#&_# 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 : 7035 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 : 0.15194177627563477 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 Thu Apr 17 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 : 7035 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 2025-04-17 05:20:34.041506: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-04-17 05:20:34.071156: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-04-17 05:20:34.073441: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f8068000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-04-17 05:20:34.073493: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-04-17 05:20:34.078002: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-04-17 05:20:34.371419: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x221251a0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-04-17 05:20:34.371473: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-04-17 05:20:34.372712: 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 2025-04-17 05:20:34.373174: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-17 05:20:34.376854: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-17 05:20:34.379898: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-17 05:20:34.380241: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-17 05:20:34.382417: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-17 05:20:34.383551: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-17 05:20:34.388657: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-17 05:20:34.389930: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-17 05:20:34.390023: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-17 05:20:34.390742: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-17 05:20:34.390759: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-17 05:20:34.390768: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-17 05:20:34.394810: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6432 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 2025-04-17 05:20:35.478388: 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 2025-04-17 05:20:35.478500: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-17 05:20:35.478521: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-17 05:20:35.478537: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-17 05:20:35.478554: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-17 05:20:35.478574: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-17 05:20:35.478592: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-17 05:20:35.478610: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-17 05:20:35.479816: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-17 05:20:35.481193: 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 2025-04-17 05:20:35.481283: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-17 05:20:35.481315: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-17 05:20:35.481343: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-17 05:20:35.481377: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-17 05:20:35.481407: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-17 05:20:35.481444: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-17 05:20:35.481475: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-17 05:20:35.483273: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-17 05:20:35.483338: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-17 05:20:35.483354: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-17 05:20:35.483364: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-17 05:20:35.484843: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6432 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 : [] 2025-04-17 05:20:46.446510: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-17 05:20:46.720203: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-17 05:20:48.431969: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.432594: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 3.60G (3865470464 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.433206: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 3.24G (3478923264 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.433766: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.92G (3131030784 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.434333: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.62G (2817927680 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.434957: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.36G (2536134912 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.435525: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 2.12G (2282521344 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.435567: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-17 05:20:48.436144: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.436161: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-17 05:20:48.447011: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.447043: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-17 05:20:48.447616: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.447633: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-17 05:20:48.454274: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.454297: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 466.56MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-17 05:20:48.454871: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.454886: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 466.56MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-17 05:20:48.502341: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.502421: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-17 05:20:48.503065: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.503102: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.06GiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-17 05:20:48.511836: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.511926: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 243.25MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-17 05:20:48.512520: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.512540: W tensorflow/core/common_runtime/bfc_allocator.cc:245] Allocator (GPU_0_bfc) ran out of memory trying to allocate 243.25MiB with freed_by_count=0. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory were available. 2025-04-17 05:20:48.564863: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.565845: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.568702: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.569657: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.645208: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.645864: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.648452: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.649059: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.657328: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.658082: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.664820: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.665453: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.680195: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.680844: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.682794: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.683440: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.690578: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.691224: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.694152: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.694771: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.702885: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.703638: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.705515: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.706139: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.742201: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.742879: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.743495: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.744257: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.748855: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.749642: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.770373: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.771124: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.771722: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.772340: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.789155: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.789818: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.790449: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.791081: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.796441: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.797139: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.803217: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.803886: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.820473: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.821663: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.826182: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.826936: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.827664: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.828370: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.852276: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.852879: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.853467: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.854044: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.854607: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.855246: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.855822: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.856395: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.865366: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.865977: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.873132: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.873759: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.906631: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.906712: W tensorflow/core/kernels/gpu_utils.cc:49] Failed to allocate memory for convolution redzone checking; skipping this check. This is benign and only means that we won't check cudnn for out-of-bounds reads and writes. This message will only be printed once. 2025-04-17 05:20:48.907811: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.908852: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.917260: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.918311: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.919391: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.920438: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.929529: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.930576: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.953879: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.954629: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.955217: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.955785: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.960123: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.960711: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.961264: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.962007: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.963922: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.973129: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.973724: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.983985: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.984575: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.985215: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.985767: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.986328: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 2025-04-17 05:20:48.986902: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 4.00G (4294967296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory 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 1837895 begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 1274 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 : 2459 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 : 0.0005514621734619141 nb_pixel_total : 15551 time to create 1 rle with old method : 0.036150455474853516 length of segment : 256 time for calcul the mask position with numpy : 0.002889871597290039 nb_pixel_total : 145333 time to create 1 rle with old method : 0.33181023597717285 length of segment : 371 time for calcul the mask position with numpy : 0.000286102294921875 nb_pixel_total : 14254 time to create 1 rle with old method : 0.03307604789733887 length of segment : 151 time for calcul the mask position with numpy : 0.00016379356384277344 nb_pixel_total : 5613 time to create 1 rle with old method : 0.013804197311401367 length of segment : 48 time for calcul the mask position with numpy : 8.749961853027344e-05 nb_pixel_total : 1825 time to create 1 rle with old method : 0.00456547737121582 length of segment : 39 time spent for convertir_results : 1.3539276123046875 time spend for datou_step_exec : 24.471731662750244 time spend to save output : 5.269050598144531e-05 total time spend for step 1 : 24.471784353256226 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 3327 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 : 0.015304803848266602 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, 0.99549073, [(140, 26, 6), (135, 27, 15), (133, 28, 18), (131, 29, 22), (127, 30, 27), (10, 31, 1), (121, 31, 34), (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, 137), (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, 105), (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)], ['16,276,8,273,3,265,2,261,2,229,1,228,1,114,2,113,2,82,1,81,1,46,3,37,8,32,20,32,21,33,58,33,59,34,75,34,76,35,102,35,115,32,126,31,135,27,145,26,152,29,158,35,158,48,154,54,149,56,138,58,128,61,119,67,105,81,103,86,96,94,89,98,81,109,71,119,65,132,60,138,52,151,45,158,40,166,34,172,29,188,26,193,25,200,25,219,24,270,23,273']), (957285035, 492601069, 445, 29, 591, 24, 419, 0.9923798, [(315, 37, 24), (272, 38, 86), (253, 39, 130), (238, 40, 151), (199, 41, 196), (189, 42, 213), (180, 43, 238), (175, 44, 250), (172, 45, 258), (169, 46, 266), (166, 47, 274), (162, 48, 284), (159, 49, 294), (157, 50, 304), (155, 51, 311), (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, 454), (89, 116, 455), (88, 117, 456), (88, 118, 457), (87, 119, 459), (87, 120, 459), (86, 121, 461), (85, 122, 462), (85, 123, 463), (84, 124, 464), (84, 125, 465), (83, 126, 466), (82, 127, 468), (82, 128, 468), (81, 129, 470), (80, 130, 471), (78, 131, 473), (76, 132, 476), (75, 133, 477), (73, 134, 480), (71, 135, 482), (70, 136, 484), (68, 137, 486), (67, 138, 488), (65, 139, 490), (64, 140, 492), (62, 141, 494), (61, 142, 496), (60, 143, 497), (59, 144, 499), (58, 145, 501), (58, 146, 501), (57, 147, 503), (57, 148, 504), (56, 149, 506), (56, 150, 507), (56, 151, 507), (55, 152, 509), (55, 153, 510), (54, 154, 511), (54, 155, 512), (54, 156, 513), (53, 157, 514), (53, 158, 514), (52, 159, 515), (52, 160, 516), (51, 161, 517), (51, 162, 517), (51, 163, 517), (50, 164, 518), (50, 165, 518), (49, 166, 519), (49, 167, 520), (48, 168, 521), (48, 169, 521), (47, 170, 522), (47, 171, 522), (46, 172, 523), (46, 173, 523), 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['321,407,305,404,263,401,215,388,206,382,178,371,168,363,140,349,110,336,90,330,77,323,56,316,39,299,31,273,31,236,34,199,42,184,58,145,79,131,89,116,89,101,104,88,115,72,159,49,180,43,199,41,237,41,272,38,338,37,382,39,402,43,417,43,460,50,481,55,504,76,543,116,556,143,566,156,568,167,566,186,554,199,548,216,528,235,509,249,414,315,403,339,392,355,383,385,369,400,358,405']), (957285035, 492601069, 445, 485, 636, 23, 174, 0.97117156, [(540, 24, 21), (626, 24, 3), (531, 25, 49), (594, 25, 40), (527, 26, 107), (523, 27, 111), (520, 28, 114), (518, 29, 117), (516, 30, 119), (515, 31, 120), (513, 32, 122), (512, 33, 123), (510, 34, 125), (509, 35, 126), (507, 36, 128), (506, 37, 129), (504, 38, 131), (503, 39, 132), (501, 40, 134), (500, 41, 135), (499, 42, 136), (498, 43, 137), (497, 44, 138), (496, 45, 139), (496, 46, 139), (495, 47, 140), (495, 48, 140), (494, 49, 141), (493, 50, 142), (492, 51, 143), (491, 52, 144), (491, 53, 144), (490, 54, 145), (490, 55, 145), (490, 56, 145), (490, 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119, 77), (559, 120, 76), (560, 121, 75), (560, 122, 75), (561, 123, 74), (561, 124, 74), (561, 125, 74), (562, 126, 73), (562, 127, 73), (563, 128, 72), (563, 129, 72), (564, 130, 70), (564, 131, 70), (565, 132, 69), (565, 133, 68), (565, 134, 68), (565, 135, 67), (566, 136, 65), (566, 137, 64), (566, 138, 64), (566, 139, 62), (566, 140, 61), (566, 141, 59), (566, 142, 57), (566, 143, 56), (566, 144, 55), (566, 145, 54), (567, 146, 53), (567, 147, 52), (567, 148, 51), (568, 149, 50), (568, 150, 49), (568, 151, 48), (568, 152, 47), (569, 153, 45), (569, 154, 44), (570, 155, 42), (570, 156, 42), (570, 157, 41), (571, 158, 39), (571, 159, 39), (572, 160, 37), (572, 161, 37), (573, 162, 35), (573, 163, 34), (573, 164, 34), (574, 165, 32), (575, 166, 30), (577, 167, 28), (578, 168, 26), (581, 169, 22), (584, 170, 19), (587, 171, 15), (591, 172, 8)], ['598,172,591,172,590,171,578,168,573,164,573,162,568,152,568,149,566,145,566,136,565,132,561,125,560,121,556,116,547,109,543,108,536,104,531,99,527,97,491,62,490,54,495,48,496,45,502,40,516,30,523,27,531,25,539,25,540,24,560,24,561,25,579,25,580,26,593,26,594,25,633,25,634,29,634,56,635,57,635,111,634,112,634,129,632,134,629,138,623,141,619,145,617,149,611,155,608,161,604,166']), (957285035, 492601069, 445, 280, 481, 2, 55, 0.83024913, [(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, 44), (432, 38, 41), (434, 39, 40), (436, 40, 39), (438, 41, 37), (441, 42, 35), (444, 43, 32), (448, 44, 29), (452, 45, 25), (454, 46, 23), (459, 47, 17), (463, 48, 12), (468, 49, 5)], ['472,49,468,49,467,48,459,47,458,46,454,46,451,44,448,44,447,43,444,43,440,41,438,41,428,36,424,36,423,35,419,35,418,34,409,34,408,33,401,33,400,32,371,32,370,31,337,31,336,30,283,31,281,29,281,6,284,4,291,4,292,3,419,3,420,4,429,4,430,5,432,5,436,7,441,11,445,12,453,16,456,19,457,19,465,27,465,29,472,37,476,44,476,46']), (957285035, 492601069, 445, 456, 547, 6, 45, 0.7416694, [(482, 8, 19), (463, 9, 4), (481, 9, 44), (457, 10, 12), (479, 10, 50), (457, 11, 13), (476, 11, 56), (457, 12, 15), (475, 12, 65), (457, 13, 84), (457, 14, 85), (457, 15, 89), (457, 16, 89), (458, 17, 88), (459, 18, 87), (460, 19, 86), (461, 20, 80), (464, 21, 71), (466, 22, 63), (467, 23, 59), (468, 24, 55), (469, 25, 52), (469, 26, 51), (470, 27, 48), (471, 28, 46), (471, 29, 44), (472, 30, 42), (473, 31, 39), (473, 32, 38), (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)], ['492,42,488,42,487,41,480,41,476,37,475,34,473,32,469,25,465,21,461,20,457,16,457,10,466,9,470,12,474,13,476,11,480,10,482,8,500,8,501,9,524,9,525,10,528,10,532,12,539,12,542,15,545,15,545,19,535,20,534,21,529,21,525,23,523,23,513,30,512,30,504,37,496,41,493,41'])], 'temp/1744860029_1837371_957285035_a42482e51c93c8025d243dd179aee85b.jpg']} free memory after detection : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 2459 error , can't release the memory or there are other process who occupe the free memory ERROR test release memory FAILED ############################### 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 : 0.13113093376159668 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 Thu Apr 17 05:20:55 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 Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory havn't enough memory gpu , need / 3000 l 3632 free memory gpu now : 2459 wait 20 seconds l 3637 free memory gpu now : 2459 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-04-17 05:21:19.504315: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-04-17 05:21:19.531141: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz 2025-04-17 05:21:19.533315: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f806c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-04-17 05:21:19.533354: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-04-17 05:21:19.539745: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-04-17 05:21:19.693014: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x22c1a760 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-04-17 05:21:19.693078: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-04-17 05:21:19.693904: 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 2025-04-17 05:21:19.695106: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-17 05:21:19.699003: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-17 05:21:19.703581: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-17 05:21:19.704584: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-17 05:21:19.708536: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-17 05:21:19.710580: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-17 05:21:19.717745: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-17 05:21:19.719016: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-17 05:21:19.719178: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-17 05:21:19.719738: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-17 05:21:19.719760: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-17 05:21:19.719770: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-17 05:21:19.720720: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 168 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. 