, 311-355, 384-398, 406-431, 465, 499, 545-623, 668-677, 750-793, 842 /usr/local/lib/python3.8/dist-packages/scipy/sparse/coo.py 294 251 15% 129-198, 201-236, 242-263, 271-291, 294-300, 306-317, 323-330, 352-372, 394-414, 417-420, 425-443, 448-454, 459-475, 480-513, 521-525, 533-537, 541-554, 561-564, 571-579, 583-586, 589-593, 619 /usr/local/lib/python3.8/dist-packages/scipy/sparse/csc.py 87 58 33% 111-119, 125-126, 129-132, 137-155, 164-180, 188-194, 200-206, 209, 212-214, 217-219, 222, 225, 228, 235, 261 /usr/local/lib/python3.8/dist-packages/scipy/sparse/csgraph/__init__.py 14 0 100% /usr/local/lib/python3.8/dist-packages/scipy/sparse/csgraph/_laplacian.py 51 44 14% 69-81, 85, 89-111, 115-128 /usr/local/lib/python3.8/dist-packages/scipy/sparse/csgraph/_validation.py 31 25 19% 17-58 /usr/local/lib/python3.8/dist-packages/scipy/sparse/csr.py 135 103 24% 129-137, 143-156, 161-164, 169-186, 191-222, 231, 234-242, 248-256, 263-271, 275, 278-307, 311-313, 316, 319, 322-325, 351 /usr/local/lib/python3.8/dist-packages/scipy/sparse/data.py 184 138 25% 23, 26, 29, 33-35, 38, 41, 44, 47, 50-53, 56-60, 63-68, 71-79, 84-89, 94, 99, 113-119, 126, 135-136, 148-156, 166-187, 191-215, 218-252, 255-289, 321, 353, 376, 399 /usr/local/lib/python3.8/dist-packages/scipy/sparse/dia.py 224 188 16% 79-146, 149-150, 158-164, 167-168, 171-181, 187-225, 230-241, 244, 247-276, 279-282, 287-305, 311-318, 323-343, 349-365, 374-377, 380-392, 420 /usr/local/lib/python3.8/dist-packages/scipy/sparse/dok.py 275 213 23% 23, 79-111, 115, 122, 125-128, 133-136, 139, 145, 151-158, 161, 164, 167, 170-191, 194, 197, 200-201, 204-205, 209-216, 220-227, 230-234, 237-246, 249-277, 280-301, 304-309, 312-316, 320-323, 327-332, 335-338, 341-346, 349-352, 358, 365-374, 380-384, 387-389, 394-404, 409-411, 416, 421-429, 457 /usr/local/lib/python3.8/dist-packages/scipy/sparse/extract.py 22 14 36% 38-42, 101-103, 162-164, 168-171 /usr/local/lib/python3.8/dist-packages/scipy/sparse/lil.py 291 232 20% 89-132, 135-136, 139-140, 143-147, 150-154, 160-172, 175, 181-185, 190-193, 198-206, 210-216, 220-226, 229-231, 234-235, 238, 241, 244-245, 248, 251-252, 255-256, 260-261, 265-271, 289-300, 303, 307-308, 314-324, 328-336, 339-350, 353-360, 363-369, 374-401, 406-426, 431-435, 440, 445-448, 454-484, 512-527, 553 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/__init__.py 13 0 100% /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/_expm_multiply.py 255 225 12% 18-23, 28-33, 38-43, 48-55, 140-144, 172-197, 204-223, 313, 342-346, 352, 358-360, 366-369, 375, 399, 414-417, 455-475, 506-511, 556-629, 639-648, 655-677, 684-713 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/_norm.py 70 63 10% 15-19, 110-184 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/_onenormest.py 199 177 11% 86-119, 130-139, 154-157, 162, 166-174, 178-180, 187-190, 194-197, 204-211, 215, 219, 261-322, 366-468 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/dsolve/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/dsolve/_add_newdocs.py 9 0 100% /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/dsolve/linsolve.py 197 173 12% 56-59, 63-82, 132-233, 302-324, 386-410, 442-469, 528-607 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/eigen/__init__.py 7 0 100% /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/eigen/arpack/__init__.py 2 0 100% /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/eigen/arpack/arpack.py 726 642 12% 280-281, 297-299, 307, 313-364, 367-377, 435-533, 536-573, 576-595, 636-719, 722-759, 762-896, 900-904, 914-917, 922-927, 937-939, 942, 949-951, 961-974, 977-982, 992-1020, 1023-1028, 1032, 1037-1044, 1048-1054, 1058-1089, 1251-1349, 1554-1689, 1694-1713, 1717, 1721, 1804-1910 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/eigen/lobpcg/__init__.py 6 0 100% /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/eigen/lobpcg/lobpcg.py 323 310 4% 34-44, 52-57, 64-72, 77-79, 84-114, 119-125, 287-711 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/interface.py 346 245 29% 140-152, 160-168, 173-175, 184, 196, 222-243, 269-290, 294-298, 324-339, 364-377, 381-384, 387, 390, 407-419, 423-426, 429-432, 435-438, 441-444, 447-450, 453, 456, 459-465, 481, 491, 497, 501, 509-518, 521-524, 527, 530-533, 536-539, 542, 553-556, 559, 562, 565, 568, 573-576, 580, 583, 587, 590, 593-598, 603-610, 613, 616, 619, 622, 625-626, 631-639, 642, 645, 648, 651, 654-655, 660-666, 669, 672, 675, 678, 681-682, 687-695, 698-701, 704, 707, 710, 713, 716-717, 722-725, 728, 731-733, 737-740, 744, 747, 752, 755, 758, 761, 764, 767, 795-823 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/isolve/__init__.py 11 0 100% /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/isolve/_gcrotmk.py 192 182 5% 66-182, 267-490 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/isolve/iterative.py 421 386 8% 73-77, 97-118, 137-198, 209-265, 276-337, 347-414, 514-647, 717-802 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/isolve/lgmres.py 69 59 14% 128-235 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/isolve/lsmr.py 185 177 4% 197-482 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/isolve/lsqr.py 200 192 4% 81-95, 311-570 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/isolve/minres.py 203 196 3% 71-343, 347-363 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/isolve/utils.py 56 46 18% 23-27, 31, 65-123 /usr/local/lib/python3.8/dist-packages/scipy/sparse/linalg/matfuncs.py 354 279 21% 77-82, 103-115, 120-130, 155-173, 179-188, 191-193, 196-200, 203-205, 209, 218-235, 238-240, 243-246, 249-251, 255-256, 296, 338, 367-383, 387-390, 394-397, 401-404, 408-411, 415-418, 422-424, 428-430, 434-436, 440-442, 446-454, 458-466, 470-478, 482-490, 493-498, 501-506, 509-514, 517-525, 528-547, 595, 603-677, 700-709, 736-740, 762-764, 783-813, 833-855 /usr/local/lib/python3.8/dist-packages/scipy/sparse/sputils.py 176 146 17% 42-53, 58-63, 70, 80-90, 94, 105-118, 143-171, 176-180, 185, 194-207, 215-225, 229, 235, 241, 245-264, 269-314, 326-331, 338-339, 346-349, 353-356, 360-363 /usr/local/lib/python3.8/dist-packages/scipy/spatial/__init__.py 13 0 100% /usr/local/lib/python3.8/dist-packages/scipy/spatial/_plotutils.py 78 65 17% 11-27, 31-35, 81-90, 136-148, 212-264 /usr/local/lib/python3.8/dist-packages/scipy/spatial/_procrustes.py 25 20 20% 101-132 /usr/local/lib/python3.8/dist-packages/scipy/spatial/_spherical_voronoi.py 68 57 16% 133-166, 171-206, 217-243, 273-277 /usr/local/lib/python3.8/dist-packages/scipy/spatial/distance.py 633 503 21% 135-165, 170-172, 176-178, 182-183, 194-195, 200-220, 224-240, 244-259, 263-269, 273-286, 290-292, 307-309, 314-329, 334-339, 343-346, 350-357, 451-457, 508-524, 580-581, 620, 661-674, 708-721, 766, 813-820, 883-894, 941-950, 985-991, 1031-1037, 1079-1084, 1122-1130, 1170-1178, 1221-1236, 1286-1296, 1337-1342, 1353, 1397-1412, 1457-1462, 1507-1519, 1565-1578, 1624-1638, 1718, 1722, 1724-1731, 1999, 2006-2012, 2017, 2023, 2027, 2031, 2039-2050, 2069-2094, 2149-2212, 2254-2302, 2334-2339, 2344-2358, 2378-2380, 2403, 2407, 2708-2793 /usr/local/lib/python3.8/dist-packages/scipy/spatial/kdtree.py 419 379 10% 39-55, 78-83, 93-95, 98, 102, 120-126, 140, 154, 168, 182, 243-251, 256, 259, 262, 265, 268, 272-273, 277-281, 284-323, 329-407, 492-547, 550-572, 625-636, 663-705, 731-812, 842-889, 912-942, 978-996 /usr/local/lib/python3.8/dist-packages/scipy/spatial/transform/__init__.py 7 0 100% /usr/local/lib/python3.8/dist-packages/scipy/spatial/transform/_rotation_groups.py 56 48 14% 6-58, 62-76, 80-90, 94-99, 103-105, 109-140 /usr/local/lib/python3.8/dist-packages/scipy/spatial/transform/_rotation_spline.py 176 159 10% 18-25, 30, 48-65, 83-104, 124-151, 168, 188, 220-248, 331-361, 364-404, 424-456 /usr/local/lib/python3.8/dist-packages/scipy/spatial/transform/rotation.py 470 416 11% 15-17, 29-142, 146-150, 154-158, 162-173, 369-394, 407, 474-479, 568-612, 618, 674-707, 803-860, 907-910, 964-999, 1004, 1052-1073, 1159-1179, 1298-1329, 1397-1406, 1439-1443, 1467-1475, 1510-1527, 1560-1617, 1655, 1703, 1722-1727, 1768-1775, 1783-1838, 1915-1968, 2049-2070, 2090-2114 /usr/local/lib/python3.8/dist-packages/scipy/special/__init__.py 17 0 100% /usr/local/lib/python3.8/dist-packages/scipy/special/_basic.py 524 449 14% 100-112, 179-213, 250-254, 279-285, 305, 325, 345, 365, 397-401, 433-437, 469-473, 481-487, 515-519, 547-551, 602-606, 635-639, 667-671, 699-703, 747-755, 799-807, 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/usr/local/lib/python3.8/dist-packages/scipy/stats/distributions.py 9 0 100% /usr/local/lib/python3.8/dist-packages/scipy/stats/kde.py 183 151 17% 194-209, 231-265, 293-320, 344-355, 375-388, 411-438, 465-475, 485, 495, 548-565, 571-581, 593, 600-632, 636-640, 644-648 /usr/local/lib/python3.8/dist-packages/scipy/stats/morestats.py 829 760 8% 127-136, 194-211, 278-306, 349-358, 416-421, 440-452, 457-471, 585-627, 705-718, 797-812, 894-910, 916-945, 1034-1059, 1129-1165, 1173-1202, 1270, 1345-1363, 1370-1385, 1470-1481, 1533-1536, 1606, 1661-1678, 1771-1825, 1853-1869, 1897-1906, 2014-2070, 2113-2166, 2225-2247, 2307-2371, 2421-2465, 2472-2475, 2548-2600, 2670-2725, 2847-2938, 3080-3162, 3167-3186, 3225-3255, 3295-3307, 3349-3361 /usr/local/lib/python3.8/dist-packages/scipy/stats/mstats.py 4 0 100% /usr/local/lib/python3.8/dist-packages/scipy/stats/mstats_basic.py 947 845 11% 61-67, 71-79, 83-89, 116-128, 151-160, 196-211, 235-259, 299-324, 328-330, 335, 373-399, 459-528, 569-663, 676-727, 759-782, 798-828, 870-884, 924-938, 942-949, 982-996, 1037-1066, 1096-1114, 1144-1165, 1214-1229, 1258-1282, 1322-1343, 1372-1410, 1465-1468, 1500, 1535-1543, 1556-1561, 1579-1586, 1604-1610, 1646-1690, 1718-1736, 1786, 1825-1831, 1876-1878, 1927-1929, 1967-1974, 2030-2071, 2101-2135, 2176-2177, 2205-2222, 2262-2283, 2343-2351, 2367-2381, 2411-2430, 2460-2490, 2521-2526, 2628-2654, 2664-2668, 2714-2720, 2736-2749, 2798-2801, 2824-2837, 2867-2888, 2931-2977 /usr/local/lib/python3.8/dist-packages/scipy/stats/mstats_extras.py 159 141 11% 62-103, 128-129, 156-190, 235-241, 260-286, 316-320, 346-371, 400-404, 429-444, 463-477 /usr/local/lib/python3.8/dist-packages/scipy/stats/stats.py 1635 1486 9% 172, 217-227, 231-245, 249-274, 328-339, 391-406, 459-503, 531-549, 594-599, 648-654, 706-717, 768-779, 828, 877-883, 950-970, 974-1021, 1064-1072, 1149-1175, 1259-1288, 1357-1374, 1437-1463, 1520-1560, 1625-1637, 1681-1693, 1738-1740, 1805-1820, 1825-1864, 1934-1954, 2008-2036, 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/usr/local/lib/python3.8/dist-packages/skimage/_shared/_warnings.py 54 42 22% 46-70, 109-145 /usr/local/lib/python3.8/dist-packages/skimage/_shared/fft.py 9 4 56% 12-15 /usr/local/lib/python3.8/dist-packages/skimage/_shared/utils.py 123 45 63% 63-66, 99, 104-114, 154-163, 179, 235-236, 242-243, 251-253, 270-278, 298-304, 333-334, 362, 365, 369 /usr/local/lib/python3.8/dist-packages/skimage/_shared/version_requirements.py 60 51 15% 6, 10-12, 48-62, 67-69, 95-117, 141-155, 177-179 /usr/local/lib/python3.8/dist-packages/skimage/color/__init__.py 4 0 100% /usr/local/lib/python3.8/dist-packages/skimage/color/adapt_rgb.py 25 11 56% 19, 37-40, 58-62, 77-79 /usr/local/lib/python3.8/dist-packages/skimage/color/colorconv.py 355 254 28% 79-82, 124-140, 147-153, 188-212, 249-294, 331-348, 486-490, 596-598, 638-643, 681-685, 717, 750, 793-811, 816-818, 840-855, 880-920, 925-927, 974-993, 1034-1056, 1092, 1128, 1176-1213, 1252-1280, 1311, 1336, 1371, 1407, 1459-1462, 1516-1521, 1559-1563, 1571-1573, 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/usr/local/lib/python3.8/dist-packages/skimage/draw/_random_shapes.py 119 107 10% 40-62, 96-119, 153-172, 208-241, 283-289, 378-434 /usr/local/lib/python3.8/dist-packages/skimage/draw/draw.py 112 92 18% 35-43, 114-143, 177-181, 225-226, 277-305, 345-369, 411, 453, 500, 563, 624, 695, 752, 840-848, 912-921, 936-949 /usr/local/lib/python3.8/dist-packages/skimage/draw/draw3d.py 35 31 11% 33-63, 88-114 /usr/local/lib/python3.8/dist-packages/skimage/draw/draw_nd.py 19 16 16% 45-51, 97-108 /usr/local/lib/python3.8/dist-packages/skimage/exposure/__init__.py 4 0 100% /usr/local/lib/python3.8/dist-packages/skimage/exposure/_adapthist.py 106 95 10% 78-98, 126-233, 256-287, 312-317 /usr/local/lib/python3.8/dist-packages/skimage/exposure/exposure.py 138 117 15% 23-35, 61-74, 122-144, 181-184, 217-223, 254-266, 292-307, 405-428, 433-434, 485-494, 528-537, 577-586, 629-640 /usr/local/lib/python3.8/dist-packages/skimage/exposure/histogram_matching.py 20 17 15% 9-19, 53-70 /usr/local/lib/python3.8/dist-packages/skimage/feature/__init__.py 25 4 84% 35-36, 46-47 /usr/local/lib/python3.8/dist-packages/skimage/feature/_canny.py 108 100 7% 45-50, 157-297 /usr/local/lib/python3.8/dist-packages/skimage/feature/_daisy.py 97 90 7% 97-222 /usr/local/lib/python3.8/dist-packages/skimage/feature/_hog.py 82 77 6% 6-19, 34-43, 142-295 /usr/local/lib/python3.8/dist-packages/skimage/feature/_orb_descriptor_positions.py 6 0 100% /usr/local/lib/python3.8/dist-packages/skimage/feature/blob.py 148 130 12% 38-52, 79-81, 111-141, 168-185, 192-210, 312-373, 468-533, 618-644 /usr/local/lib/python3.8/dist-packages/skimage/feature/brief.py 41 33 20% 119-130, 143-185 /usr/local/lib/python3.8/dist-packages/skimage/feature/censure.py 100 81 19% 31-76, 80-90, 94-102, 106-107, 201-216, 242-296 /usr/local/lib/python3.8/dist-packages/skimage/feature/corner.py 200 168 16% 41-44, 95-104, 159-173, 191-197, 236-242, 246-248, 285, 317-325, 394-397, 433-445, 513-525, 583-588, 657-672, 733-737, 801-916, 981-1024, 1071, 1138 /usr/local/lib/python3.8/dist-packages/skimage/feature/haar.py 58 44 24% 21-33, 77-84, 195-219, 290-321 /usr/local/lib/python3.8/dist-packages/skimage/feature/match.py 36 33 8% 53-97 /usr/local/lib/python3.8/dist-packages/skimage/feature/orb.py 132 113 14% 120-131, 134-135, 140-161, 172-210, 213-222, 244-276, 290-348 /usr/local/lib/python3.8/dist-packages/skimage/feature/peak.py 133 124 7% 12-20, 28-40, 48-53, 162-254, 285-357 /usr/local/lib/python3.8/dist-packages/skimage/feature/template.py 59 53 10% 9-17, 22-28, 113-179 /usr/local/lib/python3.8/dist-packages/skimage/feature/texture.py 115 104 10% 106-155, 217-278, 326-337, 381-383, 444-493 /usr/local/lib/python3.8/dist-packages/skimage/feature/util.py 64 52 19% 10, 21, 27, 40, 77-135, 141-143, 166-174 /usr/local/lib/python3.8/dist-packages/skimage/filters/__init__.py 12 0 100% /usr/local/lib/python3.8/dist-packages/skimage/filters/_gabor.py 28 21 25% 10-12, 76-95, 170-177 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/converters/call_trees.py 97 10 90% 102-106, 136, 198-207, 211 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/converters/conditional_expressions.py 12 1 92% 29 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/converters/continue_statements.py 91 46 49% 34, 62-74, 79-93, 97-115, 124-128, 131-136, 149-154, 157-158 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/converters/control_flow.py 208 86 59% 126-128, 144-155, 160-167, 184-195, 200-203, 236, 343-353, 357-378, 381-396, 399-432, 447-510 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/converters/directives.py 92 39 58% 67-87, 94-101, 104-115, 139-140, 153-154, 156-157, 164-168, 171, 174 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/converters/function_scopes.py 57 8 86% 70-88 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/converters/lists.py 100 72 28% 46, 53-57, 60-65, 90-107, 110-123, 130-148, 151-180, 190-199, 202, 208-211, 214-217, 220-223, 226-229, 232-234, 238 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/converters/logical_expressions.py 66 23 65% 56-59, 72-77, 90-112, 119 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/converters/return_statements.py 187 49 74% 87, 99-102, 105-109, 122-126, 130-131, 144, 147, 166, 177, 258-266, 282-293, 296-315, 323-327, 330-331, 376 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/converters/slices.py 35 22 37% 37-45, 49-56, 59-80, 85 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/core/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/core/ag_ctx.py 37 3 92% 58, 70, 73 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/core/config.py 9 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/core/config_lib.py 28 3 89% 48, 60, 64 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/core/converter.py 125 24 81% 131, 136-138, 171, 187, 310-335, 340 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/core/function_wrappers.py 59 20 66% 55, 60-61, 66-68, 74, 76, 83, 85, 90-101, 107-108 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/core/naming.py 64 19 70% 62, 72-73, 79-88, 98-99, 110-113, 117-118 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/core/unsupported_features_checker.py 25 9 64% 35, 40-43, 46-49, 54, 57 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/impl/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/impl/api.py 290 117 60% 55, 78-120, 146-147, 189, 206, 212-214, 218, 263-267, 280-287, 305, 308-309, 319-333, 343, 355, 362, 374, 413, 421-422, 425-426, 448, 450, 452, 459-464, 467-468, 481-482, 488-489, 499, 511, 514-522, 526-528, 532-534, 541-580, 588-590, 655-665, 732-734, 785-788, 831-836 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/impl/conversion.py 322 94 71% 87, 117, 134, 151, 210, 308-310, 345, 350, 355, 388, 397-398, 406-410, 418-419, 440, 443-444, 451-453, 459-465, 474-476, 482-484, 509, 514-521, 526, 528-529, 538-632, 638-639, 683-690, 700, 704, 715, 724, 751, 758-759 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/lang/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/lang/directives.py 16 7 56% 44-46, 95-98 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/lang/special_functions.py 33 20 39% 33-45, 53, 83-88, 113-119 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/operators/__init__.py 32 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/operators/control_flow.py 449 379 16% 109-119, 128-135, 142-191, 204-234, 241-263, 272-297, 341-372, 377-401, 407-439, 452-485, 497-526, 538-586, 606, 621-677, 684-704, 735-751, 765-769, 772, 775-776, 779-781, 785-804, 808-811, 815-825, 830-846, 851-856, 861-886, 923, 932-966, 991-999, 1005-1030 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/operators/data_structures.py 150 118 21% 45-54, 59-104, 109-163, 168, 189-199, 204-215, 220, 226-227, 257-269, 274-286, 291-295, 321-332, 337, 342-345, 351 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/operators/exceptions.py 24 14 42% 50-59, 77-80, 85-86 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/operators/logical.py 43 16 63% 29, 35, 47, 54, 64-67, 73, 78, 83-85, 90, 95, 100 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/operators/py_builtins.py 253 176 30% 62, 68-84, 92-99, 120-161, 165-169, 173, 177-180, 184, 188-190, 195-197, 201, 205-207, 211-217, 221-223, 227-233, 237, 241, 247-273, 278, 284-294, 298, 303-319, 324-326, 336-343, 347-351, 355-361, 365, 369, 373-375, 379, 383, 387-389, 393, 397, 401-403, 407, 411, 415-417, 428-436, 440, 444-446, 454-462, 466, 470-472, 477-497, 501-507, 514 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/operators/slices.py 55 31 44% 55-67, 72, 77-81, 86, 91-92, 97, 117-125, 130, 135, 140, 145-146 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/operators/special_values.py 27 10 63% 52, 55, 58-63, 66, 81, 93, 99 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/__init__.py 4 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/anno.py 59 7 88% 40, 107, 134-138 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/ast_util.py 214 117 45% 101-105, 108-109, 112-113, 130-132, 137-142, 149-151, 154-157, 160-161, 164-170, 173-206, 222-227, 262-275, 294, 299, 309, 315-316, 318-319, 325, 330, 341, 350-351, 354-359, 362-378, 381-388, 392-394 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/cfg.py 416 121 71% 86-93, 132, 136-143, 188, 200, 334-335, 340, 356, 418, 420-422, 455-456, 468-471, 507-511, 515-526, 566, 571-576, 580-586, 662, 665, 671, 695-700, 714-728, 758, 761, 770, 773, 779, 782, 785, 794, 797, 822-841, 844-871, 874, 877, 884, 886, 906-912, 928-931 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/error_utils.py 80 60 25% 84-123, 144-145, 148, 165-175, 179-209, 212-219, 222-225 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/errors.py 8 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/inspect_utils.py 144 65 55% 57, 64, 72-79, 89, 91, 171-173, 195-237, 246, 261-262, 292-293, 299, 304-336, 349 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/loader.py 34 2 94% 80, 88 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/origin_info.py 114 17 85% 77, 81-85, 117, 139-155, 180 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/parser.py 116 28 76% 63-67, 75-78, 81, 93, 149-178, 197-198, 213, 239, 258, 279 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/pretty_printer.py 87 69 21% 30-33, 36-38, 41, 44, 47, 50, 53, 56-57, 62-125, 129-135 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/qual_names.py 