2025-04-17 05:21:19.856812: 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 2025-04-17 05:21:19.856935: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-17 05:21:19.856960: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-17 05:21:19.856982: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-17 05:21:19.857001: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-17 05:21:19.857021: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-17 05:21:19.857041: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-17 05:21:19.857061: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-17 05:21:19.857907: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-17 05:21:19.859007: 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 2025-04-17 05:21:19.859067: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-04-17 05:21:19.859088: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-04-17 05:21:19.859111: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-04-17 05:21:19.859130: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-04-17 05:21:19.859150: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-04-17 05:21:19.859169: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-04-17 05:21:19.859189: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-04-17 05:21:19.859944: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-04-17 05:21:19.859977: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-04-17 05:21:19.859986: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-04-17 05:21:19.859994: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-04-17 05:21:19.860746: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 168 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) 2025-04-17 05:21:32.470256: W tensorflow/core/common_runtime/bfc_allocator.cc:434] Allocator (GPU_0_bfc) ran out of memory trying to allocate 9.00MiB (rounded to 9437184) Current allocation summary follows. 2025-04-17 05:21:32.470354: I tensorflow/core/common_runtime/bfc_allocator.cc:934] BFCAllocator dump for GPU_0_bfc 2025-04-17 05:21:32.470375: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (256): Total Chunks: 65, Chunks in use: 65. 16.2KiB allocated for chunks. 16.2KiB in use in bin. 8.9KiB client-requested in use in bin. 2025-04-17 05:21:32.470392: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (512): Total Chunks: 40, Chunks in use: 40. 20.0KiB allocated for chunks. 20.0KiB in use in bin. 20.0KiB client-requested in use in bin. 2025-04-17 05:21:32.470409: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1024): Total Chunks: 251, Chunks in use: 251. 251.2KiB allocated for chunks. 251.2KiB in use in bin. 251.0KiB client-requested in use in bin. 2025-04-17 05:21:32.470451: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2048): Total Chunks: 40, Chunks in use: 40. 80.0KiB allocated for chunks. 80.0KiB in use in bin. 80.0KiB client-requested in use in bin. 2025-04-17 05:21:32.470468: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (4096): Total Chunks: 120, Chunks in use: 120. 487.5KiB allocated for chunks. 487.5KiB in use in bin. 480.0KiB client-requested in use in bin. 2025-04-17 05:21:32.470484: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (8192): Total Chunks: 10, Chunks in use: 10. 80.0KiB allocated for chunks. 80.0KiB in use in bin. 80.0KiB client-requested in use in bin. 2025-04-17 05:21:32.470499: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (16384): Total Chunks: 1, Chunks in use: 1. 16.0KiB allocated for chunks. 16.0KiB in use in bin. 16.0KiB client-requested in use in bin. 2025-04-17 05:21:32.470514: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (32768): Total Chunks: 1, Chunks in use: 1. 36.8KiB allocated for chunks. 36.8KiB in use in bin. 36.8KiB client-requested in use in bin. 2025-04-17 05:21:32.470529: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (65536): Total Chunks: 6, Chunks in use: 6. 384.0KiB allocated for chunks. 384.0KiB in use in bin. 384.0KiB client-requested in use in bin. 2025-04-17 05:21:32.470545: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (131072): Total Chunks: 4, Chunks in use: 4. 560.0KiB allocated for chunks. 560.0KiB in use in bin. 560.0KiB client-requested in use in bin. 2025-04-17 05:21:32.470558: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (262144): Total Chunks: 8, Chunks in use: 7. 2.35MiB allocated for chunks. 1.91MiB in use in bin. 1.75MiB client-requested in use in bin. 2025-04-17 05:21:32.470571: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (524288): Total Chunks: 7, Chunks in use: 6. 4.39MiB allocated for chunks. 3.44MiB in use in bin. 3.25MiB client-requested in use in bin. 2025-04-17 05:21:32.470585: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1048576): Total Chunks: 48, Chunks in use: 45. 54.12MiB allocated for chunks. 50.62MiB in use in bin. 45.00MiB client-requested in use in bin. 2025-04-17 05:21:32.470600: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2097152): Total Chunks: 28, Chunks in use: 25. 64.25MiB allocated for chunks. 55.75MiB in use in bin. 55.75MiB client-requested in use in bin. 2025-04-17 05:21:32.470614: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (4194304): Total Chunks: 3, Chunks in use: 2. 14.88MiB allocated for chunks. 10.88MiB in use in bin. 8.00MiB client-requested in use in bin. 2025-04-17 05:21:32.470628: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (8388608): Total Chunks: 3, Chunks in use: 2. 27.00MiB allocated for chunks. 19.00MiB in use in bin. 17.00MiB client-requested in use in bin. 2025-04-17 05:21:32.470640: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (16777216): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-04-17 05:21:32.470652: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (33554432): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-04-17 05:21:32.470664: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (67108864): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-04-17 05:21:32.470675: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (134217728): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-04-17 05:21:32.470687: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (268435456): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-04-17 05:21:32.470711: I tensorflow/core/common_runtime/bfc_allocator.cc:957] Bin for 9.00MiB was 8.00MiB, Chunk State: 2025-04-17 05:21:32.470730: I tensorflow/core/common_runtime/bfc_allocator.cc:963] Size: 8.00MiB | Requested Size: 4.00MiB | in_use: 0 | bin_num: 15, next: Size: 10.00MiB | Requested Size: 8.00MiB | in_use: 1 | bin_num: -1 2025-04-17 05:21:32.470741: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 43909120 2025-04-17 05:21:32.470754: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7e8c000000 of size 8388608 next 624 2025-04-17 05:21:32.470767: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e8c800000 of size 10485760 next 608 2025-04-17 05:21:32.470777: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e8d200000 of size 9437184 next 607 2025-04-17 05:21:32.470788: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e8db00000 of size 4194304 next 630 2025-04-17 05:21:32.470798: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7e8df00000 of size 4194304 next 617 2025-04-17 05:21:32.470809: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e8e300000 of size 7208960 next 18446744073709551615 2025-04-17 05:21:32.470819: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 67108864 2025-04-17 05:21:32.470830: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e90000000 of size 2359296 next 370 2025-04-17 05:21:32.470841: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e90240000 of size 1048576 next 394 2025-04-17 05:21:32.470851: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7e90340000 of size 1310720 next 388 2025-04-17 05:21:32.470861: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e90480000 of size 2359296 next 387 2025-04-17 05:21:32.470871: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e906c0000 of size 1048576 next 412 2025-04-17 05:21:32.470883: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e907c0000 of size 1310720 next 406 2025-04-17 05:21:32.470893: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e90900000 of size 2359296 next 405 2025-04-17 05:21:32.470916: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e90b40000 of size 1048576 next 430 2025-04-17 05:21:32.470927: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e90c40000 of size 1310720 next 424 2025-04-17 05:21:32.470937: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e90d80000 of size 2359296 next 423 2025-04-17 05:21:32.470947: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e90fc0000 of size 1048576 next 447 2025-04-17 05:21:32.470958: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e910c0000 of size 1310720 next 441 2025-04-17 05:21:32.470968: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e91200000 of size 2359296 next 440 2025-04-17 05:21:32.470978: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e91440000 of size 1048576 next 465 2025-04-17 05:21:32.470988: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e91540000 of size 1310720 next 459 2025-04-17 05:21:32.470999: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e91680000 of size 2359296 next 458 2025-04-17 05:21:32.471009: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e918c0000 of size 1048576 next 483 2025-04-17 05:21:32.471022: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e919c0000 of size 1310720 next 477 2025-04-17 05:21:32.471033: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e91b00000 of size 2359296 next 476 2025-04-17 05:21:32.471043: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e91d40000 of size 1048576 next 501 2025-04-17 05:21:32.471061: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e91e40000 of size 1310720 next 495 2025-04-17 05:21:32.471072: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e91f80000 of size 2359296 next 494 2025-04-17 05:21:32.471084: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e921c0000 of size 1048576 next 519 2025-04-17 05:21:32.471096: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e922c0000 of size 1310720 next 513 2025-04-17 05:21:32.471107: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e92400000 of size 2359296 next 512 2025-04-17 05:21:32.471118: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e92640000 of size 1048576 next 537 2025-04-17 05:21:32.471130: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e92740000 of size 1310720 next 531 2025-04-17 05:21:32.471141: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e92880000 of size 2359296 next 530 2025-04-17 05:21:32.471153: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e92ac0000 of size 1048576 next 555 2025-04-17 05:21:32.471164: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e92bc0000 of size 1310720 next 549 2025-04-17 05:21:32.471176: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e92d00000 of size 2359296 next 548 2025-04-17 05:21:32.471187: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e92f40000 of size 1048576 next 573 2025-04-17 05:21:32.471198: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e93040000 of size 1310720 next 567 2025-04-17 05:21:32.471208: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e93180000 of size 2359296 next 566 2025-04-17 05:21:32.471220: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e933c0000 of size 1048576 next 591 2025-04-17 05:21:32.471232: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7e934c0000 of size 1310720 next 585 2025-04-17 05:21:32.471243: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e93600000 of size 2359296 next 584 2025-04-17 05:21:32.471255: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7e93840000 of size 2097152 next 597 2025-04-17 05:21:32.471267: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e93a40000 of size 2097152 next 596 2025-04-17 05:21:32.471279: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7e93c40000 of size 3932160 next 18446744073709551615 2025-04-17 05:21:32.471290: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 33554432 2025-04-17 05:21:32.471302: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e94000000 of size 2359296 next 245 2025-04-17 05:21:32.471314: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e94240000 of size 1048576 next 269 2025-04-17 05:21:32.471325: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e94340000 of size 1310720 next 263 2025-04-17 05:21:32.471337: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e94480000 of size 2359296 next 262 2025-04-17 05:21:32.471348: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e946c0000 of size 1048576 next 287 2025-04-17 05:21:32.471360: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e947c0000 of size 1310720 next 281 2025-04-17 05:21:32.471371: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e94900000 of size 2359296 next 280 2025-04-17 05:21:32.471382: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e94b40000 of size 1048576 next 304 2025-04-17 05:21:32.471394: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e94c40000 of size 1310720 next 298 2025-04-17 05:21:32.471405: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e94d80000 of size 2359296 next 297 2025-04-17 05:21:32.471416: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e94fc0000 of size 1048576 next 322 2025-04-17 05:21:32.471437: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e950c0000 of size 1310720 next 316 2025-04-17 05:21:32.471449: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e95200000 of size 2359296 next 315 2025-04-17 05:21:32.471461: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e95440000 of size 1048576 next 340 2025-04-17 05:21:32.471471: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e95540000 of size 1310720 next 334 2025-04-17 05:21:32.471482: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e95680000 of size 2359296 next 333 2025-04-17 05:21:32.471492: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e958c0000 of size 1048576 next 358 2025-04-17 05:21:32.471502: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e959c0000 of size 1310720 next 352 2025-04-17 05:21:32.471512: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e95b00000 of size 2359296 next 351 2025-04-17 05:21:32.471522: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e95d40000 of size 1048576 next 376 2025-04-17 05:21:32.471532: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e95e40000 of size 1835008 next 18446744073709551615 2025-04-17 05:21:32.471544: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 16777216 2025-04-17 05:21:32.471555: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e96000000 of size 2359296 next 181 2025-04-17 05:21:32.471565: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e96240000 of size 2097152 next 196 2025-04-17 05:21:32.471577: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e96440000 of size 1048576 next 216 2025-04-17 05:21:32.471589: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e96540000 of size 1310720 next 209 2025-04-17 05:21:32.471601: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e96680000 of size 2359296 next 208 2025-04-17 05:21:32.471612: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e968c0000 of size 1048576 next 234 2025-04-17 05:21:32.471623: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e969c0000 of size 1310720 next 228 2025-04-17 05:21:32.471633: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e96b00000 of size 2359296 next 227 2025-04-17 05:21:32.471643: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7e96d40000 of size 2883584 next 18446744073709551615 2025-04-17 05:21:32.471653: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 2097152 2025-04-17 05:21:32.471663: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98600000 of size 147456 next 55 2025-04-17 05:21:32.471675: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98624000 of size 65536 next 78 2025-04-17 05:21:32.471685: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98634000 of size 4096 next 191 2025-04-17 05:21:32.471695: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98635000 of size 4096 next 192 2025-04-17 05:21:32.471705: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98636000 of size 4096 next 193 2025-04-17 05:21:32.471716: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98637000 of size 256 next 194 2025-04-17 05:21:32.471726: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98637100 of size 256 next 195 2025-04-17 05:21:32.471736: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98637200 of size 4096 next 197 2025-04-17 05:21:32.471747: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98638200 of size 4096 next 198 2025-04-17 05:21:32.471757: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98639200 of size 4096 next 199 2025-04-17 05:21:32.471767: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863a200 of size 4096 next 200 2025-04-17 05:21:32.471784: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863b200 of size 4096 next 201 2025-04-17 05:21:32.471796: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863c200 of size 1024 next 202 2025-04-17 05:21:32.471806: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863c600 of size 1024 next 204 2025-04-17 05:21:32.471816: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863ca00 of size 1024 next 205 2025-04-17 05:21:32.471826: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863ce00 of size 1024 next 206 2025-04-17 05:21:32.471836: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863d200 of size 1024 next 207 2025-04-17 05:21:32.471846: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863d600 of size 1024 next 210 2025-04-17 05:21:32.471857: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863da00 of size 1024 next 211 2025-04-17 05:21:32.471867: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863de00 of size 1024 next 212 2025-04-17 05:21:32.471878: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863e200 of size 1024 next 213 2025-04-17 05:21:32.471889: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863e600 of size 1024 next 214 2025-04-17 05:21:32.471899: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863ea00 of size 4096 next 215 2025-04-17 05:21:32.471909: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9863fa00 of size 4096 next 217 2025-04-17 05:21:32.471919: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98640a00 of size 4096 next 218 2025-04-17 05:21:32.471930: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98641a00 of size 4096 next 219 2025-04-17 05:21:32.471940: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98642a00 of size 4096 next 220 2025-04-17 05:21:32.471951: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98643a00 of size 1024 next 221 2025-04-17 05:21:32.471961: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98643e00 of size 1024 next 223 2025-04-17 05:21:32.471973: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98644200 of size 1024 next 224 2025-04-17 05:21:32.471985: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98644600 of size 1024 next 225 2025-04-17 05:21:32.471995: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98644a00 of size 1024 next 226 2025-04-17 05:21:32.472007: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98644e00 of size 1024 next 229 2025-04-17 05:21:32.472018: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98645200 of size 1024 next 230 2025-04-17 05:21:32.472030: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98645600 of size 1024 next 231 2025-04-17 05:21:32.472041: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98645a00 of size 1024 next 232 2025-04-17 05:21:32.472052: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98645e00 of size 1024 next 233 2025-04-17 05:21:32.472064: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98646200 of size 7680 next 72 2025-04-17 05:21:32.472076: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98648000 of size 147456 next 71 2025-04-17 05:21:32.472087: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9866c000 of size 131072 next 87 2025-04-17 05:21:32.472098: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9868c000 of size 4096 next 289 2025-04-17 05:21:32.472108: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9868d000 of size 4096 next 290 2025-04-17 05:21:32.472118: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9868e000 of size 4096 next 291 2025-04-17 05:21:32.472136: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9868f000 of size 1024 next 292 2025-04-17 05:21:32.472146: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9868f400 of size 1024 next 293 2025-04-17 05:21:32.472157: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9868f800 of size 1024 next 294 2025-04-17 05:21:32.472167: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9868fc00 of size 1024 next 295 2025-04-17 05:21:32.472177: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98690000 of size 1024 next 296 2025-04-17 05:21:32.472187: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98690400 of size 1024 next 299 2025-04-17 05:21:32.472197: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98690800 of size 1024 next 300 2025-04-17 05:21:32.472207: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98690c00 of size 1024 next 301 2025-04-17 05:21:32.472217: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98691000 of size 1024 next 302 2025-04-17 05:21:32.472227: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98691400 of size 1024 next 303 2025-04-17 05:21:32.472237: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98691800 of size 4096 next 305 2025-04-17 05:21:32.472247: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98692800 of size 4096 next 306 2025-04-17 05:21:32.472265: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98693800 of size 4096 next 307 2025-04-17 05:21:32.472275: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98694800 of size 4096 next 308 2025-04-17 05:21:32.472285: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98695800 of size 4096 next 309 2025-04-17 05:21:32.472295: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98696800 of size 1024 next 310 2025-04-17 05:21:32.472305: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98696c00 of size 1024 next 311 2025-04-17 05:21:32.472316: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98697000 of size 1024 next 312 2025-04-17 05:21:32.472326: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98697400 of size 1024 next 313 2025-04-17 05:21:32.472336: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98697800 of size 1024 next 314 2025-04-17 05:21:32.472346: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98697c00 of size 1024 next 317 2025-04-17 05:21:32.472356: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98698000 of size 1024 next 318 2025-04-17 05:21:32.472371: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98698400 of size 1024 next 319 2025-04-17 05:21:32.472382: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98698800 of size 1024 next 320 2025-04-17 05:21:32.472393: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98698c00 of size 1024 next 321 2025-04-17 05:21:32.472403: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98699000 of size 4096 next 323 2025-04-17 05:21:32.472413: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869a000 of size 4096 next 324 2025-04-17 05:21:32.472426: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869b000 of size 4096 next 325 2025-04-17 05:21:32.472436: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869c000 of size 4096 next 326 2025-04-17 05:21:32.472446: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869d000 of size 4096 next 327 2025-04-17 05:21:32.472457: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869e000 of size 1024 next 328 2025-04-17 05:21:32.472466: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869e400 of size 1024 next 329 2025-04-17 05:21:32.472485: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869e800 of size 1024 next 330 2025-04-17 05:21:32.472496: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869ec00 of size 1024 next 331 2025-04-17 05:21:32.472506: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869f000 of size 1024 next 332 2025-04-17 05:21:32.472516: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869f400 of size 1024 next 335 2025-04-17 05:21:32.472526: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869f800 of size 1024 next 336 2025-04-17 05:21:32.472536: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9869fc00 of size 1024 next 337 2025-04-17 05:21:32.472546: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a0000 of size 1024 next 338 2025-04-17 05:21:32.472556: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a0400 of size 1024 next 339 2025-04-17 05:21:32.472566: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a0800 of size 4096 next 341 2025-04-17 05:21:32.472576: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a1800 of size 4096 next 342 2025-04-17 05:21:32.472587: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a2800 of size 4096 next 343 2025-04-17 05:21:32.472597: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a3800 of size 4096 next 344 2025-04-17 05:21:32.472607: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a4800 of size 4096 next 345 2025-04-17 05:21:32.472618: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a5800 of size 1024 next 346 2025-04-17 05:21:32.472629: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a5c00 of size 1024 next 347 2025-04-17 05:21:32.472641: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a6000 of size 1024 next 348 2025-04-17 05:21:32.472653: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a6400 of size 1024 next 349 2025-04-17 05:21:32.472664: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a6800 of size 1024 next 350 2025-04-17 05:21:32.472674: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a6c00 of size 1024 next 353 2025-04-17 05:21:32.472684: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a7000 of size 1024 next 354 2025-04-17 05:21:32.472694: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a7400 of size 1024 next 355 2025-04-17 05:21:32.472704: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a7800 of size 1024 next 356 2025-04-17 05:21:32.472714: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a7c00 of size 1024 next 357 2025-04-17 05:21:32.472724: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a8000 of size 4096 next 359 2025-04-17 05:21:32.472735: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986a9000 of size 4096 next 360 2025-04-17 05:21:32.472745: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986aa000 of size 4096 next 361 2025-04-17 05:21:32.472755: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986ab000 of size 4096 next 362 2025-04-17 05:21:32.472765: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986ac000 of size 4096 next 363 2025-04-17 05:21:32.472775: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986ad000 of size 1024 next 364 2025-04-17 05:21:32.472785: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986ad400 of size 1024 next 365 2025-04-17 05:21:32.472795: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986ad800 of size 1024 next 366 2025-04-17 05:21:32.472805: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986adc00 of size 1024 next 367 2025-04-17 05:21:32.472823: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986ae000 of size 1024 next 368 2025-04-17 05:21:32.472833: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986ae400 of size 1024 next 371 2025-04-17 05:21:32.472844: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986ae800 of size 1024 next 372 2025-04-17 05:21:32.472854: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986aec00 of size 1024 next 373 2025-04-17 05:21:32.472864: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986af000 of size 1024 next 374 2025-04-17 05:21:32.472874: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986af400 of size 1024 next 375 2025-04-17 05:21:32.472884: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986af800 of size 4096 next 377 2025-04-17 05:21:32.472894: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b0800 of size 4096 next 378 2025-04-17 05:21:32.472904: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b1800 of size 4096 next 379 2025-04-17 05:21:32.472914: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b2800 of size 4096 next 380 2025-04-17 05:21:32.472924: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b3800 of size 4096 next 381 2025-04-17 05:21:32.472934: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b4800 of size 1024 next 382 2025-04-17 05:21:32.472944: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b4c00 of size 1024 next 383 2025-04-17 05:21:32.472954: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b5000 of size 1024 next 384 2025-04-17 05:21:32.472964: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b5400 of size 1024 next 385 2025-04-17 05:21:32.472974: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b5800 of size 1024 next 386 2025-04-17 05:21:32.472985: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b5c00 of size 1024 next 389 2025-04-17 05:21:32.472995: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b6000 of size 1024 next 390 2025-04-17 05:21:32.473006: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b6400 of size 1024 next 391 2025-04-17 05:21:32.473016: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b6800 of size 1024 next 392 2025-04-17 05:21:32.473026: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b6c00 of size 1024 next 393 2025-04-17 05:21:32.473037: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b7000 of size 4096 next 395 2025-04-17 05:21:32.473047: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b8000 of size 4096 next 396 2025-04-17 05:21:32.473057: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986b9000 of size 4096 next 397 2025-04-17 05:21:32.473067: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986ba000 of size 4096 next 398 2025-04-17 05:21:32.473077: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986bb000 of size 4096 next 399 2025-04-17 05:21:32.473087: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986bc000 of size 1024 next 400 2025-04-17 05:21:32.473097: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986bc400 of size 1024 next 401 2025-04-17 05:21:32.473107: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986bc800 of size 1024 next 402 2025-04-17 05:21:32.473117: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986bcc00 of size 1024 next 403 2025-04-17 05:21:32.473128: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986bd000 of size 1024 next 404 2025-04-17 05:21:32.473138: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986bd400 of size 1024 next 407 2025-04-17 05:21:32.473148: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986bd800 of size 1024 next 408 2025-04-17 05:21:32.473166: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986bdc00 of size 1024 next 409 2025-04-17 05:21:32.473176: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986be000 of size 1024 next 410 2025-04-17 05:21:32.473187: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986be400 of size 1024 next 411 2025-04-17 05:21:32.473199: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986be800 of size 4096 next 413 2025-04-17 05:21:32.473210: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986bf800 of size 4096 next 414 2025-04-17 05:21:32.473221: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c0800 of size 4096 next 415 2025-04-17 05:21:32.473231: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c1800 of size 4096 next 416 2025-04-17 05:21:32.473241: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c2800 of size 4096 next 417 2025-04-17 05:21:32.473253: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c3800 of size 1024 next 418 2025-04-17 05:21:32.473264: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c3c00 of size 1024 next 419 2025-04-17 05:21:32.473276: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c4000 of size 1024 next 420 2025-04-17 05:21:32.473287: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c4400 of size 1024 next 421 2025-04-17 05:21:32.473298: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c4800 of size 1024 next 422 2025-04-17 05:21:32.473310: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c4c00 of size 1024 next 425 2025-04-17 05:21:32.473322: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c5000 of size 1024 next 426 2025-04-17 05:21:32.473332: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c5400 of size 1024 next 427 2025-04-17 05:21:32.473344: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c5800 of size 1024 next 428 2025-04-17 05:21:32.473356: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c5c00 of size 1024 next 429 2025-04-17 05:21:32.473367: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c6000 of size 4096 next 431 2025-04-17 05:21:32.473379: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c7000 of size 4096 next 432 2025-04-17 05:21:32.473389: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c8000 of size 4096 next 433 2025-04-17 05:21:32.473402: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986c9000 of size 4096 next 434 2025-04-17 05:21:32.473413: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986ca000 of size 4096 next 435 2025-04-17 05:21:32.473425: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986cb000 of size 1024 next 436 2025-04-17 05:21:32.473436: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986cb400 of size 1024 next 437 2025-04-17 05:21:32.473447: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986cb800 of size 1024 next 438 2025-04-17 05:21:32.473458: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986cbc00 of size 1024 next 103 2025-04-17 05:21:32.473469: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e986cc000 of size 262144 next 102 2025-04-17 05:21:32.473480: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7e9870c000 of size 999424 next 18446744073709551615 2025-04-17 05:21:32.473491: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 4194304 2025-04-17 05:21:32.473503: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98800000 of size 589824 next 96 2025-04-17 05:21:32.473514: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98890000 of size 262144 next 117 2025-04-17 05:21:32.473535: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d0000 of size 1024 next 439 2025-04-17 05:21:32.473547: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d0400 of size 1024 next 442 2025-04-17 05:21:32.473559: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d0800 of size 1024 next 443 2025-04-17 05:21:32.473570: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d0c00 of size 1024 next 444 2025-04-17 05:21:32.473581: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d1000 of size 1024 next 445 2025-04-17 05:21:32.473593: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d1400 of size 1024 next 446 2025-04-17 05:21:32.473604: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d1800 of size 4096 next 448 2025-04-17 05:21:32.473615: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d2800 of size 4096 next 449 2025-04-17 05:21:32.473627: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d3800 of size 4096 next 450 2025-04-17 05:21:32.473638: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d4800 of size 4096 next 451 2025-04-17 05:21:32.473650: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d5800 of size 4096 next 452 2025-04-17 05:21:32.473661: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d6800 of size 1024 next 453 2025-04-17 05:21:32.473672: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d6c00 of size 1024 next 454 2025-04-17 05:21:32.473684: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d7000 of size 1024 next 455 2025-04-17 05:21:32.473695: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d7400 of size 1024 next 456 2025-04-17 05:21:32.473707: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d7800 of size 1024 next 457 2025-04-17 05:21:32.473718: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d7c00 of size 1024 next 460 2025-04-17 05:21:32.473729: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d8000 of size 1024 next 461 2025-04-17 05:21:32.473740: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d8400 of size 1024 next 462 2025-04-17 05:21:32.473752: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d8800 of size 1024 next 463 2025-04-17 05:21:32.473763: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d8c00 of size 1024 next 464 2025-04-17 05:21:32.473774: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988d9000 of size 4096 next 466 2025-04-17 05:21:32.473786: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988da000 of size 4096 next 467 2025-04-17 