141 45 68% 48, 51, 58, 61, 70, 77, 80, 88, 96, 104, 107, 120-122, 134-138, 153-161, 173, 180, 187-191, 198, 203, 210-215, 244, 252, 265-267 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/static_analysis/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/static_analysis/activity.py 341 103 70% 121-124, 134-135, 189, 204-205, 244-249, 261-264, 269-274, 279, 281, 290-300, 324, 327, 330-332, 347, 352-361, 364, 372-382, 387, 400-404, 407, 445-456, 461-463, 466, 469, 472, 475, 481-497, 554-568, 571-579, 586 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/static_analysis/annos.py 17 1 94% 30 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/static_analysis/liveness.py 121 9 93% 78, 191-194, 204-206, 209-211 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/static_analysis/reaching_definitions.py 166 26 84% 56, 78, 109, 159-174, 249, 279-292, 295-296 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/templates.py 147 28 81% 69-70, 86-87, 90-93, 98-99, 158-167, 175, 179, 190-195, 260, 283, 289-292 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/pyct/transformer.py 134 27 80% 131, 258-259, 264-265, 322, 329, 382-395, 398-406, 415-418, 421, 443 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/utils/__init__.py 10 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/utils/ag_logging.py 47 19 60% 37, 87-88, 111, 117, 126-128, 132-135, 140-142, 146-149 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/utils/compat_util.py 14 3 79% 31, 37-38 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/utils/context_managers.py 18 10 44% 38-49 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/utils/misc.py 26 15 42% 42-52, 57-59, 63-69 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/utils/py_func.py 48 37 23% 64-132 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/utils/tensor_list.py 32 16 50% 28-40, 47-49, 52, 55-56, 59, 62, 65, 68 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/utils/tensors.py 16 3 81% 39, 47, 53 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/utils/testing.py 17 8 53% 30-37 /usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/utils/type_check.py 7 1 86% 33 /usr/local/lib/python3.8/dist-packages/tensorflow/python/client/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/client/client_lib.py 9 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/client/device_lib.py 15 8 47% 34-42 /usr/local/lib/python3.8/dist-packages/tensorflow/python/client/pywrap_tf_session.py 31 11 65% 53-59, 66-70 /usr/local/lib/python3.8/dist-packages/tensorflow/python/client/session.py 620 490 21% 57, 62, 66, 70, 74, 78, 84, 141, 192, 201, 206-207, 231, 245, 261-278, 301-316, 319, 322-326, 349-362, 374-379, 382, 386-396, 408-413, 416, 419-422, 434-437, 440, 443-446, 476-498, 501-502, 515, 523, 544-570, 582, 597-600, 604, 608, 612, 616, 619, 650-704, 731-742, 753-755, 759-772, 777, 787, 791, 846, 952-967, 1014, 1038-1089, 1095-1184, 1222-1309, 1340-1361, 1364-1384, 1387-1388, 1396-1411, 1417-1437, 1441, 1446, 1454-1462, 1467-1479, 1485-1487, 1504-1505, 1586-1589, 1592-1601, 1604-1641, 1669-1675, 1738-1769, 1773-1784 /usr/local/lib/python3.8/dist-packages/tensorflow/python/client/timeline.py 288 227 21% 60-62, 81-88, 97-102, 112-118, 132-135, 148-150, 163-165, 180-183, 198-200, 215-217, 230-232, 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/batching.py 107 64 40% 81-86, 133-136, 179-192, 243-255, 282-285, 293-310, 315, 323-361, 364, 368, 394-422, 426 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/cardinality.py 27 8 70% 66, 95-98, 105-114 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/counter.py 23 6 74% 51-54, 60, 66 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/distribute.py 70 45 36% 48-67, 71, 75, 88-119, 123, 130-133, 137, 150-170 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/distribute_options.py 22 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/enumerate_ops.py 12 3 75% 55-58 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/error_ops.py 17 6 65% 50-53, 61-66 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/stats_aggregator.py 23 6 74% 64-77, 128, 140 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/stats_ops.py 32 14 56% 44-48, 67-71, 90-94, 101-108 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/stats_options.py 13 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/take_while_ops.py 25 11 56% 33-49, 52, 69-72 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/threading_options.py 10 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/unique.py 20 8 60% 45-48, 56-65 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/experimental/ops/writers.py 22 7 68% 77-79, 105-114 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/ops/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/ops/dataset_ops.py 1381 743 46% 203, 227-240, 252-279, 285, 289, 293, 306-318, 329, 354, 357, 367, 385, 406, 420, 423-427, 475-484, 640, 658-665, 668-673, 676, 734, 736, 744, 785-823, 840-846, 913, 958, 987, 1057-1084, 1105, 1137-1138, 1198, 1248, 1267, 1286, 1354, 1387, 1489-1497, 1620-1623, 1748-1751, 1780, 1804-1810, 1889-1891, 1919-1996, 2023-2024, 2051, 2064-2078, 2087, 2103, 2106-2150, 2186, 2189-2204, 2218, 2232, 2246, 2254, 2260, 2265, 2278, 2283, 2289, 2294, 2298, 2302, 2307, 2311, 2315, 2320, 2324, 2328, 2332, 2336, 2345, 2351-2355, 2393-2401, 2412, 2421, 2427, 2446, 2450, 2454, 2459, 2463, 2469, 2476-2477, 2480, 2483, 2486, 2489, 2492, 2496, 2499, 2505-2524, 2540-2545, 2574-2579, 2597-2600, 2619, 2639, 2659, 2750, 2754, 2756, 2758, 2761, 2771-2774, 2782, 2858-2873, 2877, 2885-2902, 2906, 2913-2914, 2917, 2921, 2927-2929, 2933, 2948, 2961, 2985, 2988, 2992, 2995, 2999-3002, 3013, 3016, 3021-3023, 3026-3028, 3031, 3034, 3037, 3088-3092, 3097, 3104, 3144, 3168, 3172-3173, 3181-3202, 3226, 3230-3231, 3244, 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/data/ops/multi_device_iterator_ops.py 291 224 23% 43-140, 144, 148, 160-182, 186, 190, 196-208, 232-302, 306-320, 324-332, 335-340, 344-346, 350-365, 370, 381-385, 388-400, 412-414, 418, 421, 425-431, 435-437, 440, 450, 493-566, 574-582, 585, 588, 591-594, 597-602, 606, 610 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/ops/optional_ops.py 77 26 66% 59, 75, 85, 98-103, 121, 132-133, 136, 141-143, 155, 159, 170, 174, 177, 181, 184, 188, 192, 195, 198, 201 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/ops/readers.py 198 115 42% 46-64, 80-90, 114-127, 131, 160-172, 176, 188-190, 196, 200, 216-229, 233, 242-291, 295, 299, 302, 336-349, 356, 362, 366, 378-380, 390, 398, 402, 430-447, 451, 488-505, 509, 524-527, 533, 537, 545-547 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/util/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/util/convert.py 23 13 43% 30-34, 49-71 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/util/nest.py 101 35 65% 47-50, 69-70, 75, 88-89, 91, 176, 180, 186, 225-244, 297, 302, 308, 314-320, 462 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/util/options.py 59 30 49% 23, 38-43, 46-49, 52-55, 81-84, 115, 120, 124, 131-141 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/util/random_seed.py 21 10 52% 42-58 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/util/structure.py 178 72 60% 45, 51, 57, 64, 100-114, 146-172, 198, 252, 350, 394-404, 435-439, 445-450, 456-462, 476, 486, 489, 493, 496, 499, 502, 506, 509, 512, 515, 518, 521, 524 /usr/local/lib/python3.8/dist-packages/tensorflow/python/data/util/traverse.py 21 14 33% 39-56 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/__init__.py 25 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/cli/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/cli/analyzer_cli.py 581 520 10% 84-127, 151-158, 173-418, 444-458, 473-476, 479, 502-598, 616-639, 656-674, 690-738, 757-823, 834, 850-872, 891-908, 925-1050, 1069-1086, 1089-1095, 1107, 1113-1168, 1183-1240, 1244-1271, 1301-1361, 1404-1469, 1495-1520, 1533-1544, 1556-1579, 1601-1659 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/cli/cli_config.py 81 60 26% 41-50, 53-55, 71-97, 114-118, 121, 124-128, 139-147, 150-160 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/cli/cli_shared.py 177 136 23% 69-82, 99-110, 126-140, 144-147, 185-208, 229, 248-258, 264-273, 301-383, 405-431, 445-493 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/cli/command_parser.py 207 177 14% 37-40, 43-47, 50, 72-101, 118-148, 164-171, 187, 204-216, 234-240, 259-281, 299-310, 328-339, 359-403, 426-439, 454-468, 486-491, 506-550 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/cli/debugger_cli_common.py 451 353 22% 44-45, 49, 73-77, 94-107, 110, 123-132, 145-151, 198-212, 217, 221, 225, 228, 246-267, 285-300, 310-332, 343-345, 348, 359-362, 373-375, 403-431, 456-527, 563-585, 625-655, 682-716, 727, 741-757, 767, 783-790, 793-795, 807-812, 825-843, 850, 883-896, 909-915, 929-934, 948-953, 974-981, 992-1001, 1019-1023, 1026-1040, 1043-1047, 1051, 1063-1075, 1088, 1103-1105, 1125-1127, 1131, 1135, 1139, 1142, 1145, 1148, 1161-1162, 1170, 1173, 1176, 1179, 1194-1199, 1221-1248 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/cli/evaluator.py 52 37 29% 69-103, 115-116, 131-152 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/cli/profile_analyzer_cli.py 302 252 17% 58-77, 103-131, 134, 137, 140, 143, 173-195, 209-220, 236-380, 396-439, 447-474, 504-575, 586-592, 613-733, 737-742, 756-762, 765, 786-802 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/cli/tensor_format.py 240 215 10% 67-69, 103-199, 233-279, 321-403, 407-426, 449-481, 485, 503-568 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/cli/ui_factory.py 23 16 30% 51-70 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/check_numerics_callback.py 122 89 27% 103-106, 114-119, 156-212, 216, 226-232, 242-289, 314-328, 414-419, 437-448 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/common.py 22 11 50% 44, 59-71, 86 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/debug_data.py 530 403 24% 53-56, 70-71, 74-76, 80, 99-102, 121-140, 144-148, 152-156, 160, 164, 168, 182, 199, 219-231, 241-242, 252-254, 266-268, 307-330, 334, 341, 350, 361, 375, 385, 395, 405, 415, 425, 435, 442, 455, 485-498, 502-522, 555-576, 580-581, 584-590, 594-598, 602-606, 621-623, 636-655, 669-673, 684, 717-718, 723-730, 739, 748, 771-799, 802-809, 812-817, 834-886, 906-918, 922, 933-935, 953-956, 970-971, 985-986, 1007-1020, 1036-1046, 1062-1066, 1085-1093, 1121-1137, 1141-1151, 1193-1229, 1249-1258, 1266, 1284-1295, 1313-1322, 1339-1344, 1363-1378, 1397-1415, 1448-1464, 1490-1497, 1522-1528, 1560-1567, 1594-1601, 1618-1625 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/debug_events_writer.py 52 29 44% 51-54, 64-66, 76-79, 89-92, 102-104, 113-115, 125-128, 132, 137, 146, 150, 154, 157-158 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/debug_gradients.py 120 82 32% 38-39, 53-65, 85-98, 102, 106, 109, 112, 157-169, 215-222, 267-284, 287-290, 304-306, 324-329, 338, 341-346, 353, 360-363, 369, 403-417 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/debug_graphs.py 237 183 23% 40-46, 50-51, 66-67, 83, 98, 116-139, 170-178, 191-214, 217, 220, 225-234, 241-266, 277-309, 320-329, 333-337, 346-354, 358-365, 372-393, 401-405, 413-431, 435, 440, 445-446, 450, 454, 458, 462, 466, 470, 474, 478, 503 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/debug_utils.py 69 60 13% 61-79, 137-197, 252-290 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/dumping_callback.py 301 237 21% 61, 67-68, 73, 77, 89-115, 125-133, 137, 141-143, 147, 151, 155-159, 176-189, 202-205, 216-232, 242-267, 288-301, 334-421, 453-514, 526-571, 590-608, 611-617, 632-643, 740-807, 819-826 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/op_callbacks_common.py 5 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/profiling.py 41 25 39% 44-56, 62, 76-80, 90-100, 104, 108 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/lib/source_utils.py 135 110 19% 44, 48-49, 53-54, 58, 78-84, 112-125, 145-158, 192-225, 262-325, 353-383 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/wrappers/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/wrappers/dumping_wrapper.py 42 28 33% 69-90, 110-135 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/wrappers/framework.py 279 191 32% 130-131, 148-149, 177-178, 204-209, 259-270, 298-305, 314, 346-379, 383, 387, 391, 395, 428-517, 530-588, 605-634, 640-641, 645, 650, 654, 658, 661, 667-676, 679-684, 688, 691, 703, 733-734, 753, 806, 809-811, 814, 818-819, 822, 828-831, 867-874, 878, 915-923, 928, 948-951, 975-984, 989 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/wrappers/grpc_wrapper.py 58 38 34% 57-66, 100-118, 137, 140, 146-151, 155-159, 193-210, 220-224 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/wrappers/hooks.py 95 67 29% 60-65, 83-86, 89, 92-141, 146-148, 176-180, 183, 186-217, 220, 256-264, 277-301, 335-349, 352-357 /usr/local/lib/python3.8/dist-packages/tensorflow/python/debug/wrappers/local_cli_wrapper.py 237 197 17% 80-131, 136, 139-206, 218, 230, 242-277, 280-285, 289-304, 320-374, 377-378, 399-446, 449-453, 462-468, 471-485, 488-513, 525-576, 579-603, 613, 633-642 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/__init__.py 12 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/all_reduce.py 392 355 9% 44-57, 71-75, 95-128, 145-157, 176-190, 223-251, 277-294, 317-356, 370-374, 394-423, 469-477, 496-518, 532-555, 582-589, 608-626, 640-645, 666-682, 701-711, 730-762, 767-776, 781-785, 790-791, 797-800, 820-842, 848-853, 860-865 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/central_storage_strategy.py 34 11 68% 56-70, 75, 103, 144, 162, 180, 246, 255-260 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/cluster_resolver/__init__.py 12 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/cluster_resolver/cluster_resolver.py 173 108 38% 36-39, 44-56, 99, 117, 144-154, 172, 183-198, 202, 218-223, 227, 231, 235, 239, 243, 262-265, 269, 273, 305-321, 347-395, 411-415, 419, 423, 427, 431, 435, 441, 446, 450 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/cluster_resolver/gce_cluster_resolver.py 77 49 36% 30-31, 83-104, 116-149, 152-162, 166, 170, 174, 180, 184, 188 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/cluster_resolver/kubernetes_cluster_resolver.py 52 34 35% 29, 76-94, 112-120, 135-158 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/cluster_resolver/slurm_cluster_resolver.py 160 132 18% 39-86, 96-107, 121-125, 135, 146-155, 164, 233-275, 280, 284, 288, 298-301, 321-358, 372, 386-394, 401-402 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/cluster_resolver/tfconfig_cluster_resolver.py 78 42 46% 36-39, 43, 47-48, 76-79, 83-87, 91-95, 99, 103, 107, 111-114, 118, 124-126, 135-138, 160-177 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/cluster_resolver/tpu_cluster_resolver.py 106 67 37% 40, 76-85, 90-95, 150-167, 170, 173, 201-214, 217, 220, 246-256, 278-300, 305, 308-319, 324 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/collective_all_reduce_strategy.py 228 165 28% 99-110, 116-118, 135, 148-158, 169-176, 180-183, 187-242, 247-344, 356-391, 399-408, 411-412, 421-422, 434-435, 456-470, 473-508, 511-530, 537-540, 545, 549, 553, 557, 561, 565, 577 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/collective_util.py 11 3 73% 62-64 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/cross_device_ops.py 452 356 21% 56-59, 64-73, 79-102, 107-116, 122-138, 144-151, 157-161, 165, 169-174, 179-188, 194-211, 219, 224, 251-266, 298-318, 331-332, 359, 387, 402, 426-428, 432-443, 447, 472-479, 504-513, 529-531, 535-583, 587-617, 622-628, 633-635, 652-655, 659-663, 668-672, 679-690, 695-720, 724-730, 760-764, 791-795, 835-861, 867-907, 948-953, 957, 961-989, 993-1004, 1012-1024, 1031-1101, 1106-1137, 1151-1183 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/cross_device_utils.py 400 345 14% 44-53, 80-135, 158-170, 188-197, 214-229, 270-275, 280-282, 293-306, 318-319, 323-325, 329-331, 365-387, 414-433, 465-535, 545-576, 594-618, 635-655, 675-690, 705-713, 743-769, 785-801, 806-809, 813-818, 822-830, 835-842, 846-849, 863-874, 887-897, 910-916, 937-958, 976-986 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/device_util.py 47 29 38% 47-67, 72, 79-80, 87-90, 93, 96, 102-108, 113-114, 121 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/distribute_coordinator.py 315 243 23% 74-79, 83-92, 97-99, 137-146, 149-153, 156-162, 167, 172-192, 196-205, 213-216, 244-260, 268, 273, 278, 283, 288, 293, 298, 303, 308, 313, 318, 323, 336-360, 373-382, 395-451, 457-494, 500-526, 538-552, 590-625, 752-868 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/distribute_coordinator_context.py 11 4 64% 28-31 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/distribute_lib.py 687 352 49% 149-152, 159-160, 163-164, 167-168, 186-194, 206, 209-214, 220-225, 232-240, 249, 254-258, 277-285, 289-300, 303-332, 374-376, 381, 386, 391, 407-411, 414, 463-464, 469, 474, 477, 507, 617-625, 640-644, 661, 666, 673-677, 705, 711-713, 874, 943, 957, 998-1056, 1078, 1097, 1102, 1107, 1126, 1132, 1136-1144, 1147, 1201, 1264, 1314, 1388, 1429, 1470, 1501, 1536, 1540, 1559, 1754-1777, 1785, 1789, 1818, 1857-1865, 1869, 1872, 1877, 1881, 1885, 1888, 1891, 1894, 1897, 1901, 1922-1931, 1934, 1953-1959, 1964, 2007-2013, 2016, 2033-2039, 2042, 2045, 2060, 2064-2072, 2077, 2082, 2089, 2095, 2110, 2118, 2121, 2140, 2165-2166, 2169, 2182-2186, 2189, 2233-2235, 2240, 2293, 2308, 2317, 2322, 2327, 2332, 2374, 2415-2420, 2424-2429, 2434, 2447-2448, 2458-2459, 2489-2511, 2526-2530, 2544, 2550-2551, 2571, 2583-2584, 2603-2604, 2613, 2616, 2619, 2624-2625, 2628-2637, 2640-2643, 2653-2654, 2659, 2664-2669, 2672, 2675, 2682, 2686, 2691, 2695, 2708-2712, 2715, 2724-2728, 2733, 2739, 2751-2756 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/distributed_file_utils.py 33 21 36% 57-58, 62, 66-68, 73-86, 91-104 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/distribution_strategy_context.py 102 23 77% 51, 151, 176, 256-266, 275-280, 302-307 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/estimator_training.py 176 152 14% 42-46, 51-55, 61-86, 94-124, 130-177, 184-200, 216-283, 297-336, 346-384 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/experimental/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/input_lib.py 673 488 27% 83-91, 124-131, 148-150, 155, 159, 162, 165-169, 172, 175, 180-216, 231-240, 245-256, 263-289, 292, 295-298, 301, 305-377, 388-391, 400, 405, 410, 415, 420, 424-427, 432, 444-450, 454, 459, 463, 469-481, 495-508, 513-521, 524, 527, 536, 546-571, 576, 580, 589-590, 593, 597-621, 650-705, 709-729, 734, 746-747, 763, 770-773, 785, 791-794, 797-803, 806-810, 830-845, 849-873, 879-885, 893-899, 906-909, 912-920, 923-927, 953-975, 1007-1019, 1025-1065, 1082-1086, 1089, 1093-1095, 1110-1112, 1130-1156, 1165-1167, 1171, 1174, 1178-1181, 1184, 1187, 1197, 1223-1239, 1244-1249, 1254, 1258, 1271, 1283, 1295, 1305-1306, 1319-1323, 1327, 1331, 1335, 1342-1344, 1348-1350, 1354-1357, 1361-1364, 1368, 1374-1388, 1396-1415, 1422-1431, 1440-1456, 1467-1478, 1498-1500, 1515, 1519-1521, 1543-1561, 1567, 1571-1579, 1595-1608 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/input_ops.py 41 27 34% 46-53, 58-61, 65, 79-101 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/mirrored_strategy.py 526 409 22% 65-74, 78-80, 113-203, 220-236, 241-252, 265-281, 285, 305-325, 329-332, 336-341, 426-429, 439-442, 451-476, 481-488, 492-505, 510-545, 553-569, 573-607, 613, 616, 626-633, 638, 645, 649-657, 664-669, 674-725, 733-739, 742-769, 777-788, 791-793, 796, 799-810, 818, 824-835, 838-846, 850-853, 856-858, 861, 865, 869, 873, 877, 881, 885, 889, 893, 896-898, 910, 914, 922-975, 978-1001, 1006-1010, 1016-1020, 1024-1026, 1030-1032, 1048-1086, 1090-1092 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/multi_worker_util.py 74 57 23% 40-46, 72-93, 120-134, 150-168, 173-188, 211-227, 243, 256, 261, 266 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/numpy_dataset.py 45 29 36% 34-73, 79-91, 98 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/one_device_strategy.py 155 82 47% 80, 107, 146, 164, 182, 215, 231, 242, 251-256, 259-268, 271, 277, 284, 289, 293-294, 299, 303, 313, 318-357, 360-362, 365-366, 371, 374-380, 384, 387, 390, 394, 398, 402, 406, 409-410, 414, 418, 422, 426, 432, 436, 443-444, 449 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/parameter_server_strategy.py 285 204 28% 111-120, 131-136, 151-158, 165-168, 188-255, 270-305, 311, 314, 321, 332-344, 349, 353-367, 376, 385-390, 393, 398-456, 460, 464-471, 476-481, 489-491, 498-515, 518-529, 533-539, 542-544, 547-552, 557, 580-591, 594-612, 616, 620, 624, 628, 632, 635, 640, 644, 648, 652, 664 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/reduce_util.py 18 5 72% 42-51 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/shared_variable_creator.py 37 28 24% 29-35, 63-97 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/summary_op_util.py 15 7 53% 40-48 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/tpu_strategy.py 450 334 26% 65-76, 81-85, 101-105, 151-161, 168-174, 199-204, 210, 266-270, 282-349, 359-374, 378-381, 384, 388, 398-405, 412, 417, 424-432, 439-444, 452-539, 544-545, 550-565, 569-577, 582-611, 615, 623, 627-668, 675-712, 715-735, 738-740, 743-745, 748, 751-770, 774-777, 782-792, 796-798, 802, 806, 810, 814, 818, 822, 825, 828-834, 841-843, 846-851, 863, 866-867, 870-957, 966, 975-977, 982-990, 994, 1001-1013 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/tpu_values.py 143 89 38% 41-46, 51-61, 68-75, 78-81, 85-88, 92, 95-98, 101-104, 108, 114-118, 124, 127-129, 132-135, 138-141, 144-147, 151, 159-166, 171-183, 190-196, 200-202, 205-207, 210-212, 215, 218, 221, 224, 227, 230, 233, 236, 243-246, 251-254, 259-262, 266 /usr/local/lib/python3.8/dist-packages/tensorflow/python/distribute/values.py 749 470 37% 48-55, 125, 129-133, 136, 142-151, 156, 160, 163-165, 168-170, 191-198, 203, 212, 216, 219, 222, 225, 228, 231, 234, 237, 240, 243, 246, 249, 252, 255, 258, 261, 264, 267, 270, 273, 276, 279, 282, 285, 288, 291, 294, 297, 300-304, 307-311, 314-318, 321-325, 335, 341, 352, 355, 359, 362-367, 370, 380, 383-387, 391-392, 396-397, 401-402, 416-433, 445-454, 458-465, 468, 472, 476, 480, 484, 488, 493, 497, 501, 505, 509, 513-518, 521, 525, 528, 531-532, 536, 540, 544, 547, 550, 557-560, 564, 567-568, 571, 575, 582-584, 591-595, 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/backprop.py 415 331 20% 70-77, 87-97, 104-108, 111-115, 118, 144-159, 170, 226-249, 294-298, 303-326, 394-400, 424-432, 491-500, 539-572, 576-582, 589-612, 625-634, 639-647, 651, 659-681, 685-699, 715-717, 821-829, 833-834, 838-839, 843-852, 855-858, 861-867, 878-892, 917-924, 958-960, 964-966, 998-1056, 1108-1160, 1219-1281 /usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/backprop_util.py 12 5 58% 26-31 /usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/context.py 1014 426 58% 84-86, 89-95, 98, 101, 143-149, 170-172, 176-178, 332-335, 407, 440-451, 463, 498, 508, 511, 513, 522-523, 526-527, 534-536, 539, 560-572, 589-604, 620-623, 640, 653-656, 669-678, 705-721, 726, 732-735, 738-745, 771, 775, 815, 817, 822, 835, 840-857, 860-863, 867-868, 873-874, 884, 887, 891, 893, 896, 901, 904, 911, 921, 942, 963, 965-970, 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84-139, 171-202, 237-359 /usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/monitoring.py 112 35 69% 119, 125-132, 137, 164, 200, 208, 212, 236, 248, 256, 260-263, 287, 311, 347, 355, 363-368, 380, 383, 402, 425, 430 /usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/profiler.py 68 37 46% 72-84, 99-108, 120-126, 136-142, 158-160, 174, 177, 180-181 /usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/remote.py 76 53 30% 70-77, 136-219, 223 /usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/tape.py 67 26 61% 39, 42, 47-48, 53, 58, 63-70, 84, 97-109, 114, 155, 177, 184 /usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/wrap_function.py 228 179 21% 49-52, 56, 60-83, 86, 90-94, 99-119, 124-142, 160-208, 223-229, 257-362, 377-389, 433-443, 447, 451, 501, 510-539, 599-603, 630-635 /usr/local/lib/python3.8/dist-packages/tensorflow/python/feature_column/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/feature_column/dense_features.py 36 18 50% 92, 102, 111-113, 116, 137-150 /usr/local/lib/python3.8/dist-packages/tensorflow/python/feature_column/dense_features_v2.py 18 6 67% 82-87, 90-95 /usr/local/lib/python3.8/dist-packages/tensorflow/python/feature_column/feature_column.py 877 622 29% 182-231, 297, 322-329, 332, 342, 346, 350, 354, 358, 362, 366, 492-504, 516-526, 543-548, 551-566, 569-577, 590-592, 595-601, 604, 608-612, 616, 633-661, 669, 672-700, 706-708, 744-752, 801-814, 904-929, 997-1009, 1083-1097, 1144-1155, 1242-1268, 1357-1385, 1444-1453, 1488, 1558-1560, 1670-1688, 1718-1722, 1731, 1734-1742, 1745, 1768, 1790, 1810, 1815, 1840, 1861, 1885, 1910, 1921-1931, 1947-1963, 1981, 2008, 2046-2067, 2085, 2128-2129, 2149-2171, 2191-2217, 2226-2233, 2254-2274, 2297-2323, 2335, 2339, 2346-2353, 2357, 2374-2378, 2388, 2392, 2395-2396, 2402, 2406-2409, 2418, 2423-2448, 2470, 2484-2486, 2490, 2493, 2497-2499, 2507-2531, 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101, 110, 113, 133-153, 176-202, 247, 293, 355, 418, 474-482, 492-499, 511, 516, 521, 537-540, 545, 556-576, 582, 586-588, 593-596 /usr/local/lib/python3.8/dist-packages/tensorflow/python/feature_column/serialization.py 35 19 46% 84-90, 118-146, 166, 187-188, 208 /usr/local/lib/python3.8/dist-packages/tensorflow/python/feature_column/utils.py 64 47 27% 32-52, 56-57, 62-63, 94-122, 129-131, 135-137, 145-154 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/auto_control_deps.py 163 58 64% 171-175, 177-181, 184-186, 197, 244-268, 272, 275, 283, 329, 339, 342-349, 361, 366, 371-374, 377, 388, 466, 489-495 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/auto_control_deps_utils.py 82 21 74% 46-47, 53-54, 63, 67-69, 75, 121, 141-149, 166-169 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/c_api_util.py 100 27 73% 33, 38-39, 104, 107, 118-128, 133-134, 137, 140-146, 149-151, 154 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/common_shapes.py 35 26 26% 38-70, 84-86, 102-108 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/composite_tensor.py 26 9 65% 54, 71, 83-88, 107-112 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/composite_tensor_utils.py 57 41 28% 35, 43-47, 53-90, 97-110, 134-159 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/config.py 108 44 59% 37, 51, 64, 77, 91, 105, 121, 163, 178, 193, 209-219, 251-262, 275, 295-300, 406, 443, 472, 500, 541, 626, 632 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/constant_op.py 118 57 52% 39-46, 51-57, 62-65, 86-89, 93-94, 160, 273-292, 311-315, 337, 343-344, 347-350, 368-378 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/convert_to_constants.py 300 263 12% 56-70, 91-135, 147, 159, 179-185, 202-223, 248-302, 315-320, 330-335, 347-352, 366-374, 393-412, 447-650, 678-680, 705-708 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/cpp_shape_inference_pb2.py 31 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/device.py 57 8 86% 29, 42, 53, 55, 95, 117, 120, 169 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/device_spec.py 156 25 84% 46, 210, 333, 339, 344, 389, 403-404, 408-409, 413-414, 418-419, 423-424, 427-429, 432-436, 439-442, 453 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/dtypes.py 215 49 77% 79-82, 88, 95-101, 116-130, 140-154, 167-170, 200-201, 216, 628-629, 633-642 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/error_interpolation.py 202 168 17% 86-98, 119-140, 145, 168-189, 195, 214-223, 243-251, 256-257, 274-281, 299-337, 372-401, 416-425, 438-452, 467-484, 502-542 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/errors.py 6 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/errors_impl.py 210 72 66% 37-44, 82-84, 105, 110, 115, 119-163, 227, 246, 281, 316, 334, 349, 365, 382, 401, 419, 438, 454, 468, 485, 515, 520-524, 528-533, 545-546, 549-560 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/framework_lib.py 40 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/func_graph.py 504 152 70% 89-90, 95, 103-104, 115, 122, 214, 245, 251, 263, 293-319, 349-359, 390-391, 396, 419, 447, 452, 456, 468, 483, 508-528, 572, 581-582, 590, 626, 631-643, 662, 680-682, 686-690, 699, 704-705, 710-724, 728, 753, 769-772, 782, 786-793, 865, 873, 881, 891-893, 928, 933-934, 938-939, 966-970, 1004-1008, 1039-1045, 1064-1065, 1070, 1105-1113, 1169, 1173-1182, 1196, 1205, 1213-1216, 1226-1246, 1249, 1261 /usr/local/lib/python3.8/dist-packages/tensorflow/python/framework/function.py 527 443 16% 123-128, 132-184, 198, 201-212, 270-304, 310-311, 316-329, 333-334, 338-340, 345, 350, 355, 360-361, 370-371, 375-376, 380-477, 489-493, 510-540, 544-560, 563-579, 617-625, 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/datasets/imdb.py 56 42 25% 99-158, 171-177 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/datasets/mnist.py 15 6 60% 57-67 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/datasets/reuters.py 47 33 30% 106-151, 164-170 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/distribute/__init__.py 4 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/distribute/distributed_training_utils.py 473 386 18% 68-80, 113-137, 142-166, 193-213, 236, 253-272, 308-322, 343-359, 363-366, 372-375, 381-399, 404-410, 424-426, 435, 447-449, 459-469, 502-573, 577-581, 585-588, 592-595, 600-620, 636-669, 684-689, 694-703, 732-773, 779-783, 790-825, 830-835, 840-849, 854-880, 885-902, 907-913, 918-947, 953-983, 993-1025, 1033-1040, 1045-1049, 1054-1062, 1066-1071, 1075-1076, 1080-1081, 1085-1086, 1090-1091, 1095-1096, 1101-1102, 1121-1133, 1137, 1151-1169, 1176-1192, 1197-1201 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/base_preprocessing_layer_v1.py 26 14 46% 51-54, 58-61, 66-73 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/compile_utils.py 318 253 20% 41-44, 63-68, 85-98, 101, 104, 126-132, 136-149, 153-161, 183-247, 261-269, 272, 275, 295-297, 301-335, 342-370, 375-383, 387-416, 420-421, 434-477, 481-484, 488-490, 495, 500, 528-545, 575-592, 597-602, 607-617, 623-632 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/data_adapter.py 639 339 47% 56-57, 61-62, 115, 140, 156, 172, 185, 198, 203, 211, 216, 220-225, 229, 241, 249, 264-371, 388-408, 411, 414, 417, 420, 423, 427, 452, 467, 470-476, 493-523, 533, 539, 542, 546-548, 562-593, 596, 599, 602, 605, 608, 611, 622, 628, 630, 641-650, 660, 663, 666, 669, 672, 675, 691-699, 702, 705, 708, 711, 714, 720, 726-735, 762, 765, 779-780, 789, 801-802, 823, 830-831, 836-849, 855, 858, 861, 864, 867, 870, 891, 894, 917-922, 925-932, 944, 960, 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1298-1299, 1322-1325, 1346, 1360, 1368-1369, 1378-1379, 1390, 1400-1405, 1409-1410, 1433-1497, 1522-1525, 1553, 1559, 1565-1573, 1576-1582, 1587, 1591, 1603-1606, 1612, 1678, 1741-1744, 1787, 1802, 1818-1821, 1827, 1833-1847, 1852-1857, 1863-1877, 1883-1893, 1912-2056, 2069-2157 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/node.py 51 9 82% 76, 120-122, 158-159, 176-177, 182-184 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/partial_batch_padding_handler.py 62 46 26% 34-36, 40-53, 58-62, 66-87, 91-111 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/sequential.py 196 102 48% 126, 167-169, 172, 190-199, 204, 215, 226-227, 241-255, 262-266, 270-299, 302-305, 311-312, 329-335, 359-363, 366-383, 387-403, 407-409, 413, 417-422 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/training.py 459 256 44% 65-72, 86, 171, 196-197, 246-248, 347, 398-410, 450, 472, 480-494, 498, 527-544, 566-582, 785-881, 906-915, 936-952, 1039-1098, 1143, 1146-1151, 1273, 1290-1291, 1340-1359, 1400-1417, 1434-1439, 1464-1465, 1497-1500, 1525-1526, 1542, 1544, 1548-1549, 1559, 1568, 1572, 1576, 1581-1584, 1600, 1624-1627, 1634-1635, 1641, 1645, 1649-1660, 1663-1669, 1677-1688, 1691, 1701, 1721-1729, 1737, 1739, 1744, 1750-1760, 1785-1814 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/training_arrays.py 259 222 14% 42-43, 126-458, 462-467, 471-477, 482-484, 501-535, 539-542, 546-550, 555-557, 564-583, 621-649, 678-687, 705-708 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/training_distributed.py 322 282 12% 46-47, 52-56, 73-120, 164-290, 315-420, 444-574, 599-672, 698-720, 737-754, 766-779, 786, 789, 793, 798 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/training_eager.py 119 98 18% 37-39, 55-82, 114-219, 250-283, 308-322, 349-366 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/training_generator.py 239 198 17% 123-336, 349-362, 398-418, 449-484, 493-509, 514-530, 535-538, 571-574, 604-606, 626-627, 659-666, 692-695, 706-707, 738-766, 791-800, 816-819 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/training_utils.py 834 682 18% 79-83, 92, 105, 110, 124, 131, 135-140, 143-145, 156-157, 161, 168-174, 178-192, 209-212, 241-244, 253-258, 262-286, 289-300, 303-310, 321-342, 345-347, 350-353, 358-364, 385-400, 428-436, 441-457, 486-583, 601-626, 633, 638, 657-697, 713-750, 771-808, 844-891, 907-915, 944-1042, 1046-1048, 1052-1056, 1069-1091, 1106-1133, 1142-1157, 1162-1186, 1210-1213, 1216-1228, 1233-1235, 1256-1270, 1278-1289, 1297-1306, 1333-1355, 1359-1364, 1380-1391, 1405, 1420-1421, 1435-1461, 1482-1503, 1525-1544, 1552, 1556, 1584-1613, 1639-1670, 1682-1689, 1694, 1700-1705, 1709-1711, 1723-1725, 1737-1759, 1787-1817, 1827-1840, 1850, 1857-1887, 1891-1892, 1896, 1923-1925, 1929, 1947, 1951, 1965-1970, 1975-1977, 1997-2007, 2012-2030, 2049-2078, 2110, 2123, 2133 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/training_v1.py 1067 853 20% 71-72, 143-163, 167, 175-180, 228-233, 301-463, 475-476, 481-486, 494-506, 522-545, 549, 556-586, 754-766, 874-879, 953-957, 970-976, 1025-1070, 1110-1146, 1166-1192, 1217, 1249-1251, 1276, 1288-1299, 1313-1337, 1348-1350, 1362-1380, 1386-1423, 1427-1437, 1460-1468, 1471-1478, 1494-1515, 1528, 1532, 1546-1627, 1632-1642, 1646-1650, 1673-1742, 1747-1756, 1760-1768, 1791-1799, 1805, 1818-1827, 1831-1856, 1876-1882, 1914-1938, 1949-1953, 1959-2003, 2006-2030, 2033-2041, 2049-2057, 2099-2170, 2242-2302, 2312-2436, 2440-2498, 2501-2534, 2572-2591, 2596-2636, 2643-2647, 2652, 2660, 2668, 2676, 2684, 2692, 2696-2702, 2706, 2710, 2714, 2732-2735, 2743-2746, 2753-2754, 2774-2775, 2781-2787, 2791, 2794-2802, 2806, 2813-2814, 2817, 2820, 2825-2829, 2832-2835, 2842-2846, 2886-2893, 2897, 2901, 2905, 2909, 2913, 2917, 2921, 2925, 2942-2972, 2979, 2983, 2987, 2991, 2995, 2999, 3002, 3005, 3009, 3012, 3016-3018, 3023-3042, 3048, 3054-3075, 3097-3099, 3103, 3107, 3111, 3115, 3135-3151, 3165-3175, 3179-3180 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/estimator/__init__.py 23 12 48% 115-122, 212-219 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/initializers.py 89 8 91% 93, 118, 142, 166, 181, 194, 202, 207 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/__init__.py 180 21 88% 54-59, 157-159, 214-225 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/advanced_activations.py 135 78 42% 68-70, 73, 76-78, 82, 126-136, 140-157, 160-162, 165-172, 176, 203-205, 208, 211-213, 217, 244-246, 249-250, 253-255, 259, 279-281, 284, 287-289, 293, 345-358, 363, 369-375, 379 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/convolutional.py 730 587 20% 121-149, 152-191, 194-222, 225-250, 254-273, 277-282, 285-288, 291-295, 298-304, 319-325, 429, 582, 726, 874-898, 903-934, 937-994, 997-1027, 1030-1032, 1167-1190, 1195-1226, 1229-1295, 1298-1332, 1335-1338, 1430-1453, 1456-1496, 1499, 1502-1543, 1656, 1680-1719, 1841, 1866-1887, 1985-2001, 2004-2036, 2039-2056, 2060-2078, 2081-2093, 2134-2136, 2139-2141, 2144-2145, 2148-2150, 2216-2223, 2226-2239, 2243, 2248-2254, 2302-2305, 2308-2325, 2329, 2333-2335, 2384-2386, 2389-2393, 2396, 2399-2401, 2472-2492, 2495-2516, 2520, 2524-2526, 2584-2610, 2613-2642, 2646, 2650-2652, 2692-2694, 2697-2702, 2705-2708, 2711-2713, 2768-2788, 2791-2802, 2813-2833, 2838-2840, 2899-2925, 2928-2958, 2964-3014, 3020-3022 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/convolutional_recurrent.py 345 261 24% 165-181, 185-222, 228-275, 279-292, 302-350, 353-420, 510-537, 541-584, 587-644, 647-654, 657-660, 663-692, 842-869, 872-873, 880, 884, 888, 892, 896, 900, 904, 908, 912, 916, 920, 924, 928, 932, 936, 940, 944, 948, 952, 956, 960, 963-995, 999 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/core.py 458 303 34% 101-104, 107, 110-115, 118, 121-123, 179-183, 189-196, 199-212, 215, 218-224, 260-261, 264-266, 311-318, 321-325, 369-376, 379-383, 415-417, 420, 423, 426-428, 472-473, 495-515, 518-527, 530, 534-536, 571-578, 581-586, 589, 592-594, 630-632, 635-667, 670-679, 682-684, 714-716, 719-720, 723, 726-728, 825-841, 845-870, 874-890, 893-932, 937, 940-942, 945-966, 969-985, 989-1016, 1022-1048, 1129, 1150, 1154, 1176, 1183-1188, 1192, 1199, 1202-1208, 1211-1225, 1246-1250, 1253, 1256-1258 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/cudnn_recurrent.py 189 143 24% 65-81, 84-121, 124-133, 137, 141-143, 147-149, 153, 156, 215-236, 240, 243-269, 272-316, 319-337, 400-422, 426, 429-465, 468-518, 521-540 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/dense_attention.py 132 95 28% 77-80, 92, 119-134, 138-167, 170-176, 180-196, 201-206, 307-308, 312-321, 332-335, 338-340, 443-444, 447-460, 473-480, 484-486, 491-495, 499-503 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/embeddings.py 71 46 35% 101-123, 133-148, 151-154, 158-178, 181-185, 188-203 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/kernelized.py 80 56 30% 138-154, 157-200, 203-207, 210-216, 219-228, 234-251, 255-258 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/local.py 209 172 18% 151-171, 175-259, 263-274, 277-298, 301-334, 465-485, 489-581, 585-600, 603-625, 628-661, 704-724, 770-778, 807-816, 834-841 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/merge.py 342 244 29% 49, 67-87, 92-118, 122, 124-181, 187-202, 205-217, 251-254, 284-286, 290-293, 320-323, 357-360, 387-390, 417-420, 493, 496, 504-519, 526-536, 541-564, 567-571, 639-654, 659-674, 680-700, 704-722, 725, 728-733, 767, 796, 810, 846, 878, 892, 927, 947 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/noise.py 80 47 41% 60-62, 66-73, 76-78, 82, 111-113, 116-127, 130-132, 136, 170-174, 177, 180-203, 206-208, 212 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/normalization.py 511 442 14% 199-247, 258-271, 275-279, 283, 287-289, 292-295, 300-303, 306, 311-503, 506-516, 519-521, 525-635, 640-693, 696, 699-708, 711-722, 725-890, 893, 896-928, 1010-1034, 1042-1055, 1058-1105, 1109-1193, 1196, 1199-1212 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/normalization_v2.py 43 23 47% 136, 161-204 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/pooling.py 256 162 37% 60-70, 73-81, 84-98, 101-108, 193, 235, 272-282, 285-297, 300-315, 319-326, 458, 508, 544-554, 557-574, 577-596, 600-607, 654, 704, 714-717, 720-724, 727, 730-732, 775-777, 780-789, 792, 840-841, 849-852, 855-859, 862, 865-867, 906-909, 947-950, 957-960, 963-967, 970, 973-975, 1008-1011, 1043-1046 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/preprocessing/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/preprocessing/categorical_encoding.py 218 164 25% 83-129, 136, 139-145, 163-170, 173-178, 181-187, 190-193, 196-205, 208-217, 220-234, 237-292, 317-318, 322-341, 345-364, 379, 394-412, 416, 421-429, 433-447, 452-458 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/preprocessing/categorical_encoding_v1.py 7 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/preprocessing/image_preprocessing.py 485 384 21% 78-83, 86-89, 92-96, 99-100, 104-110, 135-138, 141-144, 147-171, 174-175, 179-184, 214-219, 222-277, 280-281, 285-291, 315-316, 319-320, 323, 326-330, 367-383, 386-402, 405, 408-413, 467-506, 509-541, 544, 547-555, 570-578, 647-670, 696-704, 768-790, 793-816, 819, 822-829, 879-918, 921-952, 955, 958-966, 987-997, 1043-1054, 1057-1067, 1070, 1073-1078, 1118-1132, 1135-1157, 1160-1161, 1165-1171, 1213-1227, 1230-1252, 1255-1256, 1260-1266, 1270-1273, 1277-1282 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/preprocessing/index_lookup.py 230 173 25% 104-190, 193-208, 211-212, 215, 218-222, 225-231, 234-235, 239-241, 245-246, 250-257, 260, 263-268, 283-285, 288-294, 297-305, 312, 333-353, 356-358, 361-389, 392-401, 404-429, 451, 455-465, 469-477, 489-495, 499, 504-507, 511-518, 523-524 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/preprocessing/index_lookup_v1.py 38 22 42% 63-66, 69, 72-76, 79-81, 84-85, 89-95 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/preprocessing/normalization.py 95 56 41% 63-71, 75-104, 109-111, 114, 117, 120-122, 126-128, 149, 155-173, 178-197, 202, 212-220, 225-230, 234-235, 241 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/preprocessing/normalization_v1.py 10 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/preprocessing/text_vectorization.py 309 235 24% 214-320, 325, 328-329, 332, 336-338, 342-343, 347, 350-359, 362-364, 379-404, 407, 410-420, 427, 461-521, 528-534, 537-543, 546-592, 595-633, 663-665, 669-694, 698-715, 730, 745-762, 766, 771-781, 785-802, 807-814 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/preprocessing/text_vectorization_v1.py 26 9 65% 84, 87, 91-97 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/recurrent.py 1046 802 23% 85-104, 108, 113-118, 121-131, 135-160, 165-180, 183-191, 195-200, 397-439, 444-447, 454, 457-505, 513-519, 522-592, 606-621, 625-645, 648-707, 717-814, 820-854, 857-866, 871-873, 890-943, 946-965, 969-974, 978, 1052, 1061, 1066, 1069, 1096-1099, 1110, 1121, 1124, 1131, 1153-1156, 1174-1177, 1266-1290, 1294-1319, 1322-1340, 1343, 1346-1378, 1489-1526, 1529-1530, 1535, 1539, 1543, 1547, 1551, 1555, 1559, 1563, 1567, 1571, 1575, 1579, 1583, 1587, 1590-1625, 