05:21:32.473797: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988db000 of size 4096 next 468 2025-04-17 05:21:32.473808: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988dc000 of size 4096 next 469 2025-04-17 05:21:32.473820: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988dd000 of size 4096 next 470 2025-04-17 05:21:32.473831: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988de000 of size 1024 next 471 2025-04-17 05:21:32.473842: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988de400 of size 1024 next 472 2025-04-17 05:21:32.473854: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988de800 of size 1024 next 473 2025-04-17 05:21:32.473865: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988dec00 of size 1024 next 474 2025-04-17 05:21:32.473877: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988df000 of size 1024 next 475 2025-04-17 05:21:32.473887: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988df400 of size 1024 next 478 2025-04-17 05:21:32.473907: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988df800 of size 1024 next 479 2025-04-17 05:21:32.473919: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988dfc00 of size 1024 next 480 2025-04-17 05:21:32.473931: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e0000 of size 1024 next 481 2025-04-17 05:21:32.473942: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e0400 of size 1024 next 482 2025-04-17 05:21:32.473952: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e0800 of size 4096 next 484 2025-04-17 05:21:32.473962: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e1800 of size 4096 next 485 2025-04-17 05:21:32.473972: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e2800 of size 4096 next 486 2025-04-17 05:21:32.473982: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e3800 of size 4096 next 487 2025-04-17 05:21:32.473992: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e4800 of size 4096 next 488 2025-04-17 05:21:32.474002: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e5800 of size 1024 next 489 2025-04-17 05:21:32.474012: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e5c00 of size 1024 next 490 2025-04-17 05:21:32.474022: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e6000 of size 1024 next 491 2025-04-17 05:21:32.474032: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e6400 of size 1024 next 492 2025-04-17 05:21:32.474042: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e6800 of size 1024 next 493 2025-04-17 05:21:32.474052: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e6c00 of size 1024 next 496 2025-04-17 05:21:32.474062: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e7000 of size 1024 next 497 2025-04-17 05:21:32.474072: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e7400 of size 1024 next 498 2025-04-17 05:21:32.474082: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e7800 of size 1024 next 499 2025-04-17 05:21:32.474092: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e7c00 of size 1024 next 500 2025-04-17 05:21:32.474103: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e8000 of size 4096 next 502 2025-04-17 05:21:32.474113: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988e9000 of size 4096 next 503 2025-04-17 05:21:32.474123: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ea000 of size 4096 next 504 2025-04-17 05:21:32.474133: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988eb000 of size 4096 next 505 2025-04-17 05:21:32.474143: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ec000 of size 4096 next 506 2025-04-17 05:21:32.474153: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ed000 of size 1024 next 507 2025-04-17 05:21:32.474163: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ed400 of size 1024 next 508 2025-04-17 05:21:32.474173: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ed800 of size 1024 next 509 2025-04-17 05:21:32.474183: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988edc00 of size 1024 next 510 2025-04-17 05:21:32.474193: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ee000 of size 1024 next 511 2025-04-17 05:21:32.474203: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ee400 of size 1024 next 514 2025-04-17 05:21:32.474214: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ee800 of size 1024 next 515 2025-04-17 05:21:32.474224: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988eec00 of size 1024 next 516 2025-04-17 05:21:32.474241: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ef000 of size 1024 next 517 2025-04-17 05:21:32.474252: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ef400 of size 1024 next 518 2025-04-17 05:21:32.474262: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ef800 of size 4096 next 520 2025-04-17 05:21:32.474272: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f0800 of size 4096 next 521 2025-04-17 05:21:32.474283: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f1800 of size 4096 next 522 2025-04-17 05:21:32.474293: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f2800 of size 4096 next 523 2025-04-17 05:21:32.474303: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f3800 of size 4096 next 524 2025-04-17 05:21:32.474313: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f4800 of size 1024 next 525 2025-04-17 05:21:32.474323: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f4c00 of size 1024 next 526 2025-04-17 05:21:32.474333: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f5000 of size 1024 next 527 2025-04-17 05:21:32.474343: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f5400 of size 1024 next 528 2025-04-17 05:21:32.474354: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f5800 of size 1024 next 529 2025-04-17 05:21:32.474364: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f5c00 of size 1024 next 532 2025-04-17 05:21:32.474374: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f6000 of size 1024 next 533 2025-04-17 05:21:32.474384: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f6400 of size 1024 next 534 2025-04-17 05:21:32.474394: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f6800 of size 1024 next 535 2025-04-17 05:21:32.474404: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f6c00 of size 1024 next 536 2025-04-17 05:21:32.474414: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f7000 of size 4096 next 538 2025-04-17 05:21:32.474424: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f8000 of size 4096 next 539 2025-04-17 05:21:32.474434: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988f9000 of size 4096 next 540 2025-04-17 05:21:32.474444: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fa000 of size 4096 next 541 2025-04-17 05:21:32.474454: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fb000 of size 4096 next 542 2025-04-17 05:21:32.474464: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fc000 of size 1024 next 543 2025-04-17 05:21:32.474474: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fc400 of size 1024 next 544 2025-04-17 05:21:32.474484: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fc800 of size 1024 next 545 2025-04-17 05:21:32.474494: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fcc00 of size 1024 next 546 2025-04-17 05:21:32.474504: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fd000 of size 1024 next 547 2025-04-17 05:21:32.474517: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fd400 of size 1024 next 550 2025-04-17 05:21:32.474528: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fd800 of size 1024 next 551 2025-04-17 05:21:32.474539: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fdc00 of size 1024 next 552 2025-04-17 05:21:32.474551: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fe000 of size 1024 next 553 2025-04-17 05:21:32.474562: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fe400 of size 1024 next 554 2025-04-17 05:21:32.474584: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988fe800 of size 4096 next 556 2025-04-17 05:21:32.474595: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e988ff800 of size 4096 next 557 2025-04-17 05:21:32.474605: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98900800 of size 4096 next 558 2025-04-17 05:21:32.474616: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98901800 of size 4096 next 559 2025-04-17 05:21:32.474626: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98902800 of size 4096 next 560 2025-04-17 05:21:32.474636: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98903800 of size 1024 next 561 2025-04-17 05:21:32.474646: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98903c00 of size 1024 next 562 2025-04-17 05:21:32.474656: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98904000 of size 1024 next 563 2025-04-17 05:21:32.474666: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98904400 of size 1024 next 564 2025-04-17 05:21:32.474676: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98904800 of size 1024 next 565 2025-04-17 05:21:32.474686: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98904c00 of size 1024 next 568 2025-04-17 05:21:32.474696: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98905000 of size 1024 next 569 2025-04-17 05:21:32.474706: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98905400 of size 1024 next 570 2025-04-17 05:21:32.474717: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98905800 of size 1024 next 571 2025-04-17 05:21:32.474727: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98905c00 of size 1024 next 572 2025-04-17 05:21:32.474737: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98906000 of size 4096 next 574 2025-04-17 05:21:32.474747: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98907000 of size 4096 next 575 2025-04-17 05:21:32.474757: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98908000 of size 4096 next 576 2025-04-17 05:21:32.474767: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98909000 of size 4096 next 577 2025-04-17 05:21:32.474777: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890a000 of size 4096 next 578 2025-04-17 05:21:32.474787: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890b000 of size 1024 next 579 2025-04-17 05:21:32.474797: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890b400 of size 1024 next 580 2025-04-17 05:21:32.474807: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890b800 of size 1024 next 581 2025-04-17 05:21:32.474817: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890bc00 of size 1024 next 582 2025-04-17 05:21:32.474827: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890c000 of size 1024 next 583 2025-04-17 05:21:32.474837: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890c400 of size 1024 next 586 2025-04-17 05:21:32.474847: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890c800 of size 1024 next 587 2025-04-17 05:21:32.474857: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890cc00 of size 1024 next 588 2025-04-17 05:21:32.474867: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890d000 of size 1024 next 589 2025-04-17 05:21:32.474878: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890d400 of size 1024 next 590 2025-04-17 05:21:32.474888: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890d800 of size 4096 next 592 2025-04-17 05:21:32.474905: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e9890e800 of size 6144 next 112 2025-04-17 05:21:32.474918: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98910000 of size 524288 next 111 2025-04-17 05:21:32.474937: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98990000 of size 262144 next 135 2025-04-17 05:21:32.474949: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e989d0000 of size 327680 next 124 2025-04-17 05:21:32.474959: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98a20000 of size 589824 next 123 2025-04-17 05:21:32.474969: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98ab0000 of size 262144 next 152 2025-04-17 05:21:32.474979: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98af0000 of size 327680 next 142 2025-04-17 05:21:32.474990: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98b40000 of size 786432 next 18446744073709551615 2025-04-17 05:21:32.475000: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 8388608 2025-04-17 05:21:32.475010: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c00000 of size 4096 next 593 2025-04-17 05:21:32.475020: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c01000 of size 4096 next 594 2025-04-17 05:21:32.475030: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c02000 of size 4096 next 595 2025-04-17 05:21:32.475041: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c03000 of size 2048 next 598 2025-04-17 05:21:32.475051: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c03800 of size 2048 next 599 2025-04-17 05:21:32.475061: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c04000 of size 2048 next 600 2025-04-17 05:21:32.475071: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c04800 of size 2048 next 601 2025-04-17 05:21:32.475081: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c05000 of size 2048 next 602 2025-04-17 05:21:32.475092: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c05800 of size 256 next 605 2025-04-17 05:21:32.475104: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c05900 of size 256 next 606 2025-04-17 05:21:32.475116: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c05a00 of size 2048 next 604 2025-04-17 05:21:32.475127: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c06200 of size 2048 next 609 2025-04-17 05:21:32.475138: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c06a00 of size 2048 next 610 2025-04-17 05:21:32.475150: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c07200 of size 2048 next 611 2025-04-17 05:21:32.475162: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c07a00 of size 2048 next 612 2025-04-17 05:21:32.475174: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c08200 of size 256 next 614 2025-04-17 05:21:32.475185: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c08300 of size 256 next 615 2025-04-17 05:21:32.475196: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c08400 of size 8192 next 613 2025-04-17 05:21:32.475208: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c0a400 of size 8192 next 616 2025-04-17 05:21:32.475220: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c0c400 of size 8192 next 618 2025-04-17 05:21:32.475230: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c0e400 of size 8192 next 619 2025-04-17 05:21:32.475242: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c10400 of size 8192 next 620 2025-04-17 05:21:32.475254: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c12400 of size 256 next 621 2025-04-17 05:21:32.475265: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c12500 of size 256 next 622 2025-04-17 05:21:32.475277: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c12600 of size 8192 next 623 2025-04-17 05:21:32.475297: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c14600 of size 8192 next 625 2025-04-17 05:21:32.475309: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c16600 of size 8192 next 626 2025-04-17 05:21:32.475320: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c18600 of size 8192 next 627 2025-04-17 05:21:32.475331: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c1a600 of size 8192 next 628 2025-04-17 05:21:32.475343: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c1c600 of size 2048 next 629 2025-04-17 05:21:32.475355: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c1ce00 of size 2048 next 631 2025-04-17 05:21:32.475366: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c1d600 of size 2048 next 632 2025-04-17 05:21:32.475378: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c1de00 of size 2048 next 633 2025-04-17 05:21:32.475388: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c1e600 of size 2048 next 634 2025-04-17 05:21:32.475398: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7e98c1ee00 of size 463360 next 160 2025-04-17 05:21:32.475408: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98c90000 of size 589824 next 158 2025-04-17 05:21:32.475418: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98d20000 of size 524288 next 171 2025-04-17 05:21:32.475428: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7e98da0000 of size 1048576 next 222 2025-04-17 05:21:32.475438: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98ea0000 of size 1048576 next 190 2025-04-17 05:21:32.475449: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e98fa0000 of size 1048576 next 189 2025-04-17 05:21:32.475459: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e990a0000 of size 1048576 next 203 2025-04-17 05:21:32.475470: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e991a0000 of size 1048576 next 251 2025-04-17 05:21:32.475481: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7e992a0000 of size 1441792 next 18446744073709551615 2025-04-17 05:21:32.475491: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 1048576 2025-04-17 05:21:32.475501: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00000 of size 1280 next 1 2025-04-17 05:21:32.475514: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00500 of size 256 next 5 2025-04-17 05:21:32.475526: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00600 of size 256 next 8 2025-04-17 05:21:32.475537: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00700 of size 256 next 9 2025-04-17 05:21:32.475549: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00800 of size 256 next 10 2025-04-17 05:21:32.475560: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00900 of size 256 next 11 2025-04-17 05:21:32.475572: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00a00 of size 256 next 12 2025-04-17 05:21:32.475583: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00b00 of size 256 next 13 2025-04-17 05:21:32.475594: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00c00 of size 256 next 17 2025-04-17 05:21:32.475606: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00d00 of size 256 next 19 2025-04-17 05:21:32.475618: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00e00 of size 256 next 20 2025-04-17 05:21:32.475629: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce00f00 of size 256 next 21 2025-04-17 05:21:32.475640: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01000 of size 256 next 22 2025-04-17 05:21:32.475657: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01100 of size 256 next 24 2025-04-17 05:21:32.475668: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01200 of size 256 next 25 2025-04-17 05:21:32.475679: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01300 of size 256 next 23 2025-04-17 05:21:32.475689: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01400 of size 256 next 28 2025-04-17 05:21:32.475699: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01500 of size 256 next 29 2025-04-17 05:21:32.475709: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01600 of size 256 next 30 2025-04-17 05:21:32.475720: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01700 of size 256 next 31 2025-04-17 05:21:32.475730: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01800 of size 256 next 33 2025-04-17 05:21:32.475740: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01900 of size 256 next 34 2025-04-17 05:21:32.475751: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01a00 of size 1024 next 32 2025-04-17 05:21:32.475761: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce01e00 