1629-1631, 1709-1740, 1744-1778, 1781-1879, 1882-1907, 1910, 2032-2071, 2074-2075, 2080, 2084, 2088, 2092, 2096, 2100, 2104, 2108, 2112, 2116, 2120, 2124, 2128, 2132, 2136, 2140, 2144, 2147-2188, 2192-2194, 2275-2312, 2316-2353, 2357-2367, 2371-2376, 2379-2436, 2439-2477, 2480, 2518-2530, 2536-2549, 2552-2559, 2678-2717, 2720-2721, 2726, 2730, 2734, 2738, 2742, 2746, 2750, 2754, 2758, 2762, 2766, 2770, 2774, 2778, 2782, 2786, 2790, 2793-2834, 2838-2840, 2844-2852, 2877-2913, 2918, 2923-2926, 2931-2944, 2964-2991, 3008-3011 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/recurrent_v2.py 321 259 19% 165, 345-385, 388-398, 403-454, 462-503, 547-587, 593-673, 713-791, 895, 1059-1102, 1107-1207, 1233-1238, 1288-1321, 1359-1444, 1485-1569, 1596-1602, 1625-1626, 1631-1635, 1642-1645, 1649-1650 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/rnn_cell_wrapper_v2.py 43 17 60% 42-43, 66, 71-72, 75-82, 86-89, 98-100, 113, 124 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/serialization.py 57 18 68% 68, 84-105 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/layers/wrappers.py 370 318 14% 52-54, 57-60, 64-67, 70-77, 81-86, 126-137, 163-172, 175-184, 187-195, 199-251, 290-327, 400-456, 460-469, 480-495, 499-518, 522-593, 602-677, 680-681, 684-688, 691-707, 711-715, 718-728, 733-745 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/losses.py 266 127 52% 105, 107, 140-144, 157, 161, 177, 181-201, 243-246, 249-253, 312, 372, 433, 494, 570-576, 729, 793, 855, 916, 974, 1032, 1093, 1162, 1196-1198, 1228-1230, 1262-1266, 1300-1304, 1309-1319, 1347-1350, 1379-1382, 1411-1415, 1438-1444, 1481-1487, 1517-1527, 1555-1557, 1585-1594, 1632-1636, 1667-1669, 1714-1716, 1782, 1797-1803, 1816, 1831, 1853-1863 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/metrics.py 759 457 40% 151, 164-167, 186-207, 212, 216, 224, 244, 253, 268, 274, 290, 328-374, 377-385, 425, 516-518, 533-547, 551-554, 595-604, 608-618, 624-628, 665, 710, 765, 809, 889, 913-918, 936, 944-948, 951-952, 956-958, 1004, 1054, 1104, 1154, 1225-1237, 1256, 1269-1271, 1274-1275, 1279-1285, 1351-1363, 1382, 1395-1397, 1400-1401, 1405-1411, 1423-1450, 1465, 1478-1479, 1537-1541, 1546-1556, 1561-1566, 1623-1627, 1632-1642, 1647-1652, 1701-1705, 1713-1723, 1728-1730, 1782-1786, 1796-1807, 1810-1813, 1920-1981, 1985-2023, 2038-2067, 2129-2164, 2167-2214, 2219-2223, 2228-2244, 2295, 2326, 2359, 2390, 2423, 2456, 2491, 2523, 2555, 2570-2575, 2579, 2610, 2641, 2672, 2729-2734, 2754-2776, 2780-2799, 2803, 2806-2808, 2840-2844, 2847-2857, 2861, 2865, 2877-2908, 2911-2916, 2919-2920, 2973, 3112, 3136, 3155-3157, 3160-3166, 3170-3174, 3178-3184, 3200-3202, 3219, 3239-3252, 3268, 3285-3294, 3310-3312, 3327-3330, 3335, 3340, 3345, 3355-3364, 3368 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/mixed_precision/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/mixed_precision/experimental/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/mixed_precision/experimental/autocast_variable.py 243 135 44% 63-69, 73-75, 82-85, 90, 93-96, 99-100, 104-105, 109-110, 113, 117-127, 131, 134-143, 161, 165, 169, 173, 176, 179, 183, 187, 190-191, 194-195, 198-199, 202-203, 206-207, 210-211, 214-215, 218-219, 222-223, 226-227, 230-231, 234-235, 238-239, 242-243, 246, 250, 254, 258, 262, 266, 270, 274, 277, 284, 289, 292, 304, 308, 312, 316, 325, 328, 331, 334, 337, 340, 343, 346, 349, 352, 355, 358, 361, 364, 367, 370, 373, 376, 379, 382, 385, 388-392, 395-399, 402-406, 409-413, 439-462, 481-483 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/mixed_precision/experimental/device_compatibility_check.py 66 48 27% 54-61, 73-128, 154-166 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/mixed_precision/experimental/get_layer_policy.py 11 3 73% 38-41 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/mixed_precision/experimental/loss_scale.py 15 4 73% 29, 33-38, 48 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/mixed_precision/experimental/loss_scale_optimizer.py 140 81 42% 48, 123-155, 160, 182-189, 212-214, 218-224, 227-229, 232, 238-245, 251-272, 279, 284-286, 293-298, 301-303, 313, 317, 320, 323, 327, 330, 333, 336, 345, 349, 353, 357, 366, 372, 395-405 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/mixed_precision/experimental/policy.py 133 60 55% 328, 331, 339, 341, 348, 361-371, 374, 376, 378, 382-388, 460, 463-471, 475-479, 508-509, 519-520, 549-558, 573-578, 582-586, 606, 612-617, 621-626 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/models.py 277 231 17% 57, 61, 67-74, 90-129, 162-215, 234-247, 265-276, 307-381, 419-426, 452-533, 550-557, 570-589, 638-723 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizer_v2/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizer_v2/adadelta.py 49 28 43% 100-104, 108-111, 114-115, 121-127, 130-136, 147-153, 165-172 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizer_v2/adagrad.py 60 35 42% 91-100, 103-107, 110-111, 118-124, 143-147, 150-155, 164-169, 179-186 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizer_v2/adam.py 84 61 27% 144-150, 155-161, 164-173, 185-192, 195-217, 232-269, 272-281 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizer_v2/adamax.py 63 41 35% 103-108, 112-115, 118-126, 137-144, 157-181, 184-192 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizer_v2/ftrl.py 60 42 30% 108-136, 141-146, 149-150, 162-181, 194-214, 228-245 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizer_v2/gradient_descent.py 53 24 55% 112, 118-120, 123-124, 128-143, 148-156, 161-166, 177-184 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizer_v2/learning_rate_schedule.py 249 184 26% 44, 48, 60, 135-140, 143-154, 158, 225-233, 236-256, 259, 360-367, 370-392, 399, 480-486, 489-502, 505, 573-578, 581-594, 597, 668-675, 678-716, 719, 803-810, 813-831, 835, 925-934, 937-965, 969, 983, 988 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizer_v2/nadam.py 96 72 25% 92-105, 108-124, 127-146, 164-165, 168-188, 191-228, 231-239 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizer_v2/optimizer_v2.py 448 310 31% 72-76, 268, 272, 293, 301, 333-336, 340-356, 385-402, 418-430, 472-504, 520-545, 550-604, 607-613, 618, 622-630, 633-643, 646, 661-663, 675, 677, 684, 686, 692, 696-730, 733-735, 738-754, 757-759, 763-765, 768-782, 787-795, 799-803, 807-815, 829-834, 853-859, 863-870, 874, 879, 908-909, 941-958, 969-1000, 1004, 1019-1023, 1034, 1041, 1055, 1080-1082, 1104, 1107-1109, 1112-1114, 1119, 1124, 1132-1140, 1163-1199, 1206-1224, 1243-1247, 1253-1254, 1269-1270, 1274 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizer_v2/rmsprop.py 101 76 25% 133-146, 149-156, 159-162, 171-214, 217-272, 275-281, 284-293 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/optimizers.py 434 336 23% 62-72, 88, 91, 107-121, 137-151, 159, 162-167, 171, 189-196, 199-202, 205-230, 233-240, 258-267, 270-272, 275-297, 300-307, 332-340, 343-346, 349-371, 374-380, 411-420, 423-427, 430-459, 462-469, 495-506, 509-516, 519-555, 558-567, 590-600, 604-610, 613-644, 647-655, 681-691, 694-699, 702-742, 745-753, 760-767, 772, 775, 778, 781-806, 810, 813, 816, 832, 849-865, 892-902 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/premade/__init__.py 6 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/premade/linear.py 59 39 34% 88-96, 99-127, 130-147, 150-160, 164-165 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/premade/wide_deep.py 98 75 23% 87-91, 94-109, 113-136, 140-194, 197-205, 209-215 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/preprocessing/__init__.py 14 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/preprocessing/image.py 95 29 69% 27-28, 80-87, 152-154, 230-238, 299-307 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/preprocessing/sequence.py 18 1 94% 156 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/preprocessing/text.py 19 2 89% 42-43 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/regularizers.py 65 23 65% 152, 172, 192, 215-222, 225, 244, 280, 285, 290, 302, 304-311, 315 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/hdf5_format.py 354 269 24% 43-44, 82-130, 158-217, 251-258, 272, 287-310, 316, 318, 320, 323-393, 397-404, 446, 468-473, 483-519, 527-572, 585-598, 610-613, 623-644, 661, 665, 682, 699, 729-789, 809-831, 851-856, 880 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/model_config.py 28 14 50% 29-30, 50-55, 86-90, 114-116 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/save.py 45 21 53% 39-40, 113-137, 181-192 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/base_serialization.py 33 10 70% 34, 43, 54, 74, 87-95, 106, 122, 172 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/constants.py 6 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/json_utils.py 32 19 41% 38-41, 44, 48-56, 60, 64-69 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/layer_serialization.py 74 40 46% 36, 41, 48-69, 72, 76, 81-96, 100-105, 111-119, 127, 131, 141, 144, 152, 155-160 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/load.py 460 367 20% 116-137, 143-148, 175-202, 209-215, 219, 223-234, 239-291, 295-313, 317-344, 348-363, 367-393, 401-431, 434-450, 454-466, 470-472, 486-510, 514-520, 523-539, 544-572, 577-579, 609-623, 627-646, 650-654, 662-687, 694-719, 723-725, 730-738, 745-753, 758-778, 786-791, 802-831, 835, 838-841, 848-863, 872-882, 885, 890-902, 915-922, 931-948, 953-958, 966-968, 972 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/metric_serialization.py 18 7 61% 30, 33-40, 43 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/model_serialization.py 27 11 59% 32, 35-39, 42-55, 62 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/network_serialization.py 14 5 64% 30, 33-39 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/save.py 29 14 52% 59-81 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/save_impl.py 271 210 23% 72-78, 97-116, 146-197, 201-205, 233-290, 296-302, 309-316, 320-323, 338-363, 375-397, 406-422, 427-434, 437-441, 445-448, 452, 457-491, 495-504, 509-527, 534-537, 540-542, 545-547, 564-567, 572-576, 582-586, 590-594, 603-607, 614-616, 624-626 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/serialized_attributes.py 78 34 56% 145-154, 158-160, 165, 171, 177, 183-186, 190-203, 207-218 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model/utils.py 112 88 21% 56-96, 101-113, 117-120, 125-128, 150-199, 214-220, 224-230, 234-239, 243-248 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saved_model_experimental.py 135 89 34% 133-145, 151-155, 160-163, 168-221, 226-227, 231, 255-326, 331-361, 371, 416-430 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/saving/saving_utils.py 138 110 20% 48-53, 77-87, 91, 112-142, 147-191, 197-199, 204-233, 245-264, 270-275, 280-285, 291-307 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/all_utils.py 26 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/conv_utils.py 172 152 12% 29-48, 68-87, 103-113, 128-137, 160-186, 190-197, 201-208, 227-233, 279-309, 358-400, 439-456, 475-482 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/data_utils.py 425 321 24% 56-57, 62-64, 69-104, 111-114, 133-160, 214-282, 286-294, 316-325, 342-350, 357-367, 370, 373, 376-384, 389-393, 453, 462, 467, 471-472, 485-486, 506-514, 519-525, 531-533, 538, 559-645, 662, 689-715, 718, 728-738, 743, 753-759, 762-763, 768, 780, 791, 807-808, 819-826, 831-833, 837-860, 872-880, 894-907, 923, 946-947, 958-964, 968-974, 987-1013 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/generic_utils.py 363 275 24% 72-73, 76-79, 82-83, 114, 135, 140, 167-189, 207-210, 216-221, 251-257, 263-296, 301-305, 314-347, 356, 360-382, 386, 388, 392, 397-402, 415-426, 441-474, 490-493, 518-540, 553-675, 678, 691-692, 717-739, 754-756, 766, 774, 779-781, 792, 797 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/io_utils.py 84 52 38% 32-33, 84-99, 102, 105-134, 143, 152, 161, 170, 182-185, 201-209 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/layer_utils.py 202 85 58% 50, 55, 62-69, 79-90, 136, 152-162, 205-208, 222-223, 228, 262, 287-294, 310-326, 345-357, 382-396, 400-405 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/losses_utils.py 58 39 33% 48-49, 54-55, 61-67, 91-112, 117-121, 137-148 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/metrics_utils.py 216 159 26% 75-93, 119-149, 157-166, 170-173, 179-182, 199-204, 227-234, 296-456, 472-475, 495-539 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/mode_keys.py 5 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/multi_gpu_utils.py 82 65 21% 31, 35-36, 157-266 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/np_utils.py 26 16 38% 49-61, 76-78 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/tf_utils.py 203 105 48% 61-64, 83-91, 95-99, 116-152, 178, 181, 226, 231, 248, 251, 266-295, 319, 345, 352, 355-356, 359, 392, 397-404, 408, 427-428, 452, 458-462, 467-472, 478, 481, 485, 490-496, 521 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/version_utils.py 34 4 88% 69, 79-85 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/utils/vis_utils.py 150 125 17% 45-53, 57-59, 64-65, 98-249, 278-300 /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/wrappers/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/wrappers/scikit_learn.py 106 77 27% 75-77, 88-106, 117-119, 130-132, 150-168, 181-187, 214-223, 240-242, 263-270, 293-308, 332-333, 351-355 /usr/local/lib/python3.8/dist-packages/tensorflow/python/layers/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/layers/base.py 218 171 22% 105-110, 148, 153, 195-234, 244-246, 250-258, 262-269, 273-279, 282-294, 300-302, 305-314, 376-481, 507-552, 555-569, 573, 578, 582-593 /usr/local/lib/python3.8/dist-packages/tensorflow/python/layers/convolutional.py 84 21 75% 98, 198-218, 297, 404-424, 504, 612-632, 717, 829, 947-971, 1072-1096, 1164, 1260-1279, 1344, 1434-1453 /usr/local/lib/python3.8/dist-packages/tensorflow/python/layers/core.py 39 9 77% 98, 173-187, 219, 226, 270-271, 331-332 /usr/local/lib/python3.8/dist-packages/tensorflow/python/layers/layers.py 46 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/layers/normalization.py 22 4 82% 147, 172, 312-336 /usr/local/lib/python3.8/dist-packages/tensorflow/python/layers/pooling.py 78 30 62% 50-52, 90-95, 120-122, 160-165, 194-196, 235-238, 267-269, 308-311, 342-344, 385-388, 419-421, 460-463 /usr/local/lib/python3.8/dist-packages/tensorflow/python/layers/utils.py 129 109 16% 28-47, 67-86, 90-95, 99-103, 119-129, 144-153, 168-175, 197-200, 219-227, 232-233, 238-243, 260-285 /usr/local/lib/python3.8/dist-packages/tensorflow/python/lib/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/lib/io/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/lib/io/file_io.py 257 108 58% 58, 66, 71, 76, 84, 120, 139-165, 169-170, 174-181, 189-191, 202, 205-208, 211, 220-221, 232, 316-320, 333-334, 350, 366-374, 396, 412, 458, 474, 526-535, 589-590, 610-614, 653, 681, 701-729, 782-790, 808-814 /usr/local/lib/python3.8/dist-packages/tensorflow/python/lib/io/python_io.py 5 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/lib/io/tf_record.py 81 48 41% 90-99, 114-125, 129-149, 170-171, 212, 294-298, 313, 317, 321 /usr/local/lib/python3.8/dist-packages/tensorflow/python/module/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/module/module.py 96 58 40% 107-121, 130, 135-139, 154, 169, 193, 249-252, 287-291, 295, 299, 303, 310, 314, 326-378 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/array_grad.py 573 409 29% 44, 50, 72-212, 218, 228, 247-260, 266-285, 301-305, 319, 324-329, 337, 342, 347, 352, 358, 364-368, 374-382, 389-399, 407-424, 430-460, 466-500, 505-507, 516, 525, 531-538, 552-564, 569-585, 593-615, 627-687, 692-700, 705-713, 719, 728, 737, 742, 747, 755, 767, 773, 778, 784-785, 791-792, 810-832, 842-854, 864-865, 876-877, 882-883, 889-890, 898, 906-907, 915, 923-928, 934-939, 947-948, 953-954, 959, 964, 970, 975-1027, 1032-1090, 1095-1097, 1102-1107, 1112-1115, 1120-1123, 1128-1130, 1135-1150 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/array_ops.py 1121 797 29% 193-195, 277, 341-344, 426, 475, 503, 530, 576, 602, 620-630, 649, 683, 715, 732-753, 787, 802-811, 825-836, 840, 902-973, 1037, 1137-1178, 1224, 1270-1277, 1328-1342, 1357-1393, 1407-1414, 1419-1425, 1446-1455, 1501-1511, 1594, 1601-1605, 1659-1693, 1746, 1786-1790, 1832, 1882, 1943-1961, 2042, 2112-2129, 2190-2210, 2368-2371, 2514-2517, 2653, 2661-2667, 2710, 2712, 2721-2723, 2728-2730, 2732, 2774, 2819, 2825-2850, 2883, 2918, 2923-2931, 2959-2981, 3023, 3092-3139, 3199, 3260-3294, 3311-3316, 3362-3392, 3404-3438, 3443-3456, 3519-3527, 3541, 3553, 3565, 3607-3650, 3661-3670, 3678, 3687, 3695, 3704, 3712, 3720-3729, 3845-3848, 3966-4009, 4016-4025, 4064-4090, 4141-4145, 4197, 4243-4251, 4340-4348, 4406-4410, 4424, 4512-4524, 4535, 4554-4560, 4589-4682, 4835-4846, 4852, 4860-4934, 4956-4975, 5007-5019, 5043-5060, 5106-5113, 5172-5184, 5307, 5350-5352, 5405, 5410-5416, 5441-5455, 5499-5565, 5571-5578, 5583-5591, 5641-5644 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/batch_ops.py 25 13 48% 79-111 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/bitwise_ops.py 13 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/boosted_trees_ops.py 144 76 47% 63-66, 74-89, 93-95, 111-126, 129, 133, 138-140, 143, 147, 150, 153-156, 159, 162, 176-190, 203-204, 214-227, 234, 238, 245-247, 250, 254-255, 259-262, 271-276, 290, 303 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/candidate_sampling_ops.py 37 12 68% 83-84, 148-149, 208-209, 299-300, 337-338, 386-387 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/check_ops.py 590 425 28% 73-78, 83-85, 91, 238-271, 285-297, 327-372, 392-402, 435, 442-455, 487, 494-506, 539, 547-560, 593, 601-614, 648, 654-658, 696, 705, 758, 810-838, 873, 879, 915, 923, 959, 966, 1003, 1012, 1037-1061, 1094, 1124-1156, 1189, 1222-1255, 1259, 1263-1269, 1294-1321, 1353, 1386-1416, 1436, 1462-1475, 1494, 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57% 27-30, 52-55, 79-83 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/custom_gradient.py 189 135 29% 64, 206, 211-214, 251-255, 258, 264-281, 288-298, 304-402, 408-454, 480-507, 551-560 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/data_flow_grad.py 51 20 61% 33-45, 53-65 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/data_flow_ops.py 622 469 25% 50-56, 64-88, 92-99, 104-112, 160-182, 200-219, 228, 233-235, 240, 245, 250, 272-293, 304-309, 334-347, 377-395, 412-419, 441-457, 484-500, 528-541, 565-573, 590-595, 606-611, 614-616, 683-706, 754-765, 818-829, 834, 840, 904-919, 974-987, 1055-1075, 1080, 1085-1087, 1106-1108, 1153-1178, 1202-1204, 1219-1221, 1233-1235, 1259-1268, 1273, 1278, 1283, 1294-1297, 1313, 1346-1356, 1375-1379, 1404-1407, 1438-1444, 1464, 1508-1509, 1540, 1564-1566, 1581-1584, 1600, 1618-1647, 1652, 1657, 1662, 1667, 1672, 1677, 1707-1757, 1764-1772, 1790-1800, 1811-1816, 1894, 1915-1933, 1936-1940, 1964-1974, 1994-2004, 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160, 165, 168, 171-175, 178-180, 189-196, 199, 202, 205, 208 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/distributions/util.py 438 377 14% 61-75, 85-86, 93-105, 118-134, 152-161, 193-242, 247, 256, 269, 274-283, 288-292, 297-299, 343-377, 430-485, 513-519, 572-581, 620-657, 686-701, 720-748, 760, 772, 784-787, 792-795, 841-910, 951-979, 1015-1047, 1114-1142, 1164-1199, 1209-1213, 1243-1280, 1308-1351, 1370-1388, 1427-1437, 1443, 1448 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/embedding_ops.py 239 200 16% 57-78, 118-249, 314-320, 373, 456-547, 626, 683, 746-826, 854-872, 877-885, 890-894 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/functional_ops.py 275 203 26% 103-161, 230, 296-355, 424, 535-683, 797, 832, 860-861, 867-884, 914-949, 977-1024, 1055-1079, 1118, 1121, 1124, 1127, 1130-1144, 1179 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_array_ops.py 5009 4493 10% 35-62, 68-79, 92-118, 124-133, 146-172, 178-187, 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_bitwise_ops.py 319 274 14% 56-95, 101-111, 147-186, 192-202, 238-277, 283-293, 348-387, 393-402, 449-488, 494-504, 524-550, 556-565, 615-654, 660-670 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_boosted_trees_ops.py 1223 1116 9% 46-80, 86-101, 121-162, 168-192, 241-285, 291-310, 362-409, 415-439, 484-532, 538-566, 588-619, 625-639, 657-681, 686-695, 715-744, 749-761, 781-805, 810-819, 833-869, 875-890, 913-953, 959-977, 996-1028, 1034-1044, 1068-1097, 1103-1113, 1134-1167, 1173-1189, 1215-1259, 1265-1286, 1308-1346, 1352-1369, 1389-1416, 1421-1434, 1452-1480, 1485-1498, 1523-1551, 1556-1567, 1586-1619, 1625-1635, 1649-1685, 1691-1706, 1727-1756, 1762-1772, 1816-1858, 1864-1881, 1934-1981, 1987-2008, 2045-2089, 2095-2115, 2156-2229, 2234-2291, 2338-2442, 2447-2533, 2547-2575, 2581-2591, 2607-2635, 2641-2651 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_candidate_sampling_ops.py 423 383 9% 65-108, 114-133, 169-209, 215-232, 314-400, 406-451, 499-549, 555-576, 624-673, 679-700, 748-799, 805-826, 874-922, 928-949 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_checkpoint_ops.py 103 84 18% 77-119, 125-142, 215-259, 265-284 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_clustering_ops.py 116 94 19% 42-68, 74-85, 113-145, 151-164, 194-221, 227-238 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_collective_ops.py 215 191 11% 38-85, 91-109, 127-173, 179-197, 215-260, 266-284, 305-368, 374-406 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_control_flow_ops.py 434 371 15% 40-68, 73-84, 98-117, 122-127, 151-190, 196-213, 228-254, 260-269, 286-312, 318-327, 354-386, 392-406, 419-445, 451-460, 474-505, 510-515, 539-564, 570, 585-599, 605, 631-650, 656, 669-683, 689, 704-723, 729, 756-770, 776, 802-829, 835-845 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_ctc_ops.py 214 186 13% 57-101, 107-127, 164-198, 204-217, 260-315, 321-345, 389-443, 449-472 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_cudnn_rnn_ops.py 910 857 6% 83-145, 151-184, 262-329, 335-364, 446-514, 520-550, 640-721, 727-765, 818-892, 898-948, 1003-1081, 1087-1137, 1183-1247, 1253-1289, 1349-1414, 1420-1456, 1519-1596, 1602-1644, 1711-1773, 1779-1812, 1886-1961, 1967-2007 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_data_flow_ops.py 3989 3627 9% 39-47, 52, 64-78, 84, 101-110, 115, 138-154, 160, 195-236, 242, 265-277, 282, 294-308, 314, 338-347, 352, 364-378, 384, 425-462, 468, 497-528, 534, 547-566, 571-577, 634-678, 684-695, 774-827, 833-857, 885-926, 932, 959-1015, 1021-1051, 1064-1078, 1084, 1096-1122, 1128-1137, 1150-1176, 1182-1191, 1206-1233, 1239-1249, 1266-1306, 1311-1334, 1351-1401, 1407-1433, 1455-1508, 1514-1541, 1558-1608, 1614-1640, 1666-1708, 1713-1740, 1762-1815, 1821-1848, 1876-1930, 1936-1965, 1982-2022, 2027-2050, 2067-2119, 2125-2152, 2175-2229, 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4936-4979, 4985-5012, 5032-5073, 5079-5100, 5125-5180, 5186-5212, 5230-5271, 5277-5297, 5312-5346, 5352-5364, 5384-5432, 5438-5463, 5493-5537, 5543-5567, 5598-5650, 5656-5682, 5699-5743, 5749-5770, 5788-5829, 5835-5855, 5870-5897, 5903-5915, 5936-5964, 5970-5981, 6000-6041, 6047-6067, 6089-6114, 6120-6135, 6149-6182, 6188-6203, 6223-6251, 6257-6268, 6281-6307, 6313-6322, 6393-6436, 6442-6465, 6478-6504, 6510-6519, 6541-6587, 6593-6618 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_debug_ops.py 422 389 8% 50-90, 96-116, 144-185, 191-211, 240-290, 296-322, 358-415, 421-451, 479-529, 535-561, 627-696, 702-739, 815-858, 864-883 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_decode_proto_ops.py 80 64 20% 102-165, 171-204 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_encode_proto_ops.py 59 44 25% 81-123, 129-149 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_experimental_dataset_ops.py 3926 3668 7% 36-78, 84-105, 134-176, 182-202, 231-280, 286-311, 327-368, 374-395, 417-459, 465-488, 509-578, 584-620, 636-687, 693-719, 735-761, 767-776, 792-818, 824-833, 852-872, 877-885, 908-951, 957-979, 999-1047, 1053-1080, 1096-1140, 1146-1167, 1196-1246, 1252-1278, 1294-1338, 1344-1365, 1387-1430, 1436-1460, 1476-1529, 1535-1562, 1578-1606, 1612-1622, 1641-1664, 1669-1678, 1701-1746, 1752-1774, 1794-1844, 1850-1877, 1918-1987, 1993-2023, 2048-2110, 2116-2144, 2159-2202, 2208-2228, 2241-2267, 2273-2283, 2298-2339, 2345-2365, 2381-2424, 2430-2451, 2490-2547, 2553-2582, 2601-2661, 2667-2696, 2709-2735, 2741-2751, 2768-2813, 2819-2840, 2855-2898, 2904-2924, 2957-3012, 3018-3045, 3087-3169, 3175-3223, 3240-3284, 3290-3311, 3331-3372, 3378-3399, 3423-3472, 3478-3503, 3522-3575, 3581-3608, 3626-3673, 3679-3702, 3718-3760, 3766-3787, 3811-3858, 3864-3887, 3906-3948, 3954-3976, 3990-4026, 4032-4047, 4060-4087, 4093-4103, 4129-4177, 4183-4205, 4222-4266, 4272-4293, 4315-4366, 4372-4394, 4409-4450, 4456-4476, 4491-4532, 4538-4558, 4599-4665, 4671-4700, 4725-4785, 4791-4818, 4833-4874, 4880-4899, 4912-4938, 4944-4953, 4981-5021, 5027-5046, 5062-5103, 5109-5129, 5162-5221, 5227-5257, 5296-5353, 5359-5387, 5400-5426, 5432-5441, 5458-5502, 5508-5529, 5544-5585, 5591-5611, 5668-5719, 5725-5752, 5797-5908, 5914-5983, 6033-6146, 6152-6222, 6239-6281, 6287-6308, 6339-6379, 6385-6405, 6429-6478, 6484-6508, 6536-6577, 6583-6605, 6625-6683, 6689-6719, 6737-6782, 6788-6811, 6827-6869, 6875-6895, 6919-6965, 6971-6993, 7030-7157, 7163-7233, 7252-7294, 7300-7321, 7335-7369, 7375-7389, 7403-7438, 7444-7459, 7473-7494, 7499-7507, 7520-7546, 7552-7562, 7588-7634, 7640-7661, 7678-7720, 7726-7746, 7768-7819, 7825-7846, 7861-7902, 7908-7927, 7942-7983, 7989-8008 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_functional_ops.py 540 492 9% 58-106, 112-138, 157-186, 192-202, 226-252, 258-269, 297-344, 350-373, 395-441, 447-471, 489-522, 528-542, 565-613, 619-643, 674-721, 727-750, 781-823, 829-849, 883-914, 920-934, 960-986, 992-1001, 1029-1073, 1079-1098 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_image_ops.py 1972 1820 8% 36-64, 70-82, 108-135, 141-151, 173-199, 205-215, 238-264, 270-280, 343-387, 393-414, 470-507, 513-532, 566-596, 602-618, 654-688, 694-711, 764-825, 831-861, 884-913, 919-931, 953-979, 985-994, 1045-1105, 1111-1140, 1172-1206, 1212-1227, 1256-1282, 1288-1298, 1329-1356, 1362-1373, 1423-1498, 1504-1543, 1560-1587, 1593-1604, 1631-1661, 1667-1679, 1736-1782, 1788-1812, 1830-1860, 1866-1878, 1926-1967, 1973-1992, 2014-2053, 2059-2068, 2097-2134, 2140-2157, 2197-2230, 2236-2250, 2292-2322, 2328-2340, 2384-2416, 2422-2435, 2489-2529, 2535-2552, 2616-2657, 2663-2677, 2719-2751, 2757-2771, 2803-2843, 2849-2869, 2904-2943, 2949-2958, 2987-3021, 3027-3043, 3074-3105, 3111-3124, 3146-3184, 3190-3207, 3228-3266, 3272-3289, 3311-3349, 3355-3372, 3393-3432, 3438-3455, 3475-3514, 3520-3537, 3557-3596, 3602-3620, 3709-3789, 3795-3838, 3927-4002, 4008-4048, 4066-4104, 4110-4128, 4146-4185, 4191-4209 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_io_ops.py 1163 1009 13% 46-85, 91, 119-181, 187-217, 238-260, 266, 286-320, 326-340, 358-379, 385, 405-444, 450-459, 486-512, 517-527, 543-582, 588-597, 613-627, 633, 648-674, 680-690, 703-717, 723, 735-763, 769-779, 805-820, 826, 854-870, 876, 904-933, 939-950, 976-1004, 1010-1020, 1033-1040, 1045, 1057-1076, 1081-1087, 1106-1114, 1119, 1137-1157, 1162-1169, 1185-1199, 1205, 1220-1246, 1252-1262, 1301-1335, 1341-1355, 1387-1422, 1428-1443, 1487, 1493-1515, 1522, 1534, 1559-1579, 1584-1592, 1635-1657, 1662-1671, 1696-1718, 1723-1732, 1749-1776, 1782-1793, 1807-1834, 1840-1850, 1869-1895, 1901, 1919-1959, 1965-1983, 2003-2030, 2036, 2055-2096, 2102-2120, 2141-2163, 2169, 2189-2223, 2229-2243, 2264-2296, 2301-2308 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_linalg_ops.py 1226 1097 11% 33-59, 65-74, 88-114, 120-130, 143-169, 175-185, 199-229, 235-247, 262-293, 299-312, 328-360, 366-380, 396-431, 437-454, 467-493, 499-508, 529-560, 566-578, 601-639, 645-661, 692-731, 737-746, 769-795, 801-811, 848-880, 886-899, 991-1024, 1030-1045, 1076-1103, 1109-1118, 1161-1205, 1211-1223, 1244-1283, 1289-1298, 1311-1337, 1343-1352, 1382-1425, 1431-1443, 1473-1499, 1505-1514, 1543-1587, 1593-1606, 1663-1694, 1700-1714, 1746-1785, 1791-1800, 1873-1907, 1913-1929, 1968-2012, 2018-2030, 2052-2078, 2084-2093, 2129-2160, 2166-2178, 2221-2258, 2264-2280, 2306-2333, 2339-2349, 2379-2412, 2418-2431 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_list_ops.py 716 641 10% 42-74, 80-91, 119-155, 161-174, 189-218, 224-235, 270-304, 310-322, 339-367, 373-384, 403-431, 437-448, 471-502, 508-520, 540-571, 577-589, 605-631, 637-646, 675-707, 713-724, 744-771, 777-787, 801-828, 834-845, 865-897, 903-914, 932-958, 964-974, 998-1026, 1032-1044, 1067-1096, 1102-1114, 1142-1171, 1177-1190, 1210-1237, 1243-1254, 1277-1305, 1311-1323, 1345-1381, 1387-1401 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_logging_ops.py 492 436 11% 48-63, 68-78, 108-142, 148-162, 193-225, 231-245, 267-293, 299-309, 364-400, 406-422, 445-476, 482-496, 519-560, 566-586, 604-630, 635-647, 665-691, 697-707, 729-773, 779-802, 820-848, 854-865, 884-923, 929-937 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_lookup_ops.py 714 631 12% 47-78, 84, 110-157, 163-184, 200-208, 213, 247-266, 271, 305-341, 346-363, 379-399, 404-412, 434-452, 458, 479-510, 516-527, 548-564, 570, 590-618, 624-635, 653-661, 666, 683-703, 708-716, 734-742, 747, 764-784, 789-797, 814-834, 839-846, 859-873, 879, 891-917, 923-932, 970-1015, 1021, 1059-1128, 1134-1168, 1195-1227, 1233, 1258-1296, 1302, 1327-1383, 1389-1414, 1441-1489, 1495-1516 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_manip_ops.py 46 31 33% 64-92, 98-109 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_math_ops.py 5995 5342 11% 37-63, 69-78, 103-136, 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269-278, 330-356, 362-371, 389-422, 428-442, 467-479, 486-488, 497-507, 538-579, 585-603, 618-647, 653-664, 701-721, 726-734, 771-791, 796-804, 841-861, 866-874, 911-931, 936-944, 981-1001, 1006-1014, 1051-1071, 1076-1084, 1111-1131, 1136-1144, 1173-1203, 1209-1226, 1247-1265, 1271-1280, 1303-1332, 1338-1350 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_rnn_ops.py 350 306 13% 84-130, 136-157, 220-257, 263-275, 338-375, 381-393, 460-501, 507-525, 597-625, 631-641, 753-782, 788-798, 866-912, 918-938, 987-1022, 1028-1039 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_script_ops.py 136 104 24% 39-80, 86-104, 128-140, 144, 152, 154-157, 165-179, 194-226, 232-247 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_sdca_ops.py 322 287 11% 37-76, 82-91, 170-329, 335-421, 497-617, 623-709, 730-751, 756 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_sendrecv_ops.py 97 79 19% 42-91, 97-116, 138-173, 178-193 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_set_ops.py 187 160 14% 56-94, 100-116, 167-208, 214-232, 258-292, 298-312, 378-423, 429-449 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_sparse_ops.py 1272 1150 10% 68-108, 114-132, 169-209, 215-232, 298-327, 333-343, 409-439, 445-455, 484-519, 525-539, 559-594, 600-614, 663-695, 701-716, 750-781, 787-799, 870-924, 930-965, 1040-1103, 1109-1143, 1173-1200, 1206-1218, 1242-1269, 1275-1287, 1315-1342, 1348-1360, 1427-1456, 1462-1474, 1505-1533, 1539-1550, 1586-1621, 1627-1642, 1686-1723, 1729-1744, 1780-1815, 1821-1836, 1880-1917, 1923-1938, 1973-2002, 2008-2019, 2061-2089, 2095-2106, 2153-2181, 2187-2200, 2225-2256, 2262-2274, 2309-2336, 2342-2353, 2387-2418, 2424-2438, 2472-2503, 2509-2523, 2572-2607, 2613-2630, 2652-2680, 2686-2698, 2734-2773, 2779-2799, 2845-2882, 2888-2904, 2985-3025, 3031-3049 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_special_math_ops.py 172 145 16% 33-59, 65-74, 87-113, 119-128, 141-167, 173-182, 195-221, 227-236, 249-275, 281-290 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_spectral_ops.py 714 630 12% 33-59, 65-74, 87-113, 119-128, 141-167, 173-182, 195-221, 227-236, 249-275, 281-290, 303-329, 335-344, 364-403, 409-418, 438-477, 483-492, 512-551, 557-566, 586-625, 631-640, 660-699, 705-714, 734-773, 779-788, 819-849, 855-868, 900-930, 936-949, 981-1011, 1017-1030, 1058-1089, 1095-1108, 1137-1168, 1174-1187, 1216-1247, 1253-1266 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_state_ops.py 513 432 16% 46-69, 75, 96-114, 120, 141-159, 165, 181-197, 203, 226-242, 248, 263-277, 283, 300-329, 335-346, 403-427, 432-444, 501-525, 530-542, 602-627, 632-645, 689-709, 715, 756-776, 782, 825-845, 851, 894-914, 920, 961-981, 987, 1044-1064, 1070, 1129-1149, 1155, 1213-1233, 1239, 1282-1302, 1308, 1355-1375, 1381, 1413-1435, 1441, 1456-1482, 1488, 1512-1538, 1544 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gen_user_ops.py 43 28 35% 32-57, 63-71 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gradient_checker.py 145 117 19% 39-45, 49-54, 83-132, 160-193, 202-208, 221-242, 254-268, 321-335, 339-345, 393-395 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gradient_checker_v2.py 140 116 17% 37-43, 59-64, 78-93, 110-127, 150-197, 221-261, 266-281, 287-293, 332-335, 351-355 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gradients.py 12 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gradients_impl.py 59 25 58% 168-169, 298-299, 342-357, 392-424, 433 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/gradients_util.py 446 380 15% 61-69, 97-133, 137, 162-227, 231-234, 250-254, 279-289, 295-299, 303, 308-318, 323-355, 362-374, 383, 388-392, 405-411, 428, 444-457, 471-476, 490-716, 721-728, 734-766, 771-781, 786-805, 810-813, 817-821, 826-838, 846-867, 932-987 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/histogram_ops.py 28 13 54% 77-100, 146-149 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/image_grad.py 91 69 24% 39-50, 64-69, 84-91, 105-113, 131-156, 167, 188-381 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/image_ops.py 51 32 37% 195-203, 228-239, 245-273 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/image_ops_impl.py 1010 802 21% 75-81, 93, 108-113, 133-150, 171, 193, 212-236, 258, 277-301, 315-320, 360, 401, 422-447, 481, 515, 537-546, 581-594, 610-625, 641-657, 706-715, 772-847, 907-956, 990-1036, 1070-1155, 1183-1255, 1315-1333, 1470-1511, 1523-1590, 1628-1631, 1668-1671, 1698-1717, 1748-1752, 1784-1792, 1830-1843, 1885-1899, 1945-1963, 2012-2062, 2086-2097, 2122-2132, 2168-2175, 2230-2241, 2277-2289, 2327-2339, 2377-2385, 2426-2437, 2455-2457, 2471-2473, 2540, 2586-2656, 2694-2728, 2823-2824, 2930-2931, 2988-2992, 3064-3079, 3129-3133, 3175-3179, 3211-3215, 3238-3242, 3278-3282, 3305-3309, 3329-3354, 3393-3408, 3444-3466, 3471-3483, 3519-3565, 3627-3640, 3690-3771, 3826-3844, 3861-3885, 3893, 3906, 3919, 4036, 4053-4055, 4137, 4222, 4295-4300, 4354-4356, 4408, 4427 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/init_ops.py 509 330 35% 68, 76, 97, 113, 117, 132-134, 137, 215-222, 225-229, 237, 260-263, 266-268, 272, 300-303, 306-308, 312, 346-349, 352-354, 358, 407-409, 412-427, 431, 480, 482, 487, 495-518, 522, 563-565, 568-595, 598, 626-628, 631-663, 666, 688-690, 693, 696, 708-715, 726-733, 758-771, 785, 803-813, 828-845, 860-877, 903-913, 926, 939-944, 959-973, 988-1002, 1028-1041, 1056, 1075-1093, 1109-1129, 1144-1165, 1185-1186, 1189-1201, 1204, 1236, 1265, 1269, 1318, 1345, 1370, 1394, 1410-1425, 1443 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/init_ops_v2.py 241 105 56% 59, 67, 88-89, 168-171, 239-243, 257-259, 263, 300-303, 316-319, 323, 364-367, 380-381, 385, 429-432, 445-446, 450, 509, 511, 515, 518, 541, 544, 546, 551-552, 554-555, 561, 612-614, 628-650, 653, 684, 698-708, 711, 757, 796, 803, 864, 907, 947, 987, 1004, 1006, 1013-1017, 1037, 1048, 1054-1058, 1064, 1072-1076 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/initializers_ns.py 24 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/inplace_ops.py 41 16 61% 53-64, 90, 116, 142, 160-161, 191, 221, 251 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/io_ops.py 120 54 55% 68-71, 93-94, 131-137, 142, 161-171, 193-206, 224-228, 240-244, 259-262, 278-282, 287, 298-301, 337-338, 369-371, 410-417, 446-451, 479-481, 511-512 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/adjoint_registrations.py 50 18 64% 37, 48, 54, 60-64, 76-80, 92, 106, 118-123, 134 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/cholesky_registrations.py 31 6 81% 36, 46, 57, 70, 83, 96 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/inverse_registrations.py 68 31 54% 40, 51, 57, 68, 74, 87, 132-185, 200, 213, 225 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linalg.py 36 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linalg_impl.py 400 323 19% 95-97, 126-128, 135-145, 150-161, 166-178, 183-203, 208-229, 262-339, 439-490, 496-538, 591-618, 623-635, 657-673, 746-802, 848-896, 949-959, 1000-1036, 1041-1068, 1073-1094 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator.py 387 259 33% 188-213, 218-222, 227, 232, 238, 242, 246, 250, 257-264, 269, 282, 288, 303-308, 322, 338-339, 344-349, 365-366, 381-382, 387-391, 404-407, 424-425, 430-435, 448-451, 468-469, 474-479, 483-493, 500-508, 527-528, 532-544, 560-561, 564-568, 586-587, 591-592, 598, 629-653, 656, 659-661, 690-696, 699-704, 718-723, 726-733, 747-752, 756-763, 768-771, 814-846, 850-852, 893-900, 914-917, 937-945, 966-970, 974-986, 990-991, 995, 1022-1023, 1026, 1039-1040, 1044, 1056-1059, 1062, 1078-1081, 1084-1093, 1105-1106, 1109, 1122-1127, 1137, 1142, 1155, 1161, 1166-1169, 1174-1176, 1190-1202, 1212-1215, 1220 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_addition.py 160 105 34% 99-138, 144-149, 168-187, 195-211, 217-223, 233-235, 253, 258, 264, 280-290, 301-302, 307-317, 330-331, 334, 346-347, 350-355, 367, 371-375, 412-424 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_adjoint.py 72 39 46% 116-155, 160, 163, 166, 169, 173-174, 178-179, 183, 187, 190-192, 195, 198-200, 203, 207, 210-212, 215, 218-221, 224 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_algebra.py 112 49 56% 37-48, 53, 58, 63, 68, 73, 90-96, 113-119, 138-144, 163-169, 186-192, 228, 231, 270, 273, 315, 318, 361, 364, 404, 407 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_block_diag.py 153 119 22% 156-215, 219, 223-238, 242-260, 263-273, 276-279, 282-285, 288-299, 302-308, 311-314, 317-341, 344, 348, 352, 356-362, 378-386 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_block_lower_triangular.py 191 152 20% 224-241, 250-252, 259-283, 290-301, 304-310, 314-318, 324, 328-344, 348-367, 370-417, 420-425, 428-431, 460-510, 513-520, 523-526, 529-550, 553, 557-563, 579-587 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_circulant.py 204 144 29% 93-126, 130-138, 171, 177, 180-186, 190, 194, 210-224, 239-260, 272-273, 285-286, 300-302, 305-321, 324-331, 345-350, 356, 366-368, 373, 381-402, 405-425, 428-430, 433-436, 439-450, 455-478, 490-512, 747, 758, 927, 1077, 1089-1095 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_composition.py 86 62 28% 147-187, 191, 195-211, 215-233, 239-248, 251-254, 257-260, 270-279 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_diag.py 83 49 41% 143-168, 172-173, 178-179, 182-184, 188, 191, 196-205, 210, 217-220, 223-224, 227, 230-234, 237-240, 243, 246, 249-251, 254, 257-258 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_full_matrix.py 38 17 55% 137-151, 155-172, 177, 180, 183, 187, 190 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_householder.py 86 52 40% 126-156, 160-162, 168-169, 172-174, 177, 180, 185, 200-207, 211-212, 219, 223, 228, 231-236, 240-243, 247-254, 258, 262 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_identity.py 234 171 27% 48-74, 79-83, 87, 91-98, 255-292, 295-301, 304-308, 311, 314, 317, 322-350, 354-358, 361, 364, 367, 371-380, 384, 396-400, 403, 406, 411-437, 442-470, 599-630, 634-638, 641-644, 647, 651, 656-657, 664-668, 671-675, 678, 681, 685-689, 693-702, 706, 718-731, 734, 739, 747 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_inversion.py 52 27 48% 117-168, 173, 176, 179, 182, 185, 188, 191, 194, 197, 200, 203, 206 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_kronecker.py 205 169 18% 38, 46, 55-62, 171-231, 235, 239-257, 260-277, 317-387, 399-405, 409-415, 419-422, 433-504, 507-522, 525-544, 550-563, 566-570, 575-579 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_low_rank_update.py 148 108 27% 185-263, 268-281, 286-294, 300, 305, 310, 315, 320, 325, 328-331, 334-340, 344-360, 363-374, 380-394, 397-435, 442-448 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_lower_triangular.py 49 22 55% 141-159, 164-165, 171, 175, 178, 181, 184, 189, 193, 196, 200-201, 205, 208 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_permutation.py 81 48 41% 143-156, 166-178, 183-184, 187-189, 192, 195-196, 199-220, 226, 231, 234-235, 240-241, 247, 251 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_toeplitz.py 82 50 39% 142-159, 163-170, 176-178, 181-187, 190, 210-224, 229, 234-235, 239-263, 267, 271, 275-278 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_tridiag.py 122 87 29% 175-190, 199-213, 216-230, 236-266, 270-287, 290-294, 299-331, 334-341, 344-359, 369, 373 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_util.py 150 122 19% 105-116, 122-125, 130-135, 151, 160-161, 182-187, 201-209, 228-236, 241-243, 251-255, 311-354, 359-373, 383-467, 491-502 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/linear_operator_zeros.py 157 118 25% 179-232, 235-241, 244-248, 251, 256, 261, 266-294, 297-320, 323-326, 330-333, 336, 348, 353-399, 404-432, 437-441, 445, 449-456, 459 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/matmul_registrations.py 65 28 57% 37-50, 65-66, 73-74, 82, 102-105, 112-115, 125, 142, 159, 175, 191, 209 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/registrations_util.py 29 21 28% 27-44, 49-62, 71-78, 86-91 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/solve_registrations.py 55 22 60% 37-50, 67, 75-76, 83-84, 92, 112, 129, 146, 162, 181 