of size 1024 next 37 2025-04-17 05:21:32.475771: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce02200 of size 1024 next 38 2025-04-17 05:21:32.475781: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce02600 of size 1024 next 39 2025-04-17 05:21:32.475791: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce02a00 of size 1024 next 40 2025-04-17 05:21:32.475803: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce02e00 of size 1024 next 41 2025-04-17 05:21:32.475814: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce03200 of size 1024 next 43 2025-04-17 05:21:32.475825: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce03600 of size 1024 next 44 2025-04-17 05:21:32.475835: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce03a00 of size 1024 next 45 2025-04-17 05:21:32.475846: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce03e00 of size 1024 next 46 2025-04-17 05:21:32.475856: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04200 of size 256 next 48 2025-04-17 05:21:32.475868: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04300 of size 256 next 49 2025-04-17 05:21:32.475879: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04400 of size 256 next 50 2025-04-17 05:21:32.475891: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04500 of size 256 next 51 2025-04-17 05:21:32.475901: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04600 of size 256 next 52 2025-04-17 05:21:32.475913: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04700 of size 256 next 53 2025-04-17 05:21:32.475924: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04800 of size 256 next 56 2025-04-17 05:21:32.475936: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04900 of size 256 next 57 2025-04-17 05:21:32.475947: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04a00 of size 256 next 58 2025-04-17 05:21:32.475959: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04b00 of size 256 next 14 2025-04-17 05:21:32.475969: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04c00 of size 256 next 15 2025-04-17 05:21:32.475981: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04d00 of size 256 next 16 2025-04-17 05:21:32.475992: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce04e00 of size 1024 next 60 2025-04-17 05:21:32.476003: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce05200 of size 1024 next 61 2025-04-17 05:21:32.476020: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce05600 of size 1024 next 62 2025-04-17 05:21:32.476031: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce05a00 of size 1024 next 63 2025-04-17 05:21:32.476042: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce05e00 of size 1024 next 64 2025-04-17 05:21:32.476054: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce06200 of size 256 next 66 2025-04-17 05:21:32.476064: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce06300 of size 256 next 67 2025-04-17 05:21:32.476076: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce06400 of size 256 next 68 2025-04-17 05:21:32.476088: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce06500 of size 256 next 69 2025-04-17 05:21:32.476099: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce06600 of size 256 next 70 2025-04-17 05:21:32.476110: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce06700 of size 256 next 73 2025-04-17 05:21:32.476122: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce06800 of size 256 next 74 2025-04-17 05:21:32.476133: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce06900 of size 256 next 75 2025-04-17 05:21:32.476144: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce06a00 of size 256 next 76 2025-04-17 05:21:32.476155: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce06b00 of size 256 next 77 2025-04-17 05:21:32.476167: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce06c00 of size 1024 next 79 2025-04-17 05:21:32.476178: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce07000 of size 1024 next 80 2025-04-17 05:21:32.476189: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce07400 of size 1024 next 81 2025-04-17 05:21:32.476201: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce07800 of size 1024 next 82 2025-04-17 05:21:32.476212: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce07c00 of size 1024 next 83 2025-04-17 05:21:32.476222: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce08000 of size 256 next 85 2025-04-17 05:21:32.476234: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce08100 of size 256 next 86 2025-04-17 05:21:32.476245: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce08200 of size 512 next 84 2025-04-17 05:21:32.476257: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce08400 of size 512 next 88 2025-04-17 05:21:32.476268: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce08600 of size 512 next 89 2025-04-17 05:21:32.476279: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce08800 of size 512 next 90 2025-04-17 05:21:32.476290: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce08a00 of size 512 next 91 2025-04-17 05:21:32.476301: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce08c00 of size 256 next 93 2025-04-17 05:21:32.476312: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce08d00 of size 256 next 94 2025-04-17 05:21:32.476324: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce08e00 of size 512 next 92 2025-04-17 05:21:32.476335: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce09000 of size 512 next 97 2025-04-17 05:21:32.476346: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce09200 of size 512 next 98 2025-04-17 05:21:32.476358: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce09400 of size 512 next 99 2025-04-17 05:21:32.476369: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce09600 of size 512 next 2 2025-04-17 05:21:32.476381: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce09800 of size 256 next 3 2025-04-17 05:21:32.476401: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce09900 of size 256 next 4 2025-04-17 05:21:32.476413: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce09a00 of size 16384 next 18 2025-04-17 05:21:32.476424: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce0da00 of size 256 next 100 2025-04-17 05:21:32.476436: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce0db00 of size 256 next 101 2025-04-17 05:21:32.476447: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce0dc00 of size 2048 next 104 2025-04-17 05:21:32.476458: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce0e400 of size 2048 next 105 2025-04-17 05:21:32.476468: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce0ec00 of size 2048 next 106 2025-04-17 05:21:32.476480: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce0f400 of size 2048 next 107 2025-04-17 05:21:32.476491: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce0fc00 of size 2048 next 108 2025-04-17 05:21:32.476502: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce10400 of size 256 next 109 2025-04-17 05:21:32.476514: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce10500 of size 256 next 110 2025-04-17 05:21:32.476525: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce10600 of size 2048 next 113 2025-04-17 05:21:32.476536: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce10e00 of size 2048 next 114 2025-04-17 05:21:32.476547: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce11600 of size 2048 next 115 2025-04-17 05:21:32.476559: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce11e00 of size 2048 next 116 2025-04-17 05:21:32.476570: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce12600 of size 2048 next 6 2025-04-17 05:21:32.476582: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce12e00 of size 37632 next 7 2025-04-17 05:21:32.476593: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1c100 of size 512 next 118 2025-04-17 05:21:32.476604: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1c300 of size 512 next 119 2025-04-17 05:21:32.476614: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1c500 of size 512 next 120 2025-04-17 05:21:32.476624: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1c700 of size 512 next 121 2025-04-17 05:21:32.476634: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1c900 of size 512 next 122 2025-04-17 05:21:32.476644: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1cb00 of size 512 next 125 2025-04-17 05:21:32.476654: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1cd00 of size 512 next 126 2025-04-17 05:21:32.476664: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1cf00 of size 512 next 127 2025-04-17 05:21:32.476674: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1d100 of size 512 next 128 2025-04-17 05:21:32.476684: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1d300 of size 512 next 129 2025-04-17 05:21:32.476694: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1d500 of size 2048 next 130 2025-04-17 05:21:32.476704: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1dd00 of size 2048 next 131 2025-04-17 05:21:32.476714: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1e500 of size 2048 next 132 2025-04-17 05:21:32.476724: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1ed00 of size 2048 next 133 2025-04-17 05:21:32.476734: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1f500 of size 2048 next 134 2025-04-17 05:21:32.476752: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1fd00 of size 512 next 136 2025-04-17 05:21:32.476763: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce1ff00 of size 512 next 137 2025-04-17 05:21:32.476773: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce20100 of size 512 next 138 2025-04-17 05:21:32.476783: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce20300 of size 512 next 139 2025-04-17 05:21:32.476793: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce20500 of size 512 next 140 2025-04-17 05:21:32.476803: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce20700 of size 512 next 141 2025-04-17 05:21:32.476813: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce20900 of size 512 next 143 2025-04-17 05:21:32.476823: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce20b00 of size 512 next 144 2025-04-17 05:21:32.476833: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce20d00 of size 512 next 145 2025-04-17 05:21:32.476843: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce20f00 of size 512 next 146 2025-04-17 05:21:32.476853: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce21100 of size 2048 next 147 2025-04-17 05:21:32.476863: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce21900 of size 2048 next 148 2025-04-17 05:21:32.476876: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce22100 of size 2048 next 149 2025-04-17 05:21:32.476886: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce22900 of size 2048 next 150 2025-04-17 05:21:32.476897: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce23100 of size 2048 next 151 2025-04-17 05:21:32.476906: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce23900 of size 512 next 153 2025-04-17 05:21:32.476916: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce23b00 of size 512 next 154 2025-04-17 05:21:32.476931: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce23d00 of size 512 next 155 2025-04-17 05:21:32.476943: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce23f00 of size 512 next 156 2025-04-17 05:21:32.476953: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce24100 of size 512 next 157 2025-04-17 05:21:32.476963: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce24300 of size 512 next 161 2025-04-17 05:21:32.476973: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce24500 of size 512 next 162 2025-04-17 05:21:32.476983: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce24700 of size 512 next 163 2025-04-17 05:21:32.476993: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce24900 of size 512 next 164 2025-04-17 05:21:32.477004: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce24b00 of size 512 next 165 2025-04-17 05:21:32.477014: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce24d00 of size 2048 next 166 2025-04-17 05:21:32.477024: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce25500 of size 2048 next 167 2025-04-17 05:21:32.477034: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce25d00 of size 2048 next 168 2025-04-17 05:21:32.477044: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce26500 of size 2048 next 169 2025-04-17 05:21:32.477054: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce26d00 of size 2048 next 170 2025-04-17 05:21:32.477064: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce27500 of size 1024 next 172 2025-04-17 05:21:32.477074: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce27900 of size 1024 next 173 2025-04-17 05:21:32.477092: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce27d00 of size 1024 next 174 2025-04-17 05:21:32.477103: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce28100 of size 1024 next 175 2025-04-17 05:21:32.477113: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce28500 of size 1024 next 176 2025-04-17 05:21:32.477123: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce28900 of size 256 next 178 2025-04-17 05:21:32.477133: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce28a00 of size 256 next 179 2025-04-17 05:21:32.477143: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce28b00 of size 1024 next 177 2025-04-17 05:21:32.477153: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce28f00 of size 1024 next 182 2025-04-17 05:21:32.477163: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce29300 of size 1024 next 183 2025-04-17 05:21:32.477173: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce29700 of size 1024 next 184 2025-04-17 05:21:32.477183: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce29b00 of size 1024 next 185 2025-04-17 05:21:32.477193: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce29f00 of size 256 next 187 2025-04-17 05:21:32.477203: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce2a000 of size 256 next 188 2025-04-17 05:21:32.477213: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce2a100 of size 4096 next 186 2025-04-17 05:21:32.477223: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce2b100 of size 4096 next 42 2025-04-17 05:21:32.477233: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce2c100 of size 65536 next 36 2025-04-17 05:21:32.477244: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce3c100 of size 65536 next 35 2025-04-17 05:21:32.477254: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce4c100 of size 4096 next 235 2025-04-17 05:21:32.477264: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce4d100 of size 4096 next 236 2025-04-17 05:21:32.477273: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce4e100 of size 4096 next 237 2025-04-17 05:21:32.477284: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce4f100 of size 4096 next 238 2025-04-17 05:21:32.477294: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce50100 of size 1024 next 239 2025-04-17 05:21:32.477304: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce50500 of size 1024 next 240 2025-04-17 05:21:32.477314: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce50900 of size 1024 next 241 2025-04-17 05:21:32.477324: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce50d00 of size 1024 next 242 2025-04-17 05:21:32.477334: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce51100 of size 1024 next 243 2025-04-17 05:21:32.477344: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce51500 of size 1024 next 246 2025-04-17 05:21:32.477354: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce51900 of size 1024 next 247 2025-04-17 05:21:32.477364: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce51d00 of size 1024 next 248 2025-04-17 05:21:32.477373: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce52100 of size 1024 next 249 2025-04-17 05:21:32.477384: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce52500 of size 1024 next 250 2025-04-17 05:21:32.477394: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce52900 of size 4096 next 252 2025-04-17 05:21:32.477404: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce53900 of size 4096 next 253 2025-04-17 05:21:32.477414: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce54900 of size 4096 next 254 2025-04-17 05:21:32.477431: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce55900 of size 4096 next 255 2025-04-17 05:21:32.477442: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce56900 of size 4096 next 256 2025-04-17 05:21:32.477452: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce57900 of size 1024 next 257 2025-04-17 05:21:32.477462: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce57d00 of size 1024 next 258 2025-04-17 05:21:32.477472: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce58100 of size 1024 next 259 2025-04-17 05:21:32.477482: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce58500 of size 1024 next 260 2025-04-17 05:21:32.477492: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce58900 of size 1024 next 261 2025-04-17 05:21:32.477502: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce58d00 of size 1024 next 264 2025-04-17 05:21:32.477512: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce59100 of size 1024 next 265 2025-04-17 05:21:32.477522: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce59500 of size 1024 next 266 2025-04-17 05:21:32.477532: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce59900 of size 1024 next 267 2025-04-17 05:21:32.477542: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce59d00 of size 1024 next 268 2025-04-17 05:21:32.477552: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce5a100 of size 4096 next 270 2025-04-17 05:21:32.477562: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce5b100 of size 4096 next 271 2025-04-17 05:21:32.477573: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce5c100 of size 4096 next 272 2025-04-17 05:21:32.477583: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce5d100 of size 4096 next 273 2025-04-17 05:21:32.477593: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce5e100 of size 4096 next 274 2025-04-17 05:21:32.477603: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce5f100 of size 1024 next 275 2025-04-17 05:21:32.477614: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce5f500 of size 1024 next 276 2025-04-17 05:21:32.477624: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce5f900 of size 1024 next 277 2025-04-17 05:21:32.477635: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce5fd00 of size 1024 next 278 2025-04-17 05:21:32.477645: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce60100 of size 1024 next 279 2025-04-17 05:21:32.477657: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce60500 of size 1024 next 282 2025-04-17 05:21:32.477668: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce60900 of size 1024 next 283 2025-04-17 05:21:32.477680: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce60d00 of size 1024 next 284 2025-04-17 05:21:32.477690: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce61100 of size 1024 next 285 2025-04-17 05:21:32.477701: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce61500 of size 1024 next 286 2025-04-17 05:21:32.477711: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce61900 of size 4096 next 288 2025-04-17 05:21:32.477722: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce62900 