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/sparse/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/sparse/conjugate_gradient.py 52 37 29% 76-136 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/sparse/gen_sparse_csr_matrix_ops.py 624 562 10% 48-77, 83-95, 109-137, 143-154, 177-207, 213-224, 239-266, 272-283, 303-329, 335-347, 399-459, 465-495, 518-544, 550-560, 573-599, 605-614, 677-703, 709-719, 739-766, 772-782, 797-825, 831-843, 937-965, 971-983, 1083-1133, 1139-1164, 1183-1215, 1221-1234, 1248-1275, 1281-1291, 1307-1335, 1341-1353 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/sparse/sparse.py 8 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/sparse/sparse_csr_matrix_grad.py 127 101 20% 30-34, 40-41, 65-66, 73, 80-81, 95-169, 175-222, 231-233 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg/sparse/sparse_csr_matrix_ops.py 157 96 39% 56, 61-69, 74, 80-87, 105-116, 124-144, 181-241, 253, 257, 261, 265, 269, 273, 277, 281, 286, 289, 294, 301, 307, 310, 330-352, 357, 360-370, 373, 376-377 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg_grad.py 389 345 11% 53-54, 61-366, 372-378, 392-443, 449-454, 462-480, 486-510, 516-524, 537-601, 609-633, 639-675, 690-811, 816-819, 824-827, 833-848, 854-867, 881-898, 917-937 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg_ops.py 166 121 27% 65-79, 139-140, 181-186, 227, 293-367, 393-398, 419-424, 446-447, 469-470, 535-540, 607, 682-761 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/linalg_ops_impl.py 35 24 31% 42-80 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/list_ops.py 141 87 38% 49-52, 60, 68, 76, 85, 97, 110-114, 127, 139, 148, 161-170, 176, 184-189, 194, 201-209, 214-217, 227-243, 249-259, 265-274, 279-281, 287-294, 301-311, 317-325, 350-371 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/logging_ops.py 147 89 39% 48, 112, 120-124, 129, 258-375, 383, 387-390, 426-429, 487-491, 542-552, 583-586, 606-610, 624-634, 667-670 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/lookup_ops.py 638 452 29% 63, 81-84, 99-103, 117-119, 122, 127, 132, 137, 141, 145, 165-179, 182, 187, 198-199, 217-236, 243, 279-291, 294-303, 307, 319-325, 364, 372, 385-386, 391, 396, 400, 405-411, 428-445, 461-467, 587-626, 641-654, 658-669, 712, 765, 807-814, 818-820, 896-933, 936-938, 941-944, 948-951, 956, 960-962, 966, 970-975, 979-988, 1005-1034, 1106-1144, 1147-1149, 1152-1155, 1159-1161, 1165, 1169-1174, 1191-1215, 1223-1226, 1311-1347, 1408-1446, 1520-1537, 1588-1599, 1645-1667, 1673-1694, 1698, 1709-1711, 1729-1737, 1756-1762, 1781-1789, 1801-1806, 1810, 1820-1826, 1829-1833, 1903-1930, 1936-1950, 1954, 1965-1967, 1986-1993, 2012-2020, 2039, 2057-2066, 2084, 2096-2102, 2106, 2116-2122, 2125-2129 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/losses/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/losses/loss_reduction.py 16 1 94% 68 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/losses/losses.py 6 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/losses/losses_impl.py 237 180 24% 61, 71-72, 86-87, 112-129, 134-135, 174-203, 245-255, 296-311, 348-361, 414-437, 480-493, 548-591, 633-643, 690-707, 756-778, 805-830, 873-887 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/losses/util.py 88 59 33% 58-121, 139-145, 158-175, 189-190, 204, 217, 231-235, 264-267 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/manip_grad.py 12 4 67% 28-31 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/manip_ops.py 12 1 92% 30 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/map_fn.py 85 63 26% 149-287, 417 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/math_grad.py 1177 911 23% 37, 42-43, 48-49, 56-64, 91-136, 144, 152-214, 219-235, 241, 246, 252-266, 277-315, 321, 327-334, 340-341, 349-350, 358-359, 366-367, 374-375, 382-383, 389-399, 405, 411, 426-445, 452-464, 470, 476, 482, 504-530, 535-536, 542, 548-549, 555-556, 561-566, 571-576, 581-586, 591-592, 597-605, 611-612, 618-625, 631-637, 643-650, 656-662, 668-674, 680-690, 697-707, 714-724, 731-734, 740-743, 749-752, 758-761, 767-773, 779-785, 790-793, 799-803, 809-814, 820-822, 829-831, 838-844, 850-857, 863-866, 872-874, 880-882, 888-890, 896-901, 907-914, 920-938, 944-963, 970-971, 978-1004, 1014-1032, 1040-1058, 1065-1068, 1073-1077, 1083-1084, 1090-1093, 1099-1102, 1108-1116, 1122-1132, 1138-1148, 1154-1160, 1166-1173, 1180, 1185-1189, 1197-1225, 1231-1259, 1265-1300, 1306-1315, 1324-1340, 1350, 1356-1366, 1371, 1377-1393, 1404-1420, 1431-1488, 1492-1498, 1503-1535, 1541, 1547, 1553-1587, 1605-1608, 1614-1633, 1638-1649, 1654-1665, 1671-1698, 1705-1746, 1755, 1760, 1765, 1771, 1777-1797, 1803-1835, 1845-1850, 1857-1858, 1864-1865, 1871-1878, 1884, 1890, 1899-1908, 1913-1915, 1920-1923, 1931-1940, 1945-1974, 1980-1988 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/math_ops.py 1023 622 39% 138-140, 171-173, 187-189, 224-226, 264-268, 276, 292-293, 296, 299, 302, 327-332, 381, 389, 399, 410, 436, 461-471, 477-478, 505-506, 541-552, 580-591, 619-625, 653-658, 693-698, 725-729, 775-792, 814-825, 844, 863, 882, 901, 920, 939, 958, 985-997, 1000-1002, 1008-1010, 1015-1016, 1054-1070, 1075-1090, 1107-1118, 1151, 1177, 1195-1198, 1215-1223, 1259-1260, 1273-1276, 1285-1288, 1354, 1399, 1445, 1481, 1486-1494, 1499-1505, 1564-1592, 1597-1598, 1609-1627, 1632, 1637-1640, 1692-1697, 1741, 1750-1751, 1792, 1864-1873, 1928-1934, 2001-2006, 2061-2062, 2110-2114, 2157-2160, 2191-2192, 2236-2241, 2281-2286, 2322-2323, 2367-2372, 2419, 2428-2429, 2480-2485, 2525-2526, 2579-2584, 2624-2625, 2680-2685, 2726-2745, 2787-2789, 2912-2983, 3075-3083, 3096-3106, 3113-3123, 3142-3147, 3166-3182, 3223-3239, 3282-3310, 3317, 3366-3368, 3387-3389, 3447-3464, 3497, 3565-3567, 3618-3620, 3673-3675, 3709-3720, 3734-3748, 3765-3778, 3819-3824, 3868-3873, 3941-3949, 4017, 4056-4064, 4102, 4132-4140, 4174, 4232-4361, 4416-4431, 4460-4463, 4499-4500, 4517-4518, 4532-4533, 4560, 4597, 4643, 4669-4670, 4694 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/metrics.py 5 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/metrics_impl.py 796 681 14% 76, 111-161, 180-209, 226-228, 255-277, 282-311, 358-393, 446-457, 508-621, 625-626, 720-859, 912-919, 972-994, 1045-1099, 1154-1202, 1257-1270, 1324-1331, 1382-1417, 1465-1471, 1502-1518, 1556-1569, 1612-1626, 1665-1678, 1721-1735, 1774-1787, 1830-1844, 1883-1896, 1939-1953, 2006-2048, 2103-2129, 2180-2222, 2226-2232, 2246-2265, 2286-2288, 2323-2334, 2375-2385, 2417-2429, 2470-2480, 2558-2565, 2630-2657, 2710-2735, 2788-2806, 2868-2908, 2930-2962, 2985-3000, 3035-3089, 3142-3182, 3199-3220, 3236, 3306-3322, 3360-3372, 3413-3423, 3481-3512, 3526, 3613-3620, 3690-3750 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/nccl_ops.py 85 57 33% 47, 64-72, 93, 110, 127, 146, 163-170, 183-186, 202-207, 212-236, 241-251, 257-260, 264-267 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/nn.py 16 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/nn_grad.py 344 217 37% 43, 71, 105, 127, 148-149, 171-172, 194-195, 216, 227, 238, 250, 266, 300-302, 319-320, 342-346, 364-384, 406-407, 413, 418-419, 426-427, 434, 439-440, 446-448, 453-455, 461, 466, 471, 480-484, 489, 494-495, 510-511, 522-536, 548-562, 568-582, 608, 630, 644-648, 656, 667, 678, 690-692, 704-705, 717, 733-735, 751, 782, 804, 830-833, 861-908, 913, 918, 923, 954-1002, 1020-1040, 1045, 1050-1051, 1065, 1081-1105, 1126-1138 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/nn_impl.py 390 293 25% 86-109, 161-186, 240, 299-315, 382-383, 419-439, 471-477, 495-500, 520-536, 584-589, 616-617, 642-646, 661-667, 690-708, 763-794, 852, 920-957, 1021, 1061-1088, 1116, 1137-1149, 1187-1214, 1250, 1271-1328, 1347, 1415-1421, 1498-1545, 1594-1597, 1641, 1660-1663, 1726-1848, 1941, 2046-2063, 2142, 2240-2258 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/nn_ops.py 1086 861 21% 62-81, 130-142, 169-214, 220, 231, 296-299, 317-319, 468-482, 512-588, 593-635, 638, 646-658, 686-717, 739-760, 887-890, 909, 935-1001, 1030-1075, 1085, 1095-1106, 1200-1274, 1371, 1523, 1545-1566, 1637-1664, 1721, 1783-1817, 1910, 1997-2006, 2071-2072, 2133-2136, 2202-2206, 2274-2283, 2343-2448, 2460-2462, 2481-2482, 2549-2551, 2614-2623, 2700-2714, 2729, 2769-2774, 2785-2794, 2821-2824, 2853-2856, 2861, 2882-2884, 2910-2916, 2921-2943, 2968-3022, 3062-3065, 3090-3092, 3119-3122, 3147-3149, 3154-3158, 3218, 3277-3338, 3405-3413, 3472-3539, 3590, 3621-3647, 3680-3691, 3722-3730, 3763-3781, 3806-3814, 3848-3874, 3910-3923, 3954-3972, 3996-4004, 4039-4047, 4110-4116, 4137-4144, 4160-4172, 4179-4190, 4198-4208, 4214-4217, 4235-4240, 4259-4264, 4269-4289, 4330-4343, 4419-4464, 4494, 4524, 4608, 4685-4693, 4758, 4814-4820, 4828-4838, 4888-4890, 4954-4959, 4999-5000, 5005 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/numerics.py 39 21 46% 46-49, 64-69, 99-122 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/op_selector.py 193 169 12% 26-29, 34-40, 54-59, 72-77, 96-115, 126-131, 148-161, 174-175, 188-194, 213-226, 230-234, 267-308, 319-321, 325, 339-363, 393-419 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/optional_grad.py 12 2 83% 27, 33 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/parallel_for/__init__.py 9 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/parallel_for/control_flow_ops.py 165 134 19% 64-106, 111-114, 122-132, 182-201, 206-219, 224-317, 398-407 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/parallel_for/gradients.py 57 45 21% 48-80, 112-147 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/parallel_for/pfor.py 1990 1462 27% 75-80, 103-111, 126-225, 229, 234, 239-242, 247, 252, 257, 261-265, 269, 274, 297-340, 344-354, 369-396, 400-464, 474-483, 487-514, 520-559, 604-679, 694-696, 705-711, 721-742, 746, 750, 753-754, 757-768, 771-781, 785, 789, 792, 796, 799-800, 906, 915-919, 946-953, 957-982, 990-993, 997, 1001, 1022-1060, 1075, 1088, 1101, 1105-1106, 1167-1184, 1188-1192, 1224-1239, 1243-1257, 1262-1266, 1279-1292, 1296-1297, 1300-1302, 1306-1329, 1332-1516, 1521, 1526, 1530, 1534, 1544, 1556-1558, 1563-1565, 1570-1572, 1580-1582, 1587-1589, 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_array_ops.py 187 158 16% 92-201, 230-243, 273-305, 332-373, 431-448, 474-477, 502-506, 520-528, 574-634, 660-689 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_batch_gather_ops.py 46 34 26% 64-124 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_batch_gather_with_default_op.py 61 44 28% 69-141, 147-183 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_concat_ops.py 110 87 21% 67-70, 115-118, 136-202, 219-238, 253-289, 295-297, 302-310, 315-320 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_config.py 6 1 83% 33 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_conversion_ops.py 58 39 33% 36-39, 49-52, 57, 64-106, 113-137, 141, 145 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_dispatch.py 243 116 52% 82, 90-102, 114, 119-160, 175, 182-231, 246, 252-253, 258-261, 264-284, 417, 427, 435-437, 441, 445-447, 452-456, 515, 548, 550, 559-562 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_factory_ops.py 121 99 18% 78-84, 133-143, 168-240, 260-271, 277-310, 336-346 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_functional_ops.py 39 25 36% 70-91, 112-128 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_gather_ops.py 98 80 18% 88-118, 167-261, 270-295 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_getitem.py 161 136 16% 97-103, 124-187, 200-226, 244-340, 360-361, 381-389, 394-406, 437-456, 462-471 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_map_ops.py 132 103 22% 169-331, 360-364, 372-386, 395-403, 409-418, 423-427, 434-459 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_math_ops.py 172 110 36% 88-105, 112-114, 193-256, 262, 271, 280, 289, 298-308, 313-324, 469-542, 551, 561, 572, 583, 594-608, 612, 618-619, 626-627 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_operators.py 44 1 98% 74 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_squeeze_op.py 53 40 25% 52-122 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_string_ops.py 192 153 20% 59-78, 121-175, 219-220, 280-281, 322-325, 385-394, 400-452, 493-512, 563-575, 626-643, 648, 721-803 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_tensor.py 823 674 18% 268-311, 363-428, 472-497, 531-553, 587-608, 637-659, 718-795, 837-858, 888-897, 927-936, 959-983, 992, 1011-1020, 1031-1032, 1056, 1079, 1105, 1131-1134, 1161-1166, 1192-1196, 1227-1233, 1255-1266, 1290-1291, 1315-1316, 1345-1360, 1377-1383, 1410-1435, 1456-1466, 1491-1494, 1509-1533, 1570-1583, 1652-1793, 1828-1839, 1878-1905, 1927-1930, 1985-2001, 2030-2031, 2038-2041, 2075-2086, 2096-2099, 2105-2108, 2112-2117, 2140-2143, 2151, 2158, 2162, 2167, 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/segment_id_ops.py 50 34 32% 55-71, 98-132 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/random_grad.py 32 18 44% 29-32, 58-71, 99-114 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/random_ops.py 147 77 48% 86-96, 136-153, 187-197, 276, 278-280, 292, 298-299, 340-341, 371-386, 415-416, 443-444, 449-451, 459-465, 544-558, 598, 637-643 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resource_variable_ops.py 686 328 52% 65-70, 76-81, 97-102, 126-143, 151, 161-163, 184-191, 254-255, 270, 291-300, 318-320, 447-452, 464-468, 471, 474, 477, 480-491, 506, 519, 522-524, 527-530, 535-538, 548, 554, 559, 564-566, 576, 581, 589, 593, 597-599, 602-604, 628, 641-643, 665-669, 673-688, 692-698, 713-743, 747-749, 765, 786-792, 810-816, 851, 855, 878-880, 898-900, 919-921, 940-942, 960-962, 980-982, 1000-1002, 1050-1052, 1101, 1150, 1199, 1206-1207, 1222, 1225, 1228, 1231, 1236, 1240, 1245, 1251, 1257, 1262, 1267, 1272, 1277, 1415-1421, 1512, 1517, 1527, 1531, 1534-1536, 1549-1550, 1571-1576, 1586, 1595-1632, 1639-1642, 1649, 1655, 1657, 1671-1731, 1790-1791, 1800-1807, 1846, 1853-1856, 1865-1868, 1871, 1874, 1877-1881, 1884-1885, 1889-1890, 1894-1895, 1899-1900, 1904-1905, 1909-1910, 1914-1915, 1919-1920, 1924-1925, 1929-1930, 1934-1935, 1939-1940, 1943-1944, 1947-1948, 1954, 1963, 1967-1973, 1980-1987, 1992, 1997-1999, 2050-2061, 2076, 2079, 2082-2083 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/resources.py 38 19 50% 53-57, 62, 67, 86-104, 118-120 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/rnn.py 455 407 11% 55-66, 82-93, 110-123, 127-130, 135-142, 163, 230-315, 330-357, 449-514, 638-716, 760-936, 1105-1259, 1330-1444, 1482-1538, 1594-1635 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/rnn_cell.py 5 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/rnn_cell_impl.py 509 368 28% 63-68, 86-101, 127-164, 170-179, 206-212, 232-244, 247-260, 269, 274, 279, 282-309, 328-340, 344, 385, 420-436, 440, 444, 448-462, 466-471, 474-480, 526-544, 548, 552, 556-582, 586-603, 606-614, 633-637, 697-719, 723, 728, 732-746, 762-794, 797-805, 896-941, 945, 949, 953-993, 1019-1071, 1074-1089, 1100-1104, 1123, 1147, 1151-1158, 1162-1168, 1179, 1190, 1200, 1234-1255, 1261-1264, 1268, 1271-1277, 1281-1287, 1291-1301, 1305-1327, 1345-1346, 1350-1354 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/rnn_cell_wrapper_impl.py 224 164 27% 109-173, 179-183, 187, 191, 195, 198-199, 202-203, 209-215, 225-250, 271-289, 293-308, 312-319, 337-338, 342, 346, 349-350, 369-381, 385-396, 400-407, 424-425, 429, 433, 436-438, 442-443, 446-448, 453-465, 471-494, 498-504, 508-515 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/rnn_grad.py 14 5 64% 26-50 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/script_ops.py 174 76 56% 59-67, 83-85, 102-119, 124-150, 171-172, 183, 203-212, 230-253, 257, 282, 295, 319, 336, 347, 357-364, 452-457, 517-524, 536, 555 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/sdca_ops.py 10 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/session_ops.py 128 85 34% 38, 56-60, 63-64, 67, 71-76, 85, 90, 94-99, 103-108, 117-118, 123-124, 129-130, 135, 173-178, 214-219, 239-243, 247, 251, 256-267, 272-288, 293-302 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/sets.py 5 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/sets_impl.py 55 31 44% 51-57, 81-90, 118-133, 200-201, 277-280, 356-357 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/signal/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/signal/dct_ops.py 77 60 22% 33-47, 97-179, 223-225 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/signal/fft_ops.py 217 146 33% 35-42, 48-60, 65-108, 116-140, 150-170, 198, 203-204, 209-212, 217-218, 223-226, 231-232, 237-240, 250-320, 336-360, 393-403, 434-444 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/signal/mel_ops.py 57 39 32% 46-48, 64-66, 73-89, 161-218 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/signal/mfcc_ops.py 20 9 55% 89-108 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/signal/reconstruction_ops.py 60 48 20% 54-165 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/signal/shape_ops.py 82 68 17% 33-54, 107-214 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/signal/signal.py 29 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/signal/spectral_ops.py 131 103 21% 70-94, 120-155, 224-276, 281-285, 331-365, 426-449 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/signal/util_ops.py 33 20 39% 47-73 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/signal/window_ops.py 77 52 32% 47-51, 70-90, 110-117, 135-141, 165, 192, 217-239 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/sort_ops.py 53 33 38% 65-66, 107-109, 128-140, 155-204, 209-211 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/sparse_grad.py 130 88 32% 50-60, 83-96, 101-103, 109-115, 136-145, 166-201, 206, 212-241, 247, 253, 273-286, 291, 297, 306-312, 317-322 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/sparse_ops.py 516 356 31% 66-70, 87-91, 95-101, 118-124, 147-179, 202-211, 324-331, 336-366, 430-434, 490-517, 550, 595, 614-655, 678-680, 720-731, 784-830, 840, 889-914, 955, 995-1008, 1062, 1129-1144, 1211-1216, 1259-1269, 1319-1333, 1387-1392, 1435-1445, 1490-1494, 1552-1564, 1663, 1672-1718, 1751-1765, 1829-1871, 1925-1935, 1958, 1977-1979, 2013, 2041-2043, 2107-2114, 2179-2187, 2401-2419, 2476-2480, 2508-2519, 2546-2557, 2595-2619, 2643-2645, 2683-2685, 2756-2777, 2795-2806 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/special_math_ops.py 357 299 16% 87-101, 129-130, 157-158, 186-187, 214-215, 242-243, 266-267, 290-291, 296-303, 319-324, 404, 409-468, 490-551, 580-679, 684-687, 693-700, 707-714, 723-726, 731-802, 807-853, 861-869, 881-973 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/standard_ops.py 83 1 99% 115 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/state_grad.py 17 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/state_ops.py 131 81 38% 44-52, 74, 101-114, 130-133, 161-164, 192-195, 224-228, 249-251, 301-304, 363-366, 415-418, 478-481, 532-535, 596-599, 648-651, 700-703, 755-758, 810-813, 872-914 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/stateful_random_ops.py 279 177 37% 90, 95-97, 110-136, 140-145, 149-151, 155, 168-182, 206-207, 212-216, 220-223, 230-231, 235, 239, 243-250, 254, 257, 270-278, 369-387, 410, 439-444, 467-473, 500-507, 517-519, 529-530, 541-548, 552, 557, 562, 565, 585-589, 600, 621-626, 629, 657-664, 667, 705-721, 737-741, 789-794, 810, 832-840, 880-890, 913-916, 939 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1128-1145, 1180-1199, 1225-1255, 1262-1273 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/template.py 245 168 31% 154, 212-225, 236-239, 289-314, 317-378, 381-393, 398, 403, 408, 413-419, 424, 429-433, 439-441, 446-450, 455-459, 464, 469, 474, 482, 489-494, 497, 501-515, 519-522, 528, 531, 535, 583-596, 599-655, 661-681, 687-689, 695-697, 703-705, 711-713, 719 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/tensor_array_grad.py 93 49 47% 70-80, 102-111, 129-137, 159-168, 184-192, 214-224, 240-248 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/tensor_array_ops.py 537 380 29% 101-167, 171, 175, 179, 183, 195-199, 214-220, 224-225, 233-250, 254-262, 266-279, 283-290, 294-307, 311-319, 324-326, 332-347, 352-370, 374-377, 383, 432-473, 477, 481, 485, 491, 503-507, 511-512, 516, 520-527, 531-543, 547-558, 562-568, 572-582, 587-595, 600-610, 615-633, 637-640, 644, 688-717, 722, 726, 731, 735, 739, 742, 749-778, 793-828, 832-834, 837-841, 845-852, 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100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/summary/writer/event_file_writer.py 128 95 26% 69-82, 90-96, 100, 110-112, 120-121, 132-137, 145-153, 160-163, 166-168, 193-204, 207-232, 244-254, 264-269, 285-294, 298-300 /usr/local/lib/python3.8/dist-packages/tensorflow/python/summary/writer/event_file_writer_v2.py 44 27 39% 74-96, 100, 110-112, 120-122, 131, 138-141 /usr/local/lib/python3.8/dist-packages/tensorflow/python/summary/writer/writer.py 133 90 32% 79-99, 119-142, 155-156, 159-161, 179-214, 217-227, 244-249, 263-273, 276-279, 360-372, 376, 380, 384, 387-388, 393-394, 402-403, 413-414, 421-422, 432-433 /usr/local/lib/python3.8/dist-packages/tensorflow/python/summary/writer/writer_cache.py 24 8 67% 43-48, 60-64 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tf2.py 14 1 93% 40 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tools/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/tools/module_util.py 31 12 61% 24, 47, 50-56, 60-61, 63 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/__init__.py 4 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/api.py 9 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/bfloat16.py 26 13 50% 49-68, 78-80 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/client/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/client/client.py 162 118 27% 34-35, 46, 50-54, 59-68, 75-81, 85-87, 106-141, 157-176, 181, 186-191, 196-200, 203, 206, 213-216, 220, 224, 228, 232, 236, 240, 244, 248-258, 270-281, 286-315 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/device_assignment.py 180 148 18% 36-56, 81-102, 108, 113, 118, 129, 133, 148-151, 157-158, 162-163, 167-168, 175, 198-213, 257-413 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/feature_column.py 220 158 28% 106-155, 219-285, 295-304, 310, 314, 318, 322, 330, 334, 338, 341, 344, 347, 351, 373, 397-402, 405, 409, 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/usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/preempted_hook.py 46 27 41% 40, 43-45, 48, 61-72, 75-77, 80-93 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/session_support.py 205 148 28% 45, 50, 71-74, 79-91, 95, 104-106, 111-124, 128-140, 144, 150-160, 165-175, 211-222, 226-247, 253-259, 262-265, 268, 271, 277-284, 293-298, 304-306, 325-333, 338-360, 364-381, 384-406, 417, 420-424, 435, 438, 449, 452 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tensor_tracer.py 795 657 17% 113-144, 158-179, 197-200, 217-231, 237-249, 274, 280-281, 293-295, 300, 314, 333, 340-346, 350-354, 361-373, 378-380, 386, 393-399, 402, 418-443, 448-455, 460-462, 479-509, 514-520, 524-531, 534, 538-552, 556, 571-585, 596-599, 612-745, 762-857, 871-909, 926-983, 989-1022, 1043-1055, 1060-1080, 1093-1122, 1125, 1140-1194, 1209-1213, 1219-1233, 1237-1252, 1256-1266, 1279-1283, 1294-1399, 1402, 1406, 1435-1600, 1630-1659, 1680-1701 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tensor_tracer_flags.py 250 163 35% 103-152, 155, 160-170, 174-183, 186-194, 199-211, 214, 219-229, 245-259, 263-290, 299-315, 319, 335-340, 353-363, 376-385, 401-418, 423-431, 436-444, 449-454, 468 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tensor_tracer_pb2.py 28 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tensor_tracer_report.py 242 183 24% 68-119, 126-130, 137-139, 143-160, 166-183, 193-199, 202, 205-206, 213-214, 217, 220, 223, 243-277, 281-284, 289-296, 300-304, 310-314, 319-335, 340-343, 348-361, 366-382, 387-396, 402-408 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/topology.py 90 60 33% 29-32, 37-40, 75-94, 98-129, 133-140, 145, 150, 164, 169, 182, 195, 199, 204, 211, 216, 220-228 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tpu.py 696 574 18% 90-93, 116-119, 145-147, 160-162, 175, 180-190, 196-198, 202-207, 216-221, 232-233, 235, 271-286, 303-350, 353-359, 363-399, 402-414, 420-463, 466-471, 474-481, 484, 488-508, 512-587, 591-604, 607-609, 617, 622-624, 627, 638-639, 642-645, 650-653, 658, 726-780, 886, 898-903, 926-1028, 1093-1354, 1373-1415, 1430-1461, 1532-1611, 1683, 1743, 1797, 1819-1831, 1843-1845, 1848, 1852-1858, 1861-1864, 1867, 1871, 1895-1896, 1936-1963, 1984-2001 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tpu_embedding.py 574 454 21% 106-126, 158-162, 197, 202, 223-229, 263-268, 316-322, 381-399, 458-482, 522, 691-781, 790, 801, 810, 822, 833, 837, 841, 845, 849, 853-908, 945-1012, 1033-1034, 1045-1112, 1116-1118, 1135-1163, 1175-1197, 1215-1237, 1246-1248, 1255-1267, 1273-1274, 1280-1281, 1291, 1294, 1297, 1301, 1308-1309, 1312, 1315, 1319-1377, 1384-1386, 1389-1397, 1401, 1406-1477, 1484-1486, 1489-1497, 1503, 1508-1580, 1587, 1591, 1595-1643, 1648-1657, 1662, 1667-1671, 1676-1697, 1703-1721, 1732-1758 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tpu_embedding_gradient.py 53 37 30% 45-50, 71-97, 118-126, 142-179 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tpu_feed.py 285 232 19% 52-83, 98-104, 120-121, 165-198, 206-209, 214, 219, 237-251, 258, 276-295, 300, 312, 331-337, 347, 360-362, 378-382, 404-432, 445-458, 482-496, 529-546, 596-604, 618, 621, 679-722, 757-765, 782-794, 834-882, 897-920, 934-935 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tpu_function.py 28 11 61% 35, 38, 48-54, 58, 66-67 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tpu_optimizer.py 64 43 33% 56-70, 86-107, 144-161, 184-192, 206, 220, 224 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tpu_sharding.py 91 68 25% 36-38, 41-44, 48-51, 60-62, 67, 82-91, 98, 114-120, 132-135, 161-188, 204-216, 239-252 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tpu_strategy_util.py 95 73 23% 53-127, 146-206 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/tpu_system_metadata.py 101 75 26% 56-149, 154-166, 174-176, 196-212 /usr/local/lib/python3.8/dist-packages/tensorflow/python/tpu/training_loop.py 82 70 15% 56-177, 201-222 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/adadelta.py 46 28 39% 59-67, 70-72, 75-81, 84-86, 97-99, 110-112, 124-126 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/adagrad.py 48 26 46% 63-70, 73-80, 84-90, 93-94, 98-99, 107-108, 116-117, 126-127 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/adagrad_da.py 59 39 34% 75-88, 91-100, 104-109, 112-116, 128-132, 144-148, 161-165 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/adam.py 93 67 28% 101-111, 114-119, 127-136, 139-147, 150-153, 167-170, 184-207, 210, 221-223, 226, 231-238 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/basic_loops.py 21 13 38% 51-65 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/basic_session_run_hooks.py 491 361 26% 61, 65, 69, 83, 87, 99-108, 111-112, 125-139, 142-152, 155, 162-163, 166-167, 170, 212-231, 234-237, 243-247, 250-263, 266-270, 273-275, 306-315, 352-360, 363-366, 369-371, 374-377, 382-386, 412-417, 420-422, 425-427, 430, 433-442, 500, 503, 506, 509, 546-557, 560, 563-569, 572-588, 591, 594-602, 605-609, 613-634, 637-656, 669-678, 681, 684-690, 693, 696-702, 705-736, 743, 760-761, 764, 767-775, 809-817, 822-827, 831-839, 842-861, 864-865, 873-884, 903, 906-909, 913-933, 949-951, 955, 958-977, 991, 994, 1033-1037, 1041-1044, 1047-1055, 1058-1072, 1075-1078, 1085-1104 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/checkpoint_management.py 266 201 24% 45-47, 61-63, 96-128, 167, 213-247, 270-305, 322-324, 351-364, 381-388, 410, 438-456, 476-484, 489-490, 506-508, 614-664, 668, 672, 686, 698, 702-717, 721-722, 743, 748, 771-824, 844-852 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/checkpoint_ops.py 76 60 21% 123-203, 332-416, 467-473 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/checkpoint_state_pb2.py 14 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/checkpoint_utils.py 161 125 22% 63-67, 82-85, 98-104, 125-135, 181-201, 286-291, 297-378, 384-386, 406-427, 447-459, 463, 469-476 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/coordinator.py 141 104 26% 142-159, 178-185, 201-244, 251-255, 263, 296-299, 311, 319-320, 353-395, 401, 405-407, 444-457, 478-481, 484-496, 500, 504, 508-509 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/device_setter.py 64 45 30% 53-54, 66-68, 93-98, 111-133, 202-231 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/evaluation.py 106 74 30% 47-61, 74-78, 92-94, 97, 100, 105-109, 112, 116-130, 145-149, 153, 156, 160-169, 225-277 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/experimental/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/experimental/loss_scale.py 158 90 43% 83, 88, 125, 141-162, 167-176, 180-188, 193, 198, 202, 228-239, 242, 245-246, 249, 252, 257-260, 275-277, 282, 324-335, 340, 344, 348, 351, 355-400, 403-409, 414, 424, 426, 428, 432 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/experimental/loss_scale_optimizer.py 79 52 34% 61-74, 78, 114-126, 129-136, 139-141, 147-150, 174-184, 211-221, 226-229, 233, 237, 241, 245 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/experimental/loss_scaling_gradient_tape.py 73 53 27% 43, 115-125, 163-181, 190, 200, 238-320 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/experimental/mixed_precision.py 51 30 41% 33-74, 219, 332, 339-362, 382-386, 413 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/experimental/mixed_precision_global_state.py 7 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/ftrl.py 72 53 26% 95-130, 134-138, 141-150, 154-170, 186-202, 218-235, 252-267 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/gen_training_ops.py 1619 1436 11% 57-77, 83, 115-135, 141, 167-191, 197, 226-248, 254, 282-306, 312, 353-378, 384, 414-434, 440, 490-510, 516, 552-572, 578, 617-637, 643, 662-681, 687, 720-744, 750, 780-800, 806, 835-854, 860, 886-906, 912, 952-972, 978, 1011-1038, 1043-1056, 1086-1113, 1118-1131, 1156-1185, 1190-1206, 1236-1266, 1271-1286, 1313-1343, 1348-1365, 1404-1437, 1442-1459, 1498-1527, 1532-1547, 1575-1601, 1606-1618, 1665-1692, 1697-1712, 1747-1773, 1778-1791, 1829-1856, 1861-1874, 1893-1916, 1921-1933, 1965-1995, 2000-2017, 2049-2078, 2083-2099, 2127-2153, 2158-2171, 2199-2225, 2230-2243, 2269-2296, 2301-2313, 2351-2377, 2382-2395, 2423-2451, 2456-2472, 2500-2530, 2535-2553, 2585-2616, 2621-2638, 2668-2699, 2704-2722, 2769-2800, 2805-2822, 2860-2887, 2892-2908, 2949-2977, 2982-2998, 3034-3067, 3072-3090, 3126-3156, 3161-3179, 3211-3239, 3244-3259, 3288-3316, 3321-3335, 3375-3402, 3407-3423, 3452-3474, 3480, 3509-3534, 3540, 3571-3595, 3601, 3632-3658, 3664, 3714-3737, 3743, 3782-3804, 3810, 3852-3874, 3880, 3917-3943, 3949, 3982-4003, 4009, 4038-4061, 4067, 4109-4131, 4137 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/gradient_descent.py 28 10 64% 51-53, 56, 63, 69, 73-77, 80-81 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/input.py 387 284 27% 74-75, 103-114, 174-202, 256-267, 315-317, 363-376, 383, 399-401, 404-415, 418, 421, 425-430, 434, 438, 442, 446-449, 453-463, 467-475, 509-577, 582-597, 602-627, 631-634, 638-642, 647-656, 660-667, 671-678, 698-709, 714-718, 723-735, 740-752, 756, 765-791, 804-832, 840-876, 885-919, 1009, 1066, 1177, 1234, 1335, 1399, 1498, 1562 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/learning_rate_decay.py 87 58 33% 97-103, 150-179, 268-280, 356-368, 444-451, 507-514, 579-591, 664-676, 757-771 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/momentum.py 40 22 45% 80-83, 86-87, 90-98, 101-102, 111-112, 121-122, 131-132 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/monitored_session.py 481 348 28% 153-188, 192-247, 251, 255, 259, 263, 267, 271, 275, 279, 283, 288-300, 315, 337-427, 512-601, 614, 639-644, 648-657, 660-661, 690-694, 698-707, 710-711, 734-751, 756-758, 774, 819-834, 852-853, 857, 861, 871, 874, 877, 880, 883-887, 893-897, 902-910, 915-929, 939, 950, 1034, 1118-1124, 1132, 1154-1155, 1159, 1163, 1173-1177, 1185, 1188-1197, 1200, 1206-1207, 1230-1231, 1235-1238, 1249-1272, 1276-1295, 1299-1316, 1342-1344, 1349-1351, 1354-1365, 1368-1384, 1412-1414, 1418, 1422-1453, 1458-1481, 1484-1486, 1501-1514 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/moving_averages.py 131 103 21% 87-114, 152-178, 220-266, 378-382, 387, 421-473, 485, 509-511, 545-561 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/optimizer.py 403 311 23% 58-61, 76-80, 85-87, 97, 102, 109, 112, 115, 118-132, 139, 142, 146-151, 158, 161, 165-176, 188, 191, 194, 199-213, 327-343, 353, 399-412, 458-519, 523-529, 561-640, 667-735, 755-773, 783, 794-811, 816-843, 848-857, 862-866, 869-875, 883, 894-898, 914, 924, 932, 944, 957, 980-982, 1002, 1032-1038, 1057, 1074, 1090-1094, 1109-1116, 1134-1142, 1156-1163, 1171-1179, 1202-1239, 1245 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/proximal_adagrad.py 44 25 43% 63-74, 77-82, 85-90, 95-96, 103-104, 111-112, 120-121 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/proximal_gradient_descent.py 30 13 57% 57-62, 65, 74, 83, 93, 103-107 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/py_checkpoint_reader.py 40 17 58% 31-48, 61, 73-74, 98-99 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/quantize_training.py 15 4 73% 45-50 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/queue_runner.py 5 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/queue_runner_impl.py 176 128 27% 97-118, 138-165, 175-192, 196, 200, 204, 208, 212, 231, 236, 248-283, 293-298, 327-356, 368-385, 390, 411, 451-480 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/rmsprop.py 70 50 29% 107-118, 121-131, 134-142, 145-161, 173-189, 201-218, 231-248 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/saver.py 480 383 20% 84, 104-124, 144-154, 173-179, 194, 206-207, 254-285, 298-311, 335-361, 379-390, 409-417, 462, 484-557, 574-583, 598-610, 800-843, 846-848, 851, 856-902, 906-914, 926-927, 931-942, 957-973, 981, 992-1008, 1021, 1032, 1045-1049, 1061-1062, 1075-1080, 1139-1217, 1253, 1283-1334, 1346, 1460, 1471-1490, 1496-1514, 1580-1599, 1603-1607, 1626-1634, 1679-1728 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/saving/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/saving/functional_saver.py 119 48 60% 51, 64-73, 118, 148, 153-154, 165-169, 179-182, 188-191, 202-263, 284 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/saving/saveable_hook.py 16 4 75% 44, 51, 55, 59 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/saving/saveable_object.py 34 8 76% 41, 47-51, 55, 78, 101 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/saving/saveable_object_util.py 161 98 39% 54-56, 63-64, 67-70, 84-85, 90-95, 101, 111, 120, 139, 143, 145-169, 175-183, 190, 196-209, 230-303, 319, 342 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/server_lib.py 200 151 24% 57-95, 146-150, 153-164, 173, 184, 194, 213, 235, 285-313, 318, 324, 327, 330-334, 348-361, 365, 374, 388-392, 407-411, 427-434, 457-464, 473-491, 527-530, 534-538, 542-546, 555-573 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/session_manager.py 149 120 19% 42-47, 144-155, 189-227, 288-319, 353-383, 411-442, 453-459, 473, 487, 502-512, 529-551, 557-558, 561-562 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/session_run_hook.py 41 13 68% 110, 127, 150, 169, 186, 211, 226-228, 240, 245, 255, 263 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/slot_creator.py 62 48 23% 55-101, 124-135, 161-173, 190-204 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/summary_io.py 12 1 92% 80 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/supervisor.py 339 239 29% 308-357, 360-369, 380-390, 405-416, 427-433, 444-455, 464-469, 478-484, 493-500, 509, 518, 530, 539, 548, 557, 561, 570, 579, 588, 597, 606, 615, 624, 628-636, 661-688, 720-745, 772-780, 801-808, 831-847, 859, 869, 879, 883, 898-902, 910-918, 928-931, 999-1023, 1038-1040, 1043-1051, 1066-1073, 1076-1077, 1081-1098, 1112-1114, 1117-1122 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/sync_replicas_optimizer.py 150 114 24% 181-205, 223, 248-358, 375-378, 392, 403, 417, 439-458, 462, 476-478, 481-497, 501-513 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/tracking/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/tracking/base.py 342 122 64% 71-76, 79-82, 86, 93-95, 98, 112, 126, 143-155, 161, 165, 170-173, 181-183, 187, 211, 233, 241-253, 266, 277-278, 291-307, 320, 323-324, 338-348, 352-354, 364-367, 369, 373, 376, 411, 414, 489-494, 521-526, 544-546, 550, 558, 562, 566, 570, 601, 624, 629, 633, 637-640, 726, 736-737, 754, 780-790, 822, 825, 829-839, 876, 883, 923-925, 933, 1004-1005, 1022-1023 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/tracking/data_structures.py 536 236 56% 28-30, 70, 72, 74, 92, 94, 97, 144, 167, 171, 184, 187, 193, 205, 214, 221, 228, 232, 236, 240, 248-252, 257-261, 266, 271, 314, 318, 321, 324, 328, 336, 349-350, 353, 356-366, 369, 372, 375, 381, 387, 390, 444-445, 454-455, 459-462, 465-468, 472, 482, 484-485, 494, 501, 510, 522-523, 532-545, 550, 568-574, 577, 580, 583, 586, 589, 592, 597, 600-601, 604-605, 608, 611-612, 626, 629, 646-648, 654, 657, 660, 666-669, 672-676, 679-683, 689-690, 693, 696, 699, 702, 717, 720, 732, 747, 751-754, 757-760, 770, 777, 785, 806, 808-809, 815, 823-824, 828-832, 845-859, 862-864, 867, 870, 875, 878-879, 882, 892-938, 943, 947-954, 957, 962, 967, 970, 973, 976, 983, 987, 991-998, 1001-1009, 1013, 1048-1055 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/tracking/graph_view.py 201 126 37% 78-86, 97-135, 177-179, 192, 211-312, 319-330, 335-356, 379-380, 385-402 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/tracking/layer_utils.py 110 13 88% 33-34, 190, 231, 242, 268, 293-296, 301-304 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/tracking/python_state.py 17 1 94% 87 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/tracking/tracking.py 131 52 60% 82, 92-94, 98, 102-113, 119-125, 140, 177-178, 185-186, 190-191, 221, 226, 231-234, 237-252, 274-276, 323-324, 330 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/tracking/util.py 602 378 37% 69-72, 90-115, 129, 133, 136, 143-145, 147-149, 151, 229, 244, 248-249, 252-254, 272-277, 285, 291-294, 302-308, 324-348, 355-379, 392-418, 433, 465-476, 493, 511-512, 537-607, 616, 621, 626, 631, 636, 640, 651-664, 710-740, 763, 780, 788-806, 810-814, 831-845, 849-850, 864-867, 871, 876, 881, 893, 911-921, 941-945, 959, 963-982, 990, 998, 1002-1014, 1018-1024, 1029, 1036-1037, 1040-1045, 1094-1107, 1125-1140, 1164-1198, 1259, 1263, 1268-1281, 1286-1290, 1333-1335, 1343, 1468-1481, 1485-1490, 1520-1529, 1540-1541, 1568-1601, 1705-1712, 1808-1821, 1825-1830, 1857-1866, 1877-1878, 1902-1933, 2009-2016 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/training.py 105 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/training_ops.py 6 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/training_util.py 95 65 32% 66-68, 88-103, 120-137, 158-162, 172-184, 201-209, 222-239, 243-253 /usr/local/lib/python3.8/dist-packages/tensorflow/python/training/warm_starting_util.py 150 123 18% 122-126, 152-156, 173-189, 240-311, 340-372, 396-411, 465-549 /usr/local/lib/python3.8/dist-packages/tensorflow/python/user_ops/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/user_ops/user_ops.py 10 1 90% 32 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/all_util.py 36 6 83% 78-83 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/compat.py 51 9 82% 60-61, 80, 86, 111, 116, 178-180 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/compat_internal.py 9 3 67% 34-36 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/decorator_utils.py 52 11 79% 26-32, 51, 71, 100, 108, 119, 145 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/deprecation.py 208 81 61% 95, 97, 102-110, 129-131, 188-239, 264, 314-317, 379, 381-382, 390, 439-442, 463-471, 485, 487, 489, 495, 497-500, 553, 565-568, 596-601, 635 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/dispatch.py 58 21 64% 69, 81, 100-104, 120-125, 128-131, 156, 170, 181-188 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/function_utils.py 59 38 36% 31-32, 36, 51-63, 78-86, 95-101, 106-119, 127-132 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/is_in_graph_mode.py 5 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/lazy_loader.py 27 4 85% 50-52, 66-67 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/lock_util.py 43 3 93% 68, 92, 112 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/memory.py 11 4 64% 40-45 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/module_wrapper.py 132 60 55% 37, 44-48, 52, 68-78, 104-105, 108, 133-140, 144-152, 161-162, 170-174, 193-206, 219-227, 230-233, 236, 239 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/nest.py 303 121 60% 91-93, 100-101, 150, 157-162, 165, 167-171, 178-179, 181, 185, 220-221, 223-224, 231, 256, 332, 335, 379-382, 418-441, 485-486, 489, 496, 508-512, 596, 599, 605, 610, 653-657, 696, 777, 782, 789-804, 809-822, 827-828, 833, 837, 844, 1032-1037, 1189, 1249-1285, 1347-1351 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/object_identity.py 114 27 76% 44, 47-48, 51-52, 56, 61, 70, 114, 141, 148, 155, 159, 162-168, 179-181, 190, 199, 202, 205, 232 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/protobuf/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/protobuf/compare.py 87 69 21% 94-118, 139-186, 190, 194-200, 216-255, 274 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/serialization.py 29 19 34% 43-76 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/tf_contextlib.py 9 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/tf_decorator.py 98 16 84% 172-173, 180-181, 188-193, 218, 222, 224, 257, 260, 272, 276 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/tf_export.py 145 47 68% 114, 118, 132, 154, 174, 178, 180, 194-207, 