of size 6144 next 27 2025-04-17 05:21:32.477732: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce64100 of size 147456 next 26 2025-04-17 05:21:32.477743: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce88100 of size 65536 next 47 2025-04-17 05:21:32.477754: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcce98100 of size 65536 next 59 2025-04-17 05:21:32.477772: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fccea8100 of size 65536 next 65 2025-04-17 05:21:32.477784: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7fcceb8100 of size 294656 next 18446744073709551615 2025-04-17 05:21:32.477794: I tensorflow/core/common_runtime/bfc_allocator.cc:995] Summary of in-use Chunks by size: 2025-04-17 05:21:32.477809: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 65 Chunks of size 256 totalling 16.2KiB 2025-04-17 05:21:32.477821: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 40 Chunks of size 512 totalling 20.0KiB 2025-04-17 05:21:32.477833: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 250 Chunks of size 1024 totalling 250.0KiB 2025-04-17 05:21:32.477844: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1280 totalling 1.2KiB 2025-04-17 05:21:32.477855: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 40 Chunks of size 2048 totalling 80.0KiB 2025-04-17 05:21:32.477866: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 117 Chunks of size 4096 totalling 468.0KiB 2025-04-17 05:21:32.477877: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 6144 totalling 12.0KiB 2025-04-17 05:21:32.477888: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 7680 totalling 7.5KiB 2025-04-17 05:21:32.477899: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 10 Chunks of size 8192 totalling 80.0KiB 2025-04-17 05:21:32.477910: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 16384 totalling 16.0KiB 2025-04-17 05:21:32.477921: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 37632 totalling 36.8KiB 2025-04-17 05:21:32.477933: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 6 Chunks of size 65536 totalling 384.0KiB 2025-04-17 05:21:32.477944: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 131072 totalling 128.0KiB 2025-04-17 05:21:32.477956: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 3 Chunks of size 147456 totalling 432.0KiB 2025-04-17 05:21:32.477968: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 4 Chunks of size 262144 totalling 1.00MiB 2025-04-17 05:21:32.477981: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 294656 totalling 287.8KiB 2025-04-17 05:21:32.477994: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 327680 totalling 640.0KiB 2025-04-17 05:21:32.478006: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 524288 totalling 1.00MiB 2025-04-17 05:21:32.478018: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 3 Chunks of size 589824 totalling 1.69MiB 2025-04-17 05:21:32.478029: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 786432 totalling 768.0KiB 2025-04-17 05:21:32.478041: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 25 Chunks of size 1048576 totalling 25.00MiB 2025-04-17 05:21:32.478052: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 18 Chunks of size 1310720 totalling 22.50MiB 2025-04-17 05:21:32.478063: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1441792 totalling 1.38MiB 2025-04-17 05:21:32.478074: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1835008 totalling 1.75MiB 2025-04-17 05:21:32.478084: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 2097152 totalling 4.00MiB 2025-04-17 05:21:32.478096: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 23 Chunks of size 2359296 totalling 51.75MiB 2025-04-17 05:21:32.478108: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 4194304 totalling 4.00MiB 2025-04-17 05:21:32.478119: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 7208960 totalling 6.88MiB 2025-04-17 05:21:32.478130: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 9437184 totalling 9.00MiB 2025-04-17 05:21:32.478149: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 10485760 totalling 10.00MiB 2025-04-17 05:21:32.478162: I tensorflow/core/common_runtime/bfc_allocator.cc:1002] Sum Total of in-use chunks: 143.48MiB 2025-04-17 05:21:32.478172: I tensorflow/core/common_runtime/bfc_allocator.cc:1004] total_region_allocated_bytes_: 177078272 memory_limit_: 177078272 available bytes: 0 curr_region_allocation_bytes_: 268435456 2025-04-17 05:21:32.478187: I tensorflow/core/common_runtime/bfc_allocator.cc:1010] Stats: Limit: 177078272 InUse: 150449664 MaxInUse: 162981376 NumAllocs: 2110 MaxAllocSize: 10485760 2025-04-17 05:21:32.478210: W tensorflow/core/common_runtime/bfc_allocator.cc:439] ____***************_*****************************************_****************************_********* 2025-04-17 05:21:32.478248: W tensorflow/core/framework/op_kernel.cc:1753] OP_REQUIRES failed at random_op.cc:77 : Resource exhausted: OOM when allocating tensor with shape[3,3,512,512] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc 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 Exception in mask_detect : OOM when allocating tensor with shape[3,3,512,512] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:RandomUniform] we want to redo the detection Using TensorFlow backend. max_time_sub_proc : 3600 erreur pendant la detection Useless call to update_current_state in case -12 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 ! ERROR : mask output needs to be a dictionnary now ! No output to save, continue without doing anything ! save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : -12 ERROR : 'int' object is not subscriptable reconnect to base ! warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data #&_# TEST FAILED #&_# : tests/mask_test #&_# Error : invalid literal for int() with base 10: "'int' object is not subscriptable" #&_# 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 : 0.27007079124450684 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 Thu Apr 17 05:21:33 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 Beginning of datou step sam ! Inside sam : nb paths : 1 (640, 960, 3) time for calcul the mask position with numpy : 0.002479076385498047 nb_pixel_total : 7664 time to create 1 rle with old method : 0.02066636085510254 time for calcul the mask position with numpy : 0.0015256404876708984 nb_pixel_total : 5612 time to create 1 rle with old method : 0.012991905212402344 time for calcul the mask position with numpy : 0.0015969276428222656 nb_pixel_total : 13943 time to create 1 rle with old method : 0.032919883728027344 time for calcul the mask position with numpy : 0.002852916717529297 nb_pixel_total : 84027 time to create 1 rle with old method : 0.1959235668182373 time for calcul the mask position with numpy : 0.0020406246185302734 nb_pixel_total : 16183 time to create 1 rle with old method : 0.03870725631713867 time for calcul the mask position with numpy : 0.001645803451538086 nb_pixel_total : 3764 time to create 1 rle with old method : 0.008940696716308594 time for calcul the mask position with numpy : 0.0017287731170654297 nb_pixel_total : 5519 time to create 1 rle with old method : 0.013314485549926758 time for calcul the mask position with numpy : 0.0016412734985351562 nb_pixel_total : 16448 time to create 1 rle with old method : 0.0383303165435791 time for calcul the mask position with numpy : 0.0015935897827148438 nb_pixel_total : 2953 time to create 1 rle with old method : 0.007036685943603516 time for calcul the mask position with numpy : 0.001615285873413086 nb_pixel_total : 10813 time to create 1 rle with old method : 0.0267179012298584 time for calcul the mask position with numpy : 0.0018291473388671875 nb_pixel_total : 29431 time to create 1 rle with old method : 0.06839513778686523 time for calcul the mask position with numpy : 0.0015277862548828125 nb_pixel_total : 2451 time to create 1 rle with old method : 0.0060536861419677734 time for calcul the mask position with numpy : 0.0015072822570800781 nb_pixel_total : 1228 time to create 1 rle with old method : 0.0030410289764404297 time for calcul the mask position with numpy : 0.00157928466796875 nb_pixel_total : 4265 time to create 1 rle with old method : 0.010488748550415039 time for calcul the mask position with numpy : 0.0015976428985595703 nb_pixel_total : 6639 time to create 1 rle with old method : 0.01609516143798828 time for calcul the mask position with numpy : 0.0015506744384765625 nb_pixel_total : 3951 time to create 1 rle with old method : 0.009569644927978516 time for calcul the mask position with numpy : 0.0016672611236572266 nb_pixel_total : 13142 time to create 1 rle with old method : 0.0335841178894043 time for calcul the mask position with numpy : 0.0017349720001220703 nb_pixel_total : 1513 time to create 1 rle with old method : 0.005135297775268555 time for calcul the mask position with numpy : 0.0017108917236328125 nb_pixel_total : 2078 time to create 1 rle with old method : 0.0069463253021240234 time for calcul the mask position with numpy : 0.001811981201171875 nb_pixel_total : 10608 time to create 1 rle with old method : 0.03706717491149902 time for calcul the mask position with numpy : 0.0018131732940673828 nb_pixel_total : 3508 time to create 1 rle with old method : 0.01175546646118164 time for calcul the mask position with numpy : 0.001621246337890625 nb_pixel_total : 1319 time to create 1 rle with old method : 0.003409862518310547 time for calcul the mask position with numpy : 0.001605987548828125 nb_pixel_total : 881 time to create 1 rle with old method : 0.002274751663208008 time for calcul the mask position with numpy : 0.00162506103515625 nb_pixel_total : 4299 time to create 1 rle with old method : 0.010690927505493164 time for calcul the mask position with numpy : 0.0015926361083984375 nb_pixel_total : 854 time to create 1 rle with old method : 0.002180337905883789 time for calcul the mask position with numpy : 0.0016825199127197266 nb_pixel_total : 38971 time to create 1 rle with old method : 0.09093856811523438 time for calcul the mask position with numpy : 0.0016870498657226562 nb_pixel_total : 8610 time to create 1 rle with old method : 0.019730567932128906 time for calcul the mask position with numpy : 0.0015552043914794922 nb_pixel_total : 9898 time to create 1 rle with old method : 0.02305889129638672 time for calcul the mask position with numpy : 0.0015811920166015625 nb_pixel_total : 1392 time to create 1 rle with old method : 0.0035004615783691406 time for calcul the mask position with numpy : 0.0016415119171142578 nb_pixel_total : 11947 time to create 1 rle with old method : 0.030894041061401367 time for calcul the mask position with numpy : 0.0015785694122314453 nb_pixel_total : 2448 time to create 1 rle with old method : 0.005774497985839844 time for calcul the mask position with numpy : 0.0015647411346435547 nb_pixel_total : 2728 time to create 1 rle with old method : 0.006461620330810547 time for calcul the mask position with numpy : 0.0015799999237060547 nb_pixel_total : 13042 time to create 1 rle with old method : 0.031085729598999023 time for calcul the mask position with numpy : 0.0015692710876464844 nb_pixel_total : 2835 time to create 1 rle with old method : 0.00666046142578125 time for calcul the mask position with numpy : 0.0015172958374023438 nb_pixel_total : 1636 time to create 1 rle with old method : 0.004051923751831055 time for calcul the mask position with numpy : 0.0015697479248046875 nb_pixel_total : 5396 time to create 1 rle with old method : 0.01277303695678711 time for calcul the mask position with numpy : 0.0016307830810546875 nb_pixel_total : 14862 time to create 1 rle with old method : 0.03442192077636719 time for calcul the mask position with numpy : 0.0015444755554199219 nb_pixel_total : 3330 time to create 1 rle with old method : 0.0077342987060546875 time for calcul the mask position with numpy : 0.0015137195587158203 nb_pixel_total : 1025 time to create 1 rle with old method : 0.002439260482788086 time for calcul the mask position with numpy : 0.0014996528625488281 nb_pixel_total : 1648 time to create 1 rle with old method : 0.003904581069946289 time for calcul the mask position with numpy : 0.0014834403991699219 nb_pixel_total : 4126 time to create 1 rle with old method : 0.009621381759643555 time for calcul the mask position with numpy : 0.0014841556549072266 nb_pixel_total : 344 time to create 1 rle with old method : 0.0008375644683837891 time for calcul the mask position with numpy : 0.0015141963958740234 nb_pixel_total : 1255 time to create 1 rle with old method : 0.0029604434967041016 time for calcul the mask position with numpy : 0.0014843940734863281 nb_pixel_total : 3856 time to create 1 rle with old method : 0.009220361709594727 time for calcul the mask position with numpy : 0.0015120506286621094 nb_pixel_total : 4145 time to create 1 rle with old method : 0.00980377197265625 time for calcul the mask position with numpy : 0.0014889240264892578 nb_pixel_total : 874 time to create 1 rle with old method : 0.002216815948486328 time for calcul the mask position with numpy : 0.0014834403991699219 nb_pixel_total : 594 time to create 1 rle with old method : 0.0014448165893554688 time for calcul the mask position with numpy : 0.0014603137969970703 nb_pixel_total : 2340 time to create 1 rle with old method : 0.060828208923339844 time for calcul the mask position with numpy : 0.002009868621826172 nb_pixel_total : 13154 time to create 1 rle with old method : 0.030444622039794922 time for calcul the mask position with numpy : 0.0016169548034667969 nb_pixel_total : 2380 time to create 1 rle with old method : 0.005755901336669922 time for calcul the mask position with numpy : 0.0015201568603515625 nb_pixel_total : 573 time to create 1 rle with old method : 0.0014216899871826172 time for calcul the mask position with numpy : 0.0014927387237548828 nb_pixel_total : 2408 time to create 1 rle with old method : 0.0058786869049072266 time for calcul the mask position with numpy : 0.0015690326690673828 nb_pixel_total : 1059 time to create 1 rle with old method : 0.0026857852935791016 time for calcul the mask position with numpy : 0.0015065670013427734 nb_pixel_total : 331 time to create 1 rle with old method : 0.0008618831634521484 time for calcul the mask position with numpy : 0.0014960765838623047 nb_pixel_total : 585 time to create 1 rle with old method : 0.0014309883117675781 time for calcul the mask position with numpy : 0.0014965534210205078 nb_pixel_total : 692 time to create 1 rle with old method : 0.0017316341400146484 time for calcul the mask position with numpy : 0.0014941692352294922 nb_pixel_total : 267 time to create 1 rle with old method : 0.0007135868072509766 time for calcul the mask position with numpy : 0.0014946460723876953 nb_pixel_total : 1704 time to create 1 rle with old method : 0.004679679870605469 time for calcul the mask position with numpy : 0.0015785694122314453 nb_pixel_total : 2769 time to create 1 rle with old method : 0.006587028503417969 time for calcul the mask position with numpy : 0.0015385150909423828 nb_pixel_total : 1207 time to create 1 rle with old method : 0.0029544830322265625 time for calcul the mask position with numpy : 0.0015075206756591797 nb_pixel_total : 3089 time to create 1 rle with old method : 0.009303569793701172 time for calcul the mask position with numpy : 0.0017082691192626953 nb_pixel_total : 8605 time to create 1 rle with old method : 0.028346776962280273 time for calcul the mask position with numpy : 0.0016665458679199219 nb_pixel_total : 1073 time to create 1 rle with old method : 0.0035829544067382812 time for calcul the mask position with numpy : 0.001674652099609375 nb_pixel_total : 7531 time to create 1 rle with old method : 0.024600982666015625 time for calcul the mask position with numpy : 0.002227306365966797 nb_pixel_total : 27580 time to create 1 rle with old method : 0.08780670166015625 time for calcul the mask position with numpy : 0.0018186569213867188 nb_pixel_total : 296 time to create 1 rle with old method : 0.00116729736328125 time for calcul the mask position with numpy : 0.0019078254699707031 nb_pixel_total : 16680 time to create 1 rle with old method : 0.05490732192993164 time for calcul the mask position with numpy : 0.001928091049194336 nb_pixel_total : 1752 time to create 1 rle with old method : 0.005717754364013672 time for calcul the mask position with numpy : 0.0019845962524414062 nb_pixel_total : 8432 time to create 1 rle with old method : 0.02558112144470215 time for calcul the mask position with numpy : 0.0015482902526855469 nb_pixel_total : 714 time to create 1 rle with old method : 0.0018520355224609375 time for calcul the mask position with numpy : 0.0015482902526855469 nb_pixel_total : 1539 time to create 1 rle with old method : 0.004032135009765625 time for calcul the mask position with numpy : 0.001577615737915039 nb_pixel_total : 1627 time to create 1 rle with old method : 0.003935337066650391 time for calcul the mask position with numpy : 0.0015418529510498047 nb_pixel_total : 3169 time to create 1 rle with old method : 0.007611989974975586 time for calcul the mask position with numpy : 0.0016856193542480469 nb_pixel_total : 18499 time to create 1 rle with old method : 0.04313325881958008 time for calcul the mask position with numpy : 0.0015690326690673828 nb_pixel_total : 9513 time to create 1 rle with old method : 0.02183842658996582 time for calcul the mask position with numpy : 0.0015425682067871094 nb_pixel_total : 248 time to create 1 rle with old method : 0.0006544589996337891 time for calcul the mask position with numpy : 0.0014450550079345703 nb_pixel_total : 977 time to create 1 rle with old method : 0.002342700958251953 time for calcul the mask position with numpy : 0.0015263557434082031 nb_pixel_total : 2301 time to create 1 rle with old method : 0.005425930023193359 time for calcul the mask position with numpy : 0.0015079975128173828 nb_pixel_total : 9072 time to create 1 rle with old method : 0.021121740341186523 time for calcul the mask position with numpy : 0.0015270709991455078 nb_pixel_total : 2252 time to create 1 rle with old method : 0.005458831787109375 time for calcul the mask position with numpy : 0.0014548301696777344 nb_pixel_total : 616 time to create 1 rle with old method : 0.0015087127685546875 time for calcul the mask position with numpy : 0.0014979839324951172 nb_pixel_total : 973 time to create 1 rle with old method : 0.002369403839111328 time for calcul the mask position with numpy : 0.0014545917510986328 nb_pixel_total : 221 time to create 1 rle with old method : 0.0005929470062255859 time for calcul the mask position with numpy : 0.0014312267303466797 nb_pixel_total : 909 time to create 1 rle with old method : 0.002282381057739258 time for calcul the mask position with numpy : 0.0014383792877197266 nb_pixel_total : 735 time to create 1 rle with old method : 0.001959085464477539 time for calcul the mask position with numpy : 0.0014395713806152344 nb_pixel_total : 917 time to create 1 rle with old method : 0.002463102340698242 time for calcul the mask position with numpy : 0.0014390945434570312 nb_pixel_total : 596 time to create 1 rle with old method : 0.0015652179718017578 time for calcul the mask position with numpy : 0.0014438629150390625 nb_pixel_total : 1512 time to create 1 rle with old method : 0.003610849380493164 time for calcul the mask position with numpy : 0.0014524459838867188 nb_pixel_total : 1634 time to create 1 rle with old method : 0.003934621810913086 time for calcul the mask position with numpy : 0.0014612674713134766 nb_pixel_total : 262 time to