220-228, 241-249, 274, 302, 307, 329-331, 343-344, 388-393 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/tf_inspect.py 138 55 60% 34, 43, 79-90, 95, 118, 126, 131-147, 190-235, 282, 291-293, 298, 327, 342, 347, 362, 377, 382, 397, 402, 407 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/tf_should_use.py 98 67 32% 45-61, 64-68, 72-86, 95, 100-101, 105-107, 113-117, 122-129, 148-161, 179-202, 235 /usr/local/lib/python3.8/dist-packages/tensorflow/python/util/tf_stack.py 70 6 91% 37-38, 61, 76, 88, 99 /usr/local/lib/python3.8/dist-packages/tensorflow/tools/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/tools/compatibility/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/tools/compatibility/all_renames_v2.py 15 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/tools/compatibility/renames_v2.py 5 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/tools/docs/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow/tools/docs/doc_controls.py 49 30 39% 258-261, 276-322 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/_api/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/_api/v1/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/_api/v1/estimator/__init__.py 67 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/_api/v1/estimator/experimental/__init__.py 20 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/_api/v1/estimator/export/__init__.py 15 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/_api/v1/estimator/inputs/__init__.py 9 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/_api/v1/estimator/tpu/__init__.py 13 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/_api/v1/estimator/tpu/experimental/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/api/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/api/_v1/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/api/_v1/estimator/__init__.py 67 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/api/_v1/estimator/experimental/__init__.py 20 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/api/_v1/estimator/export/__init__.py 15 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/api/_v1/estimator/inputs/__init__.py 9 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/api/_v1/estimator/tpu/__init__.py 13 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/api/_v1/estimator/tpu/experimental/__init__.py 8 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/baseline.py 124 78 37% 72-79, 83-90, 95-112, 128-154, 187-197, 220-227, 264-283, 381-398, 414-427, 497-506, 516-525, 607-621, 636-650 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/boosted_trees.py 715 607 15% 61-81, 95-99, 111-115, 130-147, 168, 201-275, 280-287, 317-388, 393-414, 443-471, 476-489, 497, 505-570, 597-621, 625-639, 643-654, 674-680, 686, 690, 703-706, 709, 717-724, 730-731, 761-776, 824, 830-836, 841-889, 898, 906-911, 916-920, 926, 938-982, 986-1010, 1017-1052, 1056-1089, 1093, 1147-1407, 1414, 1417, 1440-1479, 1489-1506, 1513-1521, 1531-1551, 1556, 1565-1578, 1601-1615, 1641-1686, 1691-1700, 1739-1751, 1770-1781, 1840-1889, 1894-1903, 2038-2063, 2190-2214, 2315-2343, 2357-2360 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/boosted_trees_utils.py 42 27 36% 33-37, 45-57, 61, 66, 73-82, 87-94 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/dnn.py 224 162 28% 46-48, 73-102, 125-153, 157-158, 174-230, 233-254, 260, 272, 287-344, 347-359, 363-364, 371-379, 431-456, 489-504, 552-579, 737-759, 787-807, 946-962, 986-1003, 1151-1172, 1199-1221 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/dnn_linear_combined.py 187 140 25% 43-44, 64-65, 69-71, 76-82, 141-226, 288-383, 554-585, 615-643, 657-682, 820-843, 864-888, 1048-1077, 1106-1136 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/head.py 497 410 18% 58, 78-89, 155, 166, 193, 230-240, 274, 299-354, 382-443, 448-472, 487-494, 510-520, 536-559, 563-567, 571-573, 579-584, 590-598, 615-617, 622-628, 632-637, 646-650, 658-666, 671-679, 738-748, 767-774, 778, 782, 787-808, 812-825, 829-852, 893-994, 1062-1077, 1096-1101, 1105, 1109, 1113-1195, 1199-1223, 1265-1373, 1435-1440, 1460-1467, 1471, 1475, 1479-1505, 1514-1532, 1571-1652, 1661-1664, 1668-1676, 1704-1715 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/kmeans.py 110 69 37% 46-48, 51-52, 55-62, 82-84, 87-99, 119-127, 137-145, 173-224, 404-415, 424-425, 436-438, 454, 470-475, 479 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/linear.py 283 217 23% 128-133, 138-174, 181-239, 243-244, 248-249, 262-270, 283-308, 326-375, 394-448, 470-539, 547-548, 555, 559, 583-619, 652-678, 719-748, 759-767, 920-945, 968-991, 1107-1119, 1158-1171, 1178-1186, 1325-1349, 1371-1396 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/linear_optimizer/__init__.py 6 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/linear_optimizer/python/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/linear_optimizer/python/utils/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/linear_optimizer/python/utils/sdca_ops.py 291 245 16% 95-104, 114, 123, 132, 200-251, 254, 257, 261, 265, 270-271, 280-298, 305-307, 310-312, 316-318, 322-333, 337-348, 356-364, 368-371, 379-402, 420-433, 440-449, 464-629, 644-670, 679-699, 715-760, 775-781 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/linear_optimizer/python/utils/sharded_mutable_dense_hashtable.py 139 101 27% 73-99, 106-120, 124, 135-138, 158-165, 184-192, 204-210, 214, 223-229, 232-235, 262-280, 285, 289, 293, 296-298, 301-307, 310-311, 316-335, 339-352, 364-370 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/metric_keys.py 26 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/optimizers.py 46 27 41% 78-91, 95-97, 129-146 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/parsing_utils.py 44 25 43% 138-140, 254-257, 288-312, 321-324, 342-346 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/canned/prediction_keys.py 14 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/early_stopping.py 179 131 27% 84-104, 153, 210, 268, 326, 346-356, 365-388, 401-430, 446-450, 454-458, 471-479, 482-484, 487-488, 491-498, 505, 508, 511-512, 515-518, 525-529, 540-549, 552-566, 570-571, 577-592 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/estimator.py 729 611 16% 176-203, 209, 213, 217, 228-231, 246-248, 259-261, 270-271, 321-351, 365-376, 390, 445-462, 478-511, 525-543, 596-639, 646, 717-722, 800, 817-889, 926-1010, 1014-1017, 1020-1021, 1027-1039, 1043, 1048-1054, 1058-1072, 1086, 1097-1100, 1123-1137, 1154-1176, 1179-1182, 1197-1213, 1231-1241, 1250-1354, 1361-1385, 1390-1523, 1527-1563, 1567-1575, 1581-1631, 1636-1658, 1661-1664, 1735-1738, 1756, 1760-1763, 1769-1786, 1793-1805, 1822-1849, 1854-1861, 1871-1941, 1945-1947, 1953-1957, 1962-1968, 1985-1998, 2003-2016, 2021-2026, 2031-2040, 2052, 2065-2110, 2123-2134, 2141-2148, 2338-2341, 2366-2385 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/export/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/export/export.py 128 88 31% 65-72, 77-95, 99-103, 139-157, 206-215, 238, 271-277, 302-313, 327-343, 348, 370-376, 404-440, 470-474 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/export/export_lib.py 27 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/export/export_output.py 16 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/exporter.py 151 106 30% 41, 62, 97-100, 104, 108-117, 136-145, 150-160, 255-271, 277, 281-307, 319-337, 350-365, 400, 406, 410-416, 457-462, 467, 471-477, 489-507 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/extenders.py 38 25 34% 82-94, 104-107, 113-123 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/gc.py 63 46 27% 87-95, 110-127, 140-147, 161-166, 179-184, 207-217 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/head/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/head/base_head.py 290 222 23% 110, 122, 133, 163, 178, 192, 224, 227, 281-295, 347, 406-469, 498-582, 587-624, 639-648, 652-654, 660-661, 666-667, 673-677, 695-705, 726-759, 763-765, 771-773, 779-784, 790, 798-817, 821-824, 844-855, 896-918, 925-934 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/head/binary_class_head.py 205 164 20% 151-193, 198, 203, 208, 229-232, 245-250, 254-259, 263-275, 284-300, 318-362, 366-392, 421-427, 430-433, 443-487, 540-597 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/head/head_utils.py 30 17 43% 55-66, 70-77, 92-94, 101-102 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/head/multi_class_head.py 151 113 25% 143-168, 173, 178, 183, 204-207, 220-225, 229-242, 246-262, 271-287, 305-345, 349-359, 368-385, 436-492 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/head/multi_head.py 182 149 18% 34-35, 40-45, 178-200, 205, 210, 215-220, 250-282, 286-306, 315-342, 346-353, 357-367, 376-395, 454-512, 528-548 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/head/multi_label_head.py 217 181 17% 161-243, 248, 253, 258, 277-280, 284-315, 322-339, 348-364, 381-399, 403-427, 436-480, 532-587 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/head/regression_head.py 124 85 31% 143-159, 164, 169, 174, 177-182, 186-203, 212-228, 242-254, 258-269, 279-297, 351-402, 483-484, 493, 568-570, 577 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/hooks/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/hooks/basic_session_run_hooks.py 31 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/hooks/hooks.py 92 67 27% 103-120, 124-141, 148-176, 179-201, 205-207, 211, 237-244, 247-249, 253, 256-266, 275-277 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/hooks/session_run_hook.py 13 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/inputs/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/inputs/numpy_io.py 70 56 20% 50-53, 70-86, 141-224 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/inputs/pandas_io.py 61 46 25% 32-36, 50-52, 91-158 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/inputs/queues/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/inputs/queues/feeding_functions.py 208 177 15% 34-38, 51-60, 78-96, 126-145, 158-169, 172-181, 197-212, 215-230, 243-255, 258-271, 285-297, 300-330, 376-504 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/inputs/queues/feeding_queue_runner.py 68 56 18% 57-73, 87-122, 150-174, 177, 182 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/mode_keys.py 7 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/model_fn.py 176 139 21% 152-164, 180-184, 213-221, 237-242, 283-295, 316-331, 353-377, 405-408, 424-430, 459-507, 512-516, 534-538, 542-543, 548-550, 577-598, 607-620 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/run_config.py 315 208 34% 95-113, 118-121, 126-130, 135-139, 145-149, 154-199, 211-226, 236-248, 254-328, 337-341, 536-586, 596-597, 609-627, 635-689, 697-724, 728, 738, 742, 746, 750, 754, 758, 762, 802, 806, 810, 814, 818, 822, 826, 830, 834, 838, 842, 846, 850, 855, 860, 865, 870, 907, 933-946, 957-975 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/tools/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/tools/analytics.py 8 2 75% 28, 37 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/tpu/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/tpu/_tpu_estimator_embedding.py 227 180 21% 58, 62, 66-68, 73-94, 103-122, 137-174, 270-315, 337-358, 362-363, 368, 372-412, 415-418, 424-429, 434-490, 495-505, 510-519, 524-541, 553-557 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/tpu/error_handling.py 65 44 32% 56-58, 73-105, 115-117, 122-125, 136-154 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/tpu/iteration_count_estimator.py 64 46 28% 68, 72-81, 84, 87, 90, 107-111, 122-123, 132-150, 169-201 /usr/local/lib/python3.8/dist-packages/tensorflow_estimator/python/estimator/tpu/tpu_config.py 99 60 39% 141-189, 227-265, 272, 276, 280, 284, 288, 291-297, 304-309 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/usr/local/lib/python3.8/dist-packages/wcwidth/table_wide.py 1 0 100% /usr/local/lib/python3.8/dist-packages/wcwidth/table_zero.py 1 0 100% /usr/local/lib/python3.8/dist-packages/wcwidth/wcwidth.py 37 28 24% 116-129, 183-196, 212-220 /usr/local/lib/python3.8/dist-packages/wrapt/__init__.py 6 0 100% /usr/local/lib/python3.8/dist-packages/wrapt/decorators.py 186 91 51% 11-23, 40-41, 55-56, 60, 64, 68, 72, 76, 86, 91, 95, 99-102, 105-106, 112, 117-120, 123, 138, 142, 146, 149-150, 154, 158, 162-163, 165, 205, 208-212, 253-279, 292-294, 322, 343-390, 411, 444-445, 450-451, 454, 464-514 /usr/local/lib/python3.8/dist-packages/wrapt/importer.py 102 75 26% 12, 37-45, 52-98, 103-109, 112-119, 128-135, 145-148, 153, 156-159, 164, 172-221, 227-230 /usr/local/lib/python3.8/dist-packages/wrapt/wrappers.py 472 304 36% 11, 32, 36, 40, 44, 51, 60, 78-87, 91, 95, 99, 103, 107, 111, 114, 117, 121, 124, 130, 134, 138, 141, 144, 147, 150, 153, 156, 159, 162, 165, 168-190, 196-199, 202-216, 219, 222, 225, 228, 231, 234, 237, 240, 243, 246, 249, 252, 255, 258, 261, 264, 267, 270, 273, 276, 279, 282, 285, 288, 291, 294, 297, 300, 303-304, 307-308, 311-312, 315-316, 319-320, 323-324, 327-328, 331-332, 335-336, 339-340, 343-344, 347-348, 351-352, 355, 358, 361, 364, 367, 370, 373, 376, 379, 382, 385, 388, 391, 394, 397, 400, 403, 406, 409, 412, 415, 418, 421, 424, 427, 431, 437, 442-453, 456-461, 471-477, 505-533, 542-566, 578-624, 704-719, 727-728, 733-771, 774, 777-780, 791-794, 797-798, 801, 804, 807-811, 819-828, 831, 834-836, 839-858, 870-880, 899-928, 936-947 /usr/local/lib/python3.8/dist-packages/zmq/__init__.py 41 16 61% 23-24, 32-37, 54-60, 64-67 /usr/local/lib/python3.8/dist-packages/zmq/_future.py 323 280 13% 28-112, 129-144, 149, 152-161, 165-168, 176, 187, 196-199, 208-212, 216-241, 249-278, 282-289, 299, 308-315, 319-350, 354-406, 410-445, 448-483, 488-493, 503-509, 513-515, 519-521, 528, 532-533, 540-543 /usr/local/lib/python3.8/dist-packages/zmq/asyncio/__init__.py 48 20 58% 18-19, 28, 34-37, 41-43, 53, 60, 75-76, 83-87, 93 /usr/local/lib/python3.8/dist-packages/zmq/backend/__init__.py 26 15 42% 14-17, 22, 28-40 /usr/local/lib/python3.8/dist-packages/zmq/backend/cython/__init__.py 14 0 100% /usr/local/lib/python3.8/dist-packages/zmq/backend/select.py 15 7 53% 29-35 /usr/local/lib/python3.8/dist-packages/zmq/error.py 79 44 44% 37-50, 58, 61, 90-91, 101-102, 107-108, 120, 123-124, 132-144, 157-162, 165, 168, 183-184 /home/admin/workarea/git/Velours/python/dev/generate_new_image.py:720: SyntaxWarning: "is not" with a literal. Did you mean "!="? list_origin_portfolio_ids = [int(item) for item in options.list_origin_portfolio_ids.split(",")] if options.list_origin_portfolio_ids is not "" else [] /home/admin/workarea/git/Velours/python/dev/generate_new_image.py:721: SyntaxWarning: "is not" with a literal. Did you mean "!="? list_photo_ids = [int(item) for item in options.list_photo_ids.split(",")] if options.list_photo_ids is not "" else [] /home/admin/workarea/git/Velours/python/dev/generate_new_image.py:722: SyntaxWarning: "is not" with a literal. Did you mean "!="? rotate_angle_interval = [int(item) for item in options.interval_rotation.split(",")] if options.interval_rotation is not "" else [] /home/admin/workarea/git/Velours/python/dev/generate_new_image.py:723: SyntaxWarning: "is not" with a literal. Did you mean "!="? resize_interval = [float(item) for item in options.interval_resize.split(",")] if options.interval_resize is not "" else None /home/admin/workarea/git/Velours/python/dev/generate_new_image.py:750: SyntaxWarning: "is not" with a literal. Did you mean "!="? mother_crop_portfolio_multi = [float(item) for item in options.mother_crop_portfolio_multi.split(",")] if options.mother_crop_portfolio_multi is not "" else None /home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py:1505: SyntaxWarning: "is not" with a literal. Did you mean "!="? elif new_context_file is not "": /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:1950: SyntaxWarning: "is not" with a literal. Did you mean "!="? rotate_angle_interval_value = [int(item) for item in interval_rotation.split(",")] if interval_rotation is not "" else [] /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:1951: SyntaxWarning: "is not" with a literal. Did you mean "!="? resize_interval_value = [float(item) for item in interval_resize.split(",")] if interval_resize is not "" else None /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:1957: SyntaxWarning: "is not" with a literal. Did you mean "!="? mother_crop_portfolio_multi_value = [float(item) for item in mother_crop_portfolio_multi.split(",")] if mother_crop_portfolio_multi is not "" else None /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:2141: SyntaxWarning: "is not" with a literal. Did you mean "!="? rotate_angle_interval_value = [int(item) for item in interval_rotation.split(",")] if interval_rotation is not "" else [] /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:2142: SyntaxWarning: "is not" with a literal. Did you mean "!="? resize_interval_value = [float(item) for item in interval_resize.split(",")] if interval_resize is not "" else None /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py:2148: SyntaxWarning: "is not" with a literal. Did you mean "!="? mother_crop_portfolio_multi_value = [float(item) for item in mother_crop_portfolio_multi.split(",")] if mother_crop_portfolio_multi is not "" else None /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_batch_gather_with_default_op.py:84: SyntaxWarning: "is not" with a literal. Did you mean "!="? if (default_value.shape.ndims is not 0 /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/ragged/ragged_batch_gather_with_default_op.py:85: SyntaxWarning: "is not" with a literal. Did you mean "!="? and default_value.shape.ndims is not 1): /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/random_ops.py:285: SyntaxWarning: "is" with a literal. Did you mean "=="? minval_is_zero = minval is 0 # pylint: disable=literal-comparison /usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/random_ops.py:286: SyntaxWarning: "is" with a literal. Did you mean "=="? maxval_is_one = maxval is 1 # pylint: disable=literal-comparison /usr/local/lib/python3.8/dist-packages/traitlets/config/loader.py:795: SyntaxWarning: "is" with a literal. Did you mean "=="? if len(key) is 1: /usr/local/lib/python3.8/dist-packages/traitlets/config/loader.py:804: SyntaxWarning: "is" with a literal. Did you mean "=="? if len(key) is 1: /usr/local/lib/python3.8/dist-packages/zmq/eventloop/__init__.py 2 0 100% /usr/local/lib/python3.8/dist-packages/zmq/eventloop/ioloop.py 64 35 45% 23-26, 42-45, 49-52, 55-60, 64-67, 75, 89-91, 103-106, 114-117, 129-130, 135 /usr/local/lib/python3.8/dist-packages/zmq/eventloop/zmqstream.py 246 181 26% 44, 49, 53-54, 60-61, 114-138, 142, 146, 150, 154, 182-189, 200-203, 241-243, 255-258, 265, 271-279, 285-287, 295-299, 306-307, 311, 344-393, 397, 401-419, 423, 427, 430, 435-444, 449-469, 473-486, 491-505, 508-509, 513-522, 526-527, 531-532, 536-542, 546 /usr/local/lib/python3.8/dist-packages/zmq/sugar/__init__.py 15 0 100% /usr/local/lib/python3.8/dist-packages/zmq/sugar/attrsettr.py 29 21 28% 15-32, 36, 40-48, 52 /usr/local/lib/python3.8/dist-packages/zmq/sugar/constants.py 53 5 91% 34, 47, 104, 107-108 /usr/local/lib/python3.8/dist-packages/zmq/sugar/context.py 125 78 38% 27, 43-49, 53-54, 57, 60, 64, 77-79, 89-94, 119-132, 139-145, 152-154, 157-163, 180-192, 196, 210-222, 229, 236, 240-243, 247-253, 257-266 /usr/local/lib/python3.8/dist-packages/zmq/sugar/frame.py 29 12 59% 12-14, 51, 61-62, 66-67, 77-78, 82-83 /usr/local/lib/python3.8/dist-packages/zmq/sugar/poll.py 62 48 23% 22-23, 26, 44-57, 61, 71-75, 95-99, 126-152 /usr/local/lib/python3.8/dist-packages/zmq/sugar/socket.py 229 160 30% 32, 39-40, 59-63, 66-67, 75, 78, 86, 99-101, 104-106, 114-117, 124-132, 142-155, 166, 175-177, 186-188, 207-209, 229-231, 261-283, 290-300, 313-328, 390-400, 431-447, 475-481, 499, 519-520, 548-549, 566-568, 592-593, 610-611, 631-632, 646-651, 673-674, 697-704, 725-746, 754-755 /usr/local/lib/python3.8/dist-packages/zmq/sugar/stopwatch.py 15 11 27% 12-21, 25, 29-30 /usr/local/lib/python3.8/dist-packages/zmq/sugar/tracker.py 56 37 34% 54-63, 68-74, 96-118 /usr/local/lib/python3.8/dist-packages/zmq/sugar/version.py 20 7 65% 17-18, 26-29, 36, 41 /usr/local/lib/python3.8/dist-packages/zmq/utils/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/zmq/utils/constant_names.py 16 1 94% 549 /usr/local/lib/python3.8/dist-packages/zmq/utils/jsonapi.py 21 11 48% 26-27, 37-45, 53-56 /usr/local/lib/python3.8/dist-packages/zmq/utils/strtypes.py 23 13 43% 18-20, 24-29, 33-38 ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ TOTAL 809902 560608 31% ret : 0 command : coverage3 html -i --omit=/usr/local/lib/python3.8/dist-packages/*,/home/admin/.local/lib/python3.8/site-packages/*,/usr/lib/python3/dist-packages/* -d htmlcov ret : 0 command : coverage3 report -i -m ret : 0 321.04user 102.56system 19:05.67elapsed 36%CPU (0avgtext+0avgdata 6529972maxresident)k 6874352inputs+995752outputs (21370major+13250232minor)pagefaults 0swaps