create 1 rle with old method : 0.0007038116455078125 time for calcul the mask position with numpy : 0.001462697982788086 nb_pixel_total : 5013 time to create 1 rle with old method : 0.011913776397705078 time for calcul the mask position with numpy : 0.0015017986297607422 nb_pixel_total : 1123 time to create 1 rle with old method : 0.0027191638946533203 time for calcul the mask position with numpy : 0.0014476776123046875 nb_pixel_total : 1659 time to create 1 rle with old method : 0.004127979278564453 time for calcul the mask position with numpy : 0.0014472007751464844 nb_pixel_total : 1081 time to create 1 rle with old method : 0.0026395320892333984 time for calcul the mask position with numpy : 0.00145721435546875 nb_pixel_total : 2689 time to create 1 rle with old method : 0.006412029266357422 time for calcul the mask position with numpy : 0.0014529228210449219 nb_pixel_total : 889 time to create 1 rle with old method : 0.0022232532501220703 time for calcul the mask position with numpy : 0.0014505386352539062 nb_pixel_total : 947 time to create 1 rle with old method : 0.0023889541625976562 time for calcul the mask position with numpy : 0.001458883285522461 nb_pixel_total : 1202 time to create 1 rle with old method : 0.0029516220092773438 batch 1 Loaded 98 chid ids of type : 4677 Number RLEs to save : 9010 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 : 0.014068126678466797 save_final save missing photos in datou_result : time spend for datou_step_exec : 12.058519840240479 time spend to save output : 0.01458883285522461 total time spend for step 1 : 12.073108673095703 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : {'1189321094': [[, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ], 'temp/1744860092_1837371_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png']} nb_objects detect : 98 ############################### 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 : 0.10154962539672852 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 Thu Apr 17 05:21:45 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 : [] WARNING: Logging before InitGoogleLogging() is written to STDERR F0417 05:21:48.579591 1837371 syncedmem.cpp:71] Check failed: error == cudaSuccess (2 vs. 0) out of memory *** Check failure stack trace: *** Aborted (core dumped) /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/PIL/BmpImagePlugin.py 218 181 17% 52, 56, 76-264, 276-284, 291-355, 366, 384, 388-449 /home/admin/.local/lib/python3.8/site-packages/PIL/ExifTags.py 340 0 100% /home/admin/.local/lib/python3.8/site-packages/PIL/GifImagePlugin.py 585 527 10% 55, 71-74, 77-80, 84-108, 112-120, 124-139, 142-155, 158-410, 413-430, 433-456, 459, 480-491, 506-543, 547-564, 568-574, 578-649, 653, 658-670, 674-680, 684-746, 756-793, 812-844, 849-854, 865-872, 882, 886-905, 914-967, 971-983, 1002-1015, 1036-1048 /home/admin/.local/lib/python3.8/site-packages/PIL/GimpGradientFile.py 68 53 22% 32-43, 47, 51, 55, 59, 70-98, 105-137 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/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/utils.py 75 45 40% 29-30, 34-37, 41, 47-50, 59-61, 66-67, 70-74, 77, 80-84, 87, 97-104, 108-119, 126, 129 /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 /home/admin/.local/lib/python3.8/site-packages/dateutil/_common.py 25 15 40% 14-17, 20-25, 28, 34, 37-41 /home/admin/.local/lib/python3.8/site-packages/dateutil/_version.py 2 0 100% /home/admin/.local/lib/python3.8/site-packages/dateutil/parser/__init__.py 33 4 88% 31-32, 47-48 /home/admin/.local/lib/python3.8/site-packages/dateutil/parser/_parser.py 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71 53 25% 18, 40, 59-69, 79, 90-92, 107-116, 130-154, 168-191 /home/admin/.local/lib/python3.8/site-packages/ellipticcurve/point.py 5 0 100% /home/admin/.local/lib/python3.8/site-packages/ellipticcurve/publicKey.py 48 32 33% 11-12, 15-23, 26-32, 35, 39, 43-76, 80-97 /home/admin/.local/lib/python3.8/site-packages/ellipticcurve/signature.py 35 23 34% 10-12, 15-18, 21, 25-40, 44-45 /home/admin/.local/lib/python3.8/site-packages/ellipticcurve/utils/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/ellipticcurve/utils/base.py 8 2 75% 8, 12 /home/admin/.local/lib/python3.8/site-packages/ellipticcurve/utils/binary.py 15 5 67% 15, 26, 36, 48-49 /home/admin/.local/lib/python3.8/site-packages/ellipticcurve/utils/compatibility.py 24 13 46% 13, 19, 22-39 /home/admin/.local/lib/python3.8/site-packages/ellipticcurve/utils/der.py 149 110 26% 27-28, 32-43, 47-53, 57, 61, 65, 69-74, 78-89, 93-111, 115-121, 125-131, 135-144, 148-152, 156-164, 168-180, 184-194, 198-207, 211-227, 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234, 237-252, 263-272, 275-279, 283-287, 291-292, 297-299, 302-311, 321-322, 325-329, 334-339, 346-351, 359, 367, 377, 387, 397-402, 412-417, 427, 434-436, 439-440, 443-444, 454, 464, 482-485, 490-497, 501-505, 515-536, 542-550, 567, 576-580, 584-585, 589-590, 594-595, 604-607, 655-663, 667-672, 677-681, 684-688, 692-716, 729-730, 733-740, 747-774, 777-778, 781-782, 787-796, 802-837, 850-851, 854-858, 861-878, 882-896, 899-903, 917, 921-922, 925, 930-932, 935-939, 951-952, 992-993, 1011-1013 /home/admin/.local/lib/python3.8/site-packages/matplotlib/bezier.py 222 186 16% 18-22, 42-62, 72-81, 91-92, 100-110, 151-178, 192-198, 214-215, 222, 227, 232, 237, 264-273, 291-305, 330-337, 348-401, 413-418, 424-429, 451-459, 474-533, 541-543, 554-594 /home/admin/.local/lib/python3.8/site-packages/matplotlib/category.py 85 50 41% 48-58, 80-85, 104-108, 112-113, 127, 131, 135, 147, 151, 155-156, 161-165, 178-181, 188-196, 211-223 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81-82, 88, 91, 102, 129-149, 178-181, 200-210, 252-264, 285-293, 341-343, 364-371, 396-403, 415-425, 458-495, 509-518, 527, 531, 537, 555-563, 573, 583-587, 591, 595-620, 636, 643-647, 654-658, 665-666, 718-724 /home/admin/.local/lib/python3.8/site-packages/matplotlib/collections.py 835 666 20% 156-202, 205, 208, 211, 215-221, 232, 251-300, 305, 310-341, 345-419, 431, 434, 443-471, 484-485, 494, 529-531, 535, 545-553, 558, 562, 574-582, 610-623, 635, 638, 649, 652, 676-690, 700-703, 707, 722-723, 727, 730-734, 748-751, 754, 757-760, 764, 767-783, 798-801, 815-817, 822, 825, 841-859, 868-897, 901, 906-925, 943, 957-967, 971-972, 994-997, 1000-1001, 1004, 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, 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1118-1124, 1132, 1140-1165 /home/admin/.local/lib/python3.8/site-packages/matplotlib/figure.py 1041 867 17% 69-70, 83-84, 88, 92, 96-98, 102-103, 107, 110, 116-118, 152-154, 161-178, 187-214, 218-239, 262-282, 286, 304-308, 314, 357-394, 401-404, 411-414, 421-425, 429, 433, 441, 451, 457, 467, 477, 489-490, 516-527, 615-641, 744-770, 774-783, 904-919, 926-957, 969-992, 1009, 1128-1150, 1188-1200, 1277-1315, 1346-1357, 1400-1418, 1460-1478, 1501-1502, 1543-1545, 1587-1614, 1639-1641, 1645-1647, 1659-1660, 1680-1693, 1705-1729, 1732-1737, 1766-1808, 1812-1827, 1831-1837, 1949-2148, 2151-2154, 2219-2252, 2256, 2260, 2266, 2276-2277, 2280, 2292-2308, 2316, 2332, 2335, 2350, 2358-2373, 2399, 2402, 2505-2597, 2600-2601, 2610-2620, 2652-2684, 2689, 2698-2700, 2736-2744, 2758, 2763-2766, 2769, 2780-2787, 2793, 2814-2819, 2827, 2851-2856, 2889-2890, 2909-2923, 2933, 3007-3024, 3056-3066, 3087, 3091, 3095, 3099, 3109-3110, 3127, 3144, 3148-3153, 3161-3185, 3192-3194, 3200, 3203-3220, 3223-3247, 3253, 3366-3378, 3429-3474, 3484-3494, 3507-3509, 3539-3549, 3600-3629 /home/admin/.local/lib/python3.8/site-packages/matplotlib/font_manager.py 563 423 25% 135-136, 177, 190-191, 207-212, 217-244, 250-258, 269-291, 295-301, 305-307, 347-456, 474-524, 594-608, 622-631, 634-642, 645, 648, 658, 664, 670, 676, 685, 693, 699, 705, 715, 725-729, 739-742, 752-755, 768-781, 794-807, 820-837, 844, 853-857, 865, 885-892, 896, 907-920, 938, 958-962, 991-1024, 1037-1047, 1053, 1060, 1067, 1073, 1077-1079, 1094-1111, 1123-1128, 1136-1139, 1149-1157, 1171-1175, 1188-1199, 1257-1265, 1269, 1316-1359, 1365-1444, 1454-1458, 1463-1464, 1490, 1515-1523, 1539-1540, 1545-1548 /home/admin/.local/lib/python3.8/site-packages/matplotlib/gridspec.py 277 216 22% 48-56, 59-63, 79, 83, 97-99, 108-113, 121, 130-135, 143, 167-205, 213-226, 230-263, 273-316, 371-379, 400-410, 425-434, 443, 467-474, 501-505, 511-521, 529, 553-555, 558, 570-605, 612, 616, 619, 629-630, 635-636, 641-645, 648, 651, 654, 657, 663-673, 679-683, 691, 697, 739 /home/admin/.local/lib/python3.8/site-packages/matplotlib/hatch.py 143 103 28% 16-17, 20-28, 33-34, 37-45, 50-55, 58-64, 69-75, 78-84, 91-97, 102-121, 126-129, 136-137, 144-145, 153-154, 162-168, 183-189, 205-225 /home/admin/.local/lib/python3.8/site-packages/matplotlib/image.py 760 661 13% 83-110, 123-157, 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, 1530-1564, 1619-1689, 1708-1724, 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 /home/admin/.local/lib/python3.8/site-packages/matplotlib/legend.py 470 385 18% 69-74, 77-80, 83-90, 93-94, 343, 416-657, 666-671, 677-680, 684, 687, 694-706, 711-737, 764, 769, 774, 778-779, 797-806, 816-906, 921-941, 945, 949, 953, 957, 963, 977-979, 983, 1001-1012, 1016, 1020-1022, 1026, 1030, 1040-1041, 1047-1050, 1072-1093, 1110, 1121-1158, 1161-1164, 1189-1198, 1202, 1209-1238, 1243-1250, 1298-1348 /home/admin/.local/lib/python3.8/site-packages/matplotlib/legend_handler.py 343 255 26% 41-43, 79-82, 85, 89-93, 98-102, 125-139, 164, 189-192, 195-206, 231-236, 249-273, 290-312, 343-350, 355-359, 369, 375-384, 389-396, 404-407, 410-415, 420-428, 440-443, 447-464, 468-473, 477, 487-502, 510, 521, 538-545, 551-629, 659-664, 670-712, 719-720, 748-773, 782-807, 813-817 /home/admin/.local/lib/python3.8/site-packages/matplotlib/lines.py 679 562 17% 36-60, 64-69, 78-106, 118-201, 262-271, 310-414, 440-484, 492, 506-508, 518, 537-538, 596-597, 605, 616-618, 622-624, 627-635, 645-651, 654, 657-699, 708-714, 718-720, 724-726, 732-878, 882, 890, 898, 906, 914, 922, 930, 938-948, 956, 959-965, 973, 981, 989, 997, 1006-1010, 1019-1023, 1027-1029, 1035-1037, 1047-1049, 1059-1061, 1089-1096, 1116-1119, 1130-1134, 1167-1179, 1192-1193, 1196-1207, 1217, 1227, 1237, 1248-1252, 1263-1266, 1276-1287, 1297-1308, 1329-1332, 1336-1355, 1368-1371, 1384-1387, 1395, 1403, 1416-1419, 1432-1435, 1443, 1451, 1462, 1472-1481, 1484-1521, 1525-1526, 1566-1575, 1590, 1594-1599 /home/admin/.local/lib/python3.8/site-packages/matplotlib/markers.py 427 328 23% 253-272, 278-291, 294, 297, 300, 312-316, 319, 322, 325, 340-367, 376, 383-386, 395, 402-405, 408, 412-413, 424-429, 445-458, 474-480, 483, 486-488, 491, 494, 497-515, 523-541, 544, 547-556, 559, 562-573, 584-611, 614, 617, 620, 623, 626-641, 644-655, 658-659, 662-682, 685-704, 707-728, 731-754, 757-775, 780-783, 786-787, 792-795, 798-801, 806-809, 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250, 254, 261, 265, 272, 279, 287-289, 308-319, 328-345, 348, 351, 394-417, 441-464, 477-483, 495, 537-546, 587-590, 599-601, 619-642, 651, 662, 671-682, 704-725, 735-738, 749-762, 772-788, 796, 807-810, 834-878, 889-922, 942-1001, 1019, 1029-1030, 1043-1045, 1077-1083 /home/admin/.local/lib/python3.8/site-packages/matplotlib/projections/__init__.py 28 8 71% 75, 95, 104-110 /home/admin/.local/lib/python3.8/site-packages/matplotlib/projections/geo.py 273 183 33% 24, 27-28, 33-34, 41-57, 61-106, 111-114, 119-120, 123, 126, 129-130, 133, 136, 139, 142, 145-146, 152, 159-162, 170-172, 179-181, 187-188, 195, 205, 213, 216, 219, 222, 236-237, 240, 244-245, 256-267, 271, 278, 282, 285-288, 291, 302-309, 313, 319-323, 327, 330-333, 336, 347-377, 381, 387-393, 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 860 526 39% 119-120, 135-157, 163-167, 175, 180-182, 186-193, 204-209, 231-356, 360-375, 383-384, 397, 445-446, 476, 512-516, 552-556, 576-584, 589, 594, 599-601, 609, 614, 619, 658-686, 803-869, 882-890, 902-906, 911, 916, 921-923, 940, 945, 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3267, 3278, 3289, 3300, 3311, 3322 /home/admin/.local/lib/python3.8/site-packages/matplotlib/quiver.py 390 338 13% 291-314, 318, 322-345, 348, 357-362, 365, 373-374, 377-385, 407-437, 441-443, 477-506, 516-527, 530-536, 540-544, 549-571, 575-577, 592-596, 599-605, 608-663, 670-723, 897-941, 967-973, 1024-1117, 1122-1162, 1173-1180 /home/admin/.local/lib/python3.8/site-packages/matplotlib/rcsetup.py 414 127 69% 68-69, 75-82, 99, 110, 127, 135-136, 159, 169-170, 185, 188-189, 218, 230-234, 238, 260, 282, 288, 290, 292, 294, 296-300, 304, 344-347, 354, 366-367, 381-384, 395-398, 411, 415, 427-428, 438, 457-483, 506-524, 534, 537-541, 549-552, 560, 568, 583-589, 683, 686, 689-692, 695-698, 705, 716-718, 738-739, 746, 750, 758, 761, 783, 786-792 /home/admin/.local/lib/python3.8/site-packages/matplotlib/scale.py 274 155 43% 69, 76, 86, 105-113, 120, 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, 708-709, 726 /home/admin/.local/lib/python3.8/site-packages/matplotlib/spines.py 315 261 17% 33, 54-86, 90-99, 103-109, 113-114, 126-131, 136-140, 153-197, 200, 203-206, 216-219, 223-225, 230-282, 287-290, 313-325, 329-330, 334-386, 408-419, 423, 429-442, 448-451, 456-460, 476-477, 491, 494-505, 508-512, 539, 543, 546, 549, 552-555, 559-574, 578, 582, 585, 588 /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 335 272 19% 94-103, 108-110, 113-114, 118, 122-123, 127, 131-138, 142-149, 153-164, 170, 176-177, 188-189, 202, 206-218, 222-228, 298-321, 342-345, 351-361, 365, 384, 388-389, 392, 401-415, 423-427, 431-444, 448, 452-457, 464-488, 500-508, 512-516, 520-521, 525-539, 543-545, 568-570, 574-577, 584-635, 650, 737-830 /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 812 676 17% 41-49, 67-90, 97, 105, 130, 165-183, 201-219, 223-233, 236-239, 246-268, 274-275, 278-281, 292-313, 317-321, 327, 340-342, 346, 350-361, 369-512, 531-552, 559, 568-582, 585-589, 593-594, 598-599, 603-604, 608, 626, 633-652, 659-675, 681-685, 692-736, 742-806, 810, 814, 824, 834, 844, 854, 864, 874, 884, 891, 897-899, 905, 909, 916, 940-963, 977-983, 995-998, 1010-1012, 1026-1028, 1040-1042, 1065-1066, 1080-1081, 1095-1096, 1113-1114, 1126, 1148, 1164-1165, 1181-1182, 1192-1193, 1203-1204, 1214-1215, 1227-1236, 1246-1247, 1259-1263, 1277-1281, 1296-1305, 1318-1319, 1329-1333, 1337, 1349, 1353, 1371, 1395-1397, 1407-1408, 1412, 1415-1419, 1436-1454, 1463-1467, 1470-1478, 1482-1562, 1569, 1594, 1602, 1606-1607, 1611-1618, 1639-1654, 1673, 1848-1885, 1888-1895, 1899, 1903-1909, 1918, 1922, 1930, 1938, 1945-1947, 1954-2016, 2021-2035, 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 996 19% 165-167, 170, 173, 176, 179, 182, 186, 193, 196-197, 213, 217-218, 225, 233, 236, 245, 255, 261, 269, 283-284, 294-297, 300, 303, 316-317, 325, 328, 331, 346, 354, 365, 374, 428-439, 452, 481-486, 498, 509-512, 520, 531, 544-564, 572-578, 588, 620-622, 626-650, 654-666, 672-694, 698-703, 706-740, 748-776, 780-809, 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, 1644-1649, 1665, 1673, 1685-1686, 1690-1693, 1697-1698, 1701, 1717-1719, 1723-1724, 1727, 1739-1747, 1756, 1767, 1791-1795, 1800, 1804, 1808-1811, 1815-1816, 1819-1830, 1835-1850, 1860, 1864-1865, 1869-1870, 1873-1879, 1886-1896, 1900-1907, 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/home/admin/.local/lib/python3.8/site-packages/numpy/fft/__init__.py 8 0 100% /home/admin/.local/lib/python3.8/site-packages/numpy/fft/_pocketfft.py 164 120 27% 50-75, 79-88, 93-102, 111-114, 119, 211-216, 312-317, 405-410, 509-514, 607-612, 674-679, 683-698, 702-708, 712, 815, 918, 1014, 1107, 1200-1205, 1257, 1362-1367, 1424 /home/admin/.local/lib/python3.8/site-packages/numpy/fft/helper.py 46 33 28% 16, 64-73, 111-120, 160-169, 216-221 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/__init__.py 39 0 100% /home/admin/.local/lib/python3.8/site-packages/numpy/lib/_datasource.py 177 139 21% 59-66, 104-128, 146-147, 150-151, 192-193, 248-254, 258-261, 267-268, 274-278, 288-291, 295-300, 306-315, 325-342, 357-373, 399-415, 421-429, 463-485, 521-533, 578-579, 582, 586-591, 595, 618, 652, 683, 700-704 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/_iotools.py 352 300 15% 30-35, 42-46, 53-57, 81-84, 120-131, 168, 172-197, 201-206, 209-216, 219-224, 227, 288-310, 339-380, 383, 413-419, 505, 524, 529, 539-541, 568-582, 587-596, 601-669, 672-675, 678-700, 703, 707-723, 746-751, 754-763, 796-820, 861-898 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/_version.py 75 61 19% 56-76, 80-97, 101-112, 115-134, 137, 140, 143, 146, 149, 152, 155 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/arraypad.py 218 200 8% 29-30, 55, 81-83, 109-126, 146-151, 175-183, 208-227, 257-293, 321-378, 401-451, 482-518, 522, 736-876 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/arraysetops.py 197 166 16% 34, 82-122, 127-130, 135, 270-317, 325-359, 364, 430-463, 467, 500-510, 514, 584-631, 635, 732-733, 738, 775, 779, 819-824 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/arrayterator.py 71 58 18% 85-90, 93, 101-125, 132-134, 161-162, 172, 177-219 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/format.py 266 234 12% 192-194, 212-216, 230-235, 238-245, 270-281, 304-336, 352-364, 371-389, 396-413, 430-440, 452, 468, 499, 532, 552-567, 576-625, 663-696, 731-789, 842-890, 902-918 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/function_base.py 1153 968 16% 56, 114-143, 147, 231-241, 277, 377-419, 486-490, 494-497, 588-618, 622-623, 665-719, 723, 804, 810-811, 989-1157, 1161, 1249-1294, 1298, 1406-1439, 1443, 1485-1496, 1500, 1569-1596, 1600, 1627-1637, 1686, 1689-1693, 1698, 1750, 1754, 1794-1798, 1833-1840, 1866-1869, 1887-1905, 1926-1934, 1939, 1945-1948, 2113, 2118, 2122, 2131, 2140-2163, 2168-2232, 2236-2253, 2257-2316, 2321, 2448-2543, 2548, 2679-2701, 2796-2801, 2905-2910, 3009-3014, 3109-3114, 3182-3190, 3194, 3198, 3202, 3256-3262, 3388-3392, 3396, 3475-3477, 3481, 3508-3510, 3539-3565, 3570, 3655-3660, 3666-3716, 3721, 3863-3867, 3873, 3976-3979, 3986-3992, 3997-4004, 4009-4015, 4020-4122, 4126, 4215-4240, 4244, 4353-4375, 4379, 4447-4560, 4564, 4656-4755, 4759, 4811-4817, 4821, 4915-4932 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/histograms.py 287 254 11% 29, 49-50, 72-73, 96-97, 118-119, 146-161, 182-196, 224-226, 263-270, 285-301, 309-331, 342-357, 382-451, 460, 467, 668-670, 675, 791-929, 934-940, 1014-1129 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/index_tricks.py 258 185 28% 32, 93-107, 149-207, 325-420, 423, 593, 607, 610, 657-661, 665, 678-681, 695-696, 758-761, 775, 891-909, 977-978, 982, 1006-1013 /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 854 780 9% 34-37, 83, 86-89, 97, 108-112, 189-202, 205, 208, 215-221, 224, 228, 231, 242-260, 269-273, 277-281, 396-450, 455, 519-529, 534-535, 618, 622-623, 689, 695-726, 732-758, 768, 903-1188, 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 438 334 24% 41, 138-165, 169, 229-261, 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 263 196 25% 31-49, 53, 161-170, 174, 251-260, 264, 359-414, 418, 487-505, 509, 588-602, 648, 660, 716-723, 727-732, 736, 766-792, 796, 866-874, 878, 937-942, 989-991, 1034-1036, 1043-1048, 1055-1060, 1064, 1136-1164, 1168, 1238-1260 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/stride_tricks.py 91 70 23% 21-22, 26-35, 97-114, 119, 301-335, 340-359, 363, 411, 420-428, 470-471, 475, 536-544 /home/admin/.local/lib/python3.8/site-packages/numpy/lib/twodim_base.py 177 114 36% 34-40, 44, 95-98, 151-154, 158, 211, 216, 220, 231, 289-303, 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 90 35% 70-77, 81, 112-114, 118, 157-160, 164, 200-203, 207, 240-244, 300, 336-341, 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 454 365 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, 1003-1004, 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 678 574 15% 88, 91, 94, 97, 100, 103-105, 108-110, 113, 126, 129, 133, 137-157, 165-174, 177-185, 188-190, 194-196, 200-203, 206-208, 212, 230, 235, 286-306, 310, 378-395, 399, 456-467, 473, 538-546, 550, 618-666, 756-764, 770, 890-982, 1059-1077, 1081, 1159-1176, 1179-1181, 1314-1333, 1453-1473, 1479, 1617-1674, 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 1774 26% 102-113, 122, 124, 204-212, 217-222, 270-277, 282-291, 342, 393, 414-425, 439-469, 532-534, 543-547, 575-579, 627-636, 646-663, 708-714, 768-776, 779, 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, 1466-1469, 1534-1537, 1544-1547, 1621-1636, 1682-1686, 1726-1753, 1788-1809, 1814-1817, 1924-1943, 1969, 1995, 2021, 2047, 2073, 2101-2103, 2139-2143, 2179-2183, 2244-2251, 2323-2331, 2361-2373, 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, 2855-2882, 2887, 2889, 2895-2896, 2900-2909, 2915-2932, 2938, 2943, 2956, 3012, 3030-3042, 3047, 3054-3058, 3062, 3065, 3074-3121, 3180-3183, 3190-3194, 3204-3210, 3224-3337, 3347-3402, 3411-3419, 3427-3431, 3438-3500, 3512, 3516, 3532-3535, 3539, 3554-3555, 3570-3571, 3576, 3591-3594, 3599, 3629-3630, 3635, 3652, 3660, 3664-3665, 3697-3706, 3710-3725, 3776-3809, 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, 4585-4591, 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, 6422, 6462-6469, 6472, 6475, 6478, 6481-6485, 6491-6500, 6505, 6510, 6524, 6527, 6530, 6536-6542, 6559, 6611-6616, 6640-6647, 6651-6679, 6683-6695, 6698-6705, 6710-6717, 6723-6729, 6766-6777, 6812-6813, 6833-6865, 6872-6882, 6898-6908, 6923, 6967-6983, 6998-7001, 7016-7022, 7037-7043, 7059-7062, 7083-7101, 7136-7139, 7154-7158, 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, 7951-7952, 8000-8002, 8011, 8017, 8082, 8116-8127, 8186 /home/admin/.local/lib/python3.8/site-packages/numpy/ma/extras.py 560 468 16% 48, 101-102, 152-154, 207-209, 259, 262, 272-280, 290-293, 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 238 178 25% 15-33, 69, 116-165, 168-187, 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 873 772 12% 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, 703-852, 933-934, 1015-1046, 1127-1128, 1135, 1165-1206, 1231-1252, 1289-1290, 1300, 1329-1330, 1353-1354, 1380-1401, 1437-1447, 1455-1473, 1521-1530, 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/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, 198, 228, 236-261, 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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, 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997-1021, 1029-1034 /home/admin/.local/lib/python3.8/site-packages/requests/packages.py 17 4 76% 5-10 /home/admin/.local/lib/python3.8/site-packages/requests/sessions.py 268 219 18% 56, 67-88, 97-103, 115-125, 129-157, 173-281, 288-301, 315-332, 338-354, 396-451, 454, 457, 469-500, 563-591, 601-602, 612-613, 623-624, 637, 649, 661, 671, 680-749, 758-780, 788-794, 798-799, 806-810, 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 19 51% 41-44, 49, 52, 55, 58, 61, 65, 68-73, 77, 80, 91, 96, 99 /home/admin/.local/lib/python3.8/site-packages/requests/utils.py 485 411 15% 76-121, 127-130, 134-196, 202-253, 258-260, 268-297, 303-310, 331-337, 357-366, 393-398, 424-433, 445-459, 469-474, 485, 493-506, 521-535, 545-560, 566-577, 582-587, 602-626, 641-656, 667-678, 689-693, 703-704, 711-715, 724-739, 750-761, 772-821, 830-833, 842-859, 873-886, 902, 920-946, 962-984, 993-1013, 1022-1029, 1038-1040, 1044-1056, 1068-1076, 1083-1094 /home/admin/.local/lib/python3.8/site-packages/sendgrid/__init__.py 7 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/base_interface.py 22 5 77% 44, 49, 59-62 /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/__init__.py 0 0 100% /home/admin/.local/lib/python3.8/site-packages/sendgrid/helpers/endpoints/__init__.py 0 0 100% /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 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/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 18 40% 19-27, 36, 48, 56, 65-66, 75-81 /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 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/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 11 52% 13-18, 26, 35, 43, 53, 60, 69 /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 21 22% 18-28, 42-55, 66-69 /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 14 33% 27, 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 259 188 27% 54-88, 108-138, 156-176, 193-200, 221-244, 251-293, 296-304, 307-319, 322, 325-333, 352-365, 412-439, 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/exceptions.py 15 0 100% /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/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, 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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, 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/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 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/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/_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 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/extmath.py 223 193 13% 41-46, 69-78, 92-95, 111-115, 135-157, 211-242, 327-374, 424-448, 488-501, 535-547, 579-592, 619-626, 649-657, 686-690, 752-789, 841-867, 886-889, 907-914 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19 17% 33-61 /home/admin/.local/lib/python3.8/site-packages/sklearn/utils/validation.py 397 332 16% 66-74, 80, 86-111, 124, 163-177, 182, 189-212, 236-245, 259-262, 277-283, 298-300, 348-394, 398-400, 494-685, 691-702, 811-833, 852-864, 880-886, 914, 948-974, 1023-1041, 1057-1068, 1102-1110, 1194-1273, 1304-1326, 1351-1361, 1384-1400 /home/admin/.local/lib/python3.8/site-packages/tqdm/__init__.py 8 0 100% /home/admin/.local/lib/python3.8/site-packages/tqdm/_dist_ver.py 1 0 100% /home/admin/.local/lib/python3.8/site-packages/tqdm/_monitor.py 45 31 31% 31-39, 42-45, 49, 54-92, 95 /home/admin/.local/lib/python3.8/site-packages/tqdm/_tqdm_pandas.py 10 6 40% 12-24 /home/admin/.local/lib/python3.8/site-packages/tqdm/cli.py 188 173 8% 17-40, 54-97, 151-311 /home/admin/.local/lib/python3.8/site-packages/tqdm/gui.py 10 1 90% 181 /home/admin/.local/lib/python3.8/site-packages/tqdm/std.py 696 579 17% 46-49, 93-100, 103-104, 107-108, 111, 114, 118-121, 127-128, 154-161, 165, 169-184, 187-211, 227-229, 238-242, 390-398, 415-420, 437-439, 448-465, 537-663, 667-680, 685-687, 699-717, 722-726, 735-756, 761, 766-768, 805-950, 963-1104, 1107-1111, 1114, 1122-1130, 1133-1134, 1137, 1140-1146, 1149, 1152, 1156, 1159, 1165-1197, 1225-1264, 1268-1308, 1312-1324, 1339-1351, 1355-1359, 1371-1381, 1393-1395, 1399-1401, 1416-1432, 1438-1440, 1444-1445, 1450-1455, 1478-1499, 1515-1520, 1525 /home/admin/.local/lib/python3.8/site-packages/tqdm/utils.py 175 113 35% 22, 28-31, 70, 81-96, 108-109, 112-113, 119, 122, 125, 128, 131, 134, 139, 142, 146-149, 153, 159, 169-170, 176, 179, 191-210, 213-218, 222, 231-248, 252-262, 266-269, 273-278, 374, 382, 389-398 /home/admin/.local/lib/python3.8/site-packages/tqdm/version.py 8 6 25% 4-9 /home/admin/.local/lib/python3.8/site-packages/zipp.py 123 73 41% 28, 47-50, 62, 73-75, 78-79, 82, 89-92, 100-111, 121-124, 127-130, 223-224, 232-242, 246, 250, 254, 258, 262, 265-266, 269-270, 273, 276, 279, 282, 285, 288-291, 294, 297, 300-301, 307-312 /home/admin/mtr/.credentials/credentials.py 1 0 100% /home/admin/workarea/git/Velours/python/dev/__init__.py 0 0 100% /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/mtr/__init__.py 1 0 100% /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 180 166 8% 18-61, 66-82, 87-102, 105-107, 111-133, 137-232, 240-256, 262-268, 293 /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 457 392 14% 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, 317-323, 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, 473-485, 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 291 256 12% 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, 368-397, 402-429, 436-450, 455-485, 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 1099 25% 44, 57, 69, 87, 95-97, 100-104, 117-135, 149-153, 166-170, 186-295, 303-308, 311-316, 319-326, 329-348, 351-359, 362-369, 378-402, 406-409, 420-461, 472-492, 503-523, 526-531, 534-541, 551-572, 576-597, 608, 620, 626-627, 630, 646, 651, 658-659, 662-663, 682, 689, 696, 712, 719, 722, 726, 744, 751, 761-765, 771-780, 801, 808-811, 831, 851-923, 934-1044, 1055, 1083, 1090, 1123-1124, 1127-1129, 1135-1138, 1141-1146, 1150-1153, 1158, 1164, 1179, 1191-1195, 1206, 1211-1218, 1228-1232, 1250-1310, 1337, 1339, 1342-1349, 1366-1374, 1384-1396, 1400-1407, 1410-1416, 1419-1427, 1432-1439, 1443-1456, 1460-1473, 1476-1483, 1486-1493, 1505-1506, 1516-1517, 1524-1534, 1541, 1548-1554, 1556, 1568-1573, 1585-1590, 1602-1607, 1613-1617, 1624-1630, 1635-1649, 1655-1663, 1668-1687, 1691-1710, 1714-1729, 1733-1753, 1757-1775, 1781-1803, 1808-1818, 1821-1829, 1835-1852, 1858-1868, 1873-1908, 1912-1920, 1923-1927, 1930-1952, 1957-1970, 1975-1983, 1986-1994, 2001-2026, 2029-2069, 2075-2083, 2087-2095, 2100-2109, 2112-2121, 2124-2129, 2132-2140, 2144-2212, 2257-2281, 2297-2298, 2301, 2303, 2313-2331, 2334-2342, 2352-2377, 2385-2386, 2394, 2413-2444, 2449-2477, 2481-2487, 2491-2510, 2514-2523, 2527-2531, 2535-2547, 2551-2578, 2582-2609, 2612-2650, 2654-2690, 2693-2708, 2713-2728, 2739-2775, 2784-2820 /home/admin/workarea/git/Velours/python/mtr/database_queries/descriptor_queries.py 354 327 8% 22-79, 82-103, 106-145, 160-264, 270-301, 304-321, 328-352, 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 83 44% 12-13, 33-34, 36-37, 45-46, 49, 54-61, 74, 83-95, 103-114, 117-133, 137-140, 147-160, 163-167, 182 /home/admin/workarea/git/Velours/python/mtr/database_queries/graph_nodes_queries.py 77 64 17% 22-34, 38-54, 59-130 /home/admin/workarea/git/Velours/python/mtr/database_queries/hashtag_queries.py 158 118 25% 33-50, 64-65, 72, 80-91, 94-110, 113-125, 128-133, 136-142, 145-155, 158-165, 168-183, 186-193, 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 84 20% 30-71, 74-81, 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 558 473 15% 12, 50-75, 81-101, 107-123, 129-142, 148-161, 180-181, 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, 674-687, 694-721, 724-742, 749-802, 805-826, 832-849, 852-864, 868-922, 927-972, 975-986, 989-1010 /home/admin/workarea/git/Velours/python/mtr/database_queries/portfolio_queries.py 511 448 12% 31-50, 56-72, 75-94, 97-114, 118-124, 127-136, 140-158, 163-180, 184-199, 202-212, 215-222, 225-235, 240-255, 258-263, 266-271, 274-284, 287-299, 302-311, 315-327, 332-341, 344-354, 357-365, 369-375, 378-383, 386-390, 393-397, 400-410, 415-468, 473-497, 513-519, 522-526, 535-541, 548-571, 576-584, 589, 594, 598-608, 611-624, 627-631, 634-638, 642-662, 666-712, 717-748, 750-759, 764-801 /home/admin/workarea/git/Velours/python/mtr/datou/__init__.py 1 0 100% /home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py 1753 1149 34% 43-44, 75-101, 108-109, 112-113, 117-118, 153, 158, 161, 172-174, 188-189, 199, 206-209, 212-213, 227-229, 241-243, 246-247, 277, 302-306, 311, 328-332, 335, 344-406, 434, 462-463, 481-495, 509-516, 522-573, 580-624, 652-653, 660-663, 674-677, 691, 696, 700-702, 721, 729-730, 738-739, 773-776, 788-797, 807-810, 818, 821, 823-825, 829-853, 863-870, 874, 877, 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, 1561, 1564, 1567, 1570-1571, 1574-1577, 1580, 1583, 1586-1588, 1596, 1603-1609, 1612-1617, 1620-1625, 1634-1653, 1656-1659, 1662-1672, 1675-1678, 1682-1735, 1739-1742, 1747-1785, 1790-1791, 1795-1804, 1809-1813, 1819-1822, 1827-1871, 1878-1894, 1903-1919, 1924-1941, 1945-1957, 1966-1969, 1975-1985, 1988-1999, 2002-2006, 2009-2012, 2015-2018, 2021-2024, 2027-2034, 2037-2041, 2045-2068, 2096, 2108, 2113-2122, 2126-2129, 2148-2149, 2154-2203, 2206-2241, 2258-2264, 2267-2277, 2280-2282, 2299, 2313, 2316-2328, 2331-2332, 2343-2345, 2355, 2365-2366, 2371, 2375-2381, 2391, 2422, 2428, 2430, 2432, 2436, 2438, 2440, 2442, 2446, 2448, 2451, 2453, 2455, 2457, 2459, 2461, 2463, 2465, 2467, 2469, 2471, 2473, 2475, 2477, 2479, 2481, 2483, 2485, 2487, 2489, 2491, 2493, 2495, 2497, 2499, 2501, 2503, 2505, 2509, 2511, 2513, 2515, 2517, 2519, 2521, 2523, 2525, 2528, 2530, 2532, 2534, 2536, 2538, 2540, 2542, 2544, 2546, 2548, 2550, 2552, 2555, 2559, 2562, 2564, 2566, 2568, 2570, 2572, 2574, 2577, 2580, 2582, 2584, 2586, 2588, 2590, 2592, 2594, 2596, 2598, 2600, 2603, 2605, 2607, 2609, 2611, 2616-2667, 2683-2688, 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 478 203 58% 16-23, 35-37, 46, 51-62, 73-84, 101-122, 135-149, 178, 194, 200, 212, 215, 222-246, 252-290, 302-321, 335, 358-382, 385, 389, 392, 396, 399-402, 412, 417-418, 439-440, 469-470, 495, 499-500, 512-513, 522-523, 570, 579, 589, 616, 635-652, 660, 665, 675-679, 684-685, 687-691, 694, 723-743, 747-771 /home/admin/workarea/git/Velours/python/mtr/datou/datou_lib_step_data_increase.py 204 197 3% 7-121, 125-162, 167-218, 221-294, 297-339 /home/admin/workarea/git/Velours/python/mtr/datou/datou_lib_step_save.py 1287 1218 5% 10-15, 18-183, 191-369, 374-436, 445-486, 489-553, 559-633, 638-744, 747-761, 764-779, 783-809, 813-864, 873-902, 907-936, 943-1043, 1047-1078, 1086-1087, 1095, 1098, 1102, 1118-1213, 1223-1253, 1257-1279, 1295-1332, 1336-1357, 1362-1387, 1393-1457, 1472-1500, 1503-1519, 1523-1534, 1538-1619, 1623-1638, 1658-1727, 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 157 135 14% 11-32, 35-36, 40-56, 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/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 484 480 1% 7-29, 34-274, 288-767, 908-918 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_initialisation.py 372 364 2% 15-244, 249-267, 271-372, 376-558 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_post_processing.py 1061 858 19% 28-121, 127-305, 327-328, 356-363, 369, 371-449, 454-458, 481-482, 495-503, 505-513, 538, 541-542, 547, 549, 555, 568, 586-621, 637-647, 653-655, 660-661, 665, 669-694, 700-701, 704-705, 714-721, 724-732, 735-736, 749-867, 874-924, 932-1006, 1011-1081, 1099-1269, 2533, 2536-2538, 2541-2542, 2545-2552, 2562, 2569-2581, 2584, 2588-2592, 2599-2606, 2621-2638, 2655-2659, 2667-2669, 2677-2865 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_pre_processing.py 1402 1368 2% 34-89, 92-196, 200-500, 506, 510-696, 703-838, 843-885, 889-968, 975-1356, 1362-1459, 1463-1503, 1508-1551, 1555-1630, 1634-1715, 1719-1733, 1739-1892, 1895-1898, 1905-1986, 1989-2177 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_process.py 1968 1828 7% 40, 47-59, 62, 69-308, 313-424, 427-556, 560-628, 632-779, 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, 1081-1187, 1196-1272, 1279-1466, 1470-1499, 1503-1579, 1586-1674, 1678-1855, 1859-2027, 2031-2078, 2088-2369, 2373-2418, 2422-2481, 2485-2511, 2515-2619, 2626-2814, 2995-3193, 3452-3532, 3536-3575 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_send_or_copy.py 554 540 3% 19-195, 200-268, 273-332, 336-379, 383-488, 493-623, 628-790, 795-841 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_sort.py 193 188 3% 12-115, 119-171, 178-183, 189-287, 291-305 /home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_util.py 298 241 19% 11-21, 25-28, 34-48, 62-134, 143-155, 179-183, 194-196, 198-201, 209, 213-219, 224-231, 236-315, 319-324, 327-333, 337-398, 402-411, 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 322 286 11% 52-92, 96-119, 123-184, 187-213, 218-335, 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 299 255 15% 35-43, 49-298, 304-342, 359, 373-374, 383-387, 400-418, 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/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/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 88 33% 40, 44, 47-50, 52, 54, 59, 61, 65-68, 91-134, 137-150, 162, 164-167, 170-194 /home/admin/workarea/git/Velours/python/mtr/ses_mailer.py 55 43 22% 20-44, 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/image_utils.py 328 255 22% 21-28, 37-52, 72-85, 88, 91-113, 118-122, 129, 138-162, 166, 174, 181-191, 194-236, 239, 242-253, 256, 259, 262, 265-298, 301-314, 343, 346-354, 363-365, 368-381, 385-397, 401-441, 446-465, 470-473, 476-484 /home/admin/workarea/git/Velours/python/mtr/simple_image_editor/simple_image_editor.py 2091 1880 10% 24-25, 43-51, 60-81, 86-126, 131-134, 140-324, 329-332, 335-359, 365-387, 391-422, 429-446, 451-469, 475-485, 492-598, 605-613, 619-793, 798-815, 821-853, 859-907, 910-911, 916-936, 942-972, 979-1100, 1109-1145, 1151-1183, 1189-1227, 1232-1251, 1259-1567, 1575-1639, 1643-1654, 1660-1683, 1690-1756, 1762-1828, 1832-1907, 1913-1990, 1993-2006, 2019, 2023-2024, 2035, 2041-2042, 2044-2045, 2051, 2057-2064, 2074-2128, 2131, 2136-2234, 2237-2384, 2395-2421, 2431-2465, 2479-2741, 2752-2799, 2804-2840, 2846-2881, 2894, 2900, 2906, 2912, 2918, 2924, 2929-2966, 2973-3014, 3020-3044, 3052-3129, 3140-3156, 3164-3189, 3200-3304, 3339, 3347, 3359-3360, 3362-3363, 3387, 3409-3417, 3458, 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/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/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 151 131 13% 15-29, 32-48, 51-54, 57-79, 92-99, 103-111, 118-127, 130, 133-142, 145-156, 160-174, 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 44 28% 23, 25-30, 39-44, 48, 53-67, 70, 76-94 /home/admin/workarea/git/Velours/python/mtr/utils/upload_batch.py 58 45 22% 26-78, 86-87 /home/admin/workarea/git/Velours/python/mtr/utils/utils_timer.py 11 8 27% 12-20 /home/admin/workarea/git/Velours/python/prod/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/prod/caffe_vision.py 1390 1299 7% 47, 68-72, 77-81, 89-215, 220-274, 279-280, 284-373, 378-426, 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, 1034-1043, 1051-1112, 1116-1121, 1126-1333, 1401-2359 /home/admin/workarea/git/Velours/python/tests/__init__.py 0 0 100% /home/admin/workarea/git/Velours/python/tests/cod_main_test.py 75 67 11% 8-59, 69-124, 128, 131, 134, 138 /home/admin/workarea/git/Velours/python/tests/datou_test.py 1923 1826 5% 24-72, 83-130, 140-232, 236-277, 280-366, 378-416, 428-472, 482-518, 523-588, 594-681, 692-752, 762-837, 851-889, 900-938, 949-1000, 1011-1073, 1084-1176, 1269-1339, 1350-1811, 1822-1879, 1889-1949, 1959-2067, 2081-2133, 2144-2215, 2230-2332, 2343-2401, 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/usr/lib/python3/dist-packages/chardet/euckrfreq.py 3 0 100% /usr/lib/python3/dist-packages/chardet/euckrprober.py 16 6 62% 36-39, 43, 47 /usr/lib/python3/dist-packages/chardet/euctwfreq.py 3 0 100% /usr/lib/python3/dist-packages/chardet/euctwprober.py 16 6 62% 35-38, 42, 46 /usr/lib/python3/dist-packages/chardet/gb2312freq.py 3 0 100% /usr/lib/python3/dist-packages/chardet/gb2312prober.py 16 6 62% 35-38, 42, 46 /usr/lib/python3/dist-packages/chardet/hebrewprober.py 77 48 38% 155-162, 165-171, 175-176, 179, 193, 223-253, 259-280, 284, 289-292 /usr/lib/python3/dist-packages/chardet/jisfreq.py 3 0 100% /usr/lib/python3/dist-packages/chardet/jpcntx.py 81 61 25% 124-129, 132-141, 144-168, 171, 175-178, 181, 185-186, 190, 193-210, 214-231 /usr/lib/python3/dist-packages/chardet/langbulgarianmodel.py 5 0 100% /usr/lib/python3/dist-packages/chardet/langcyrillicmodel.py 13 0 100% /usr/lib/python3/dist-packages/chardet/langgreekmodel.py 5 0 100% /usr/lib/python3/dist-packages/chardet/langhebrewmodel.py 3 0 100% /usr/lib/python3/dist-packages/chardet/langthaimodel.py 3 0 100% /usr/lib/python3/dist-packages/chardet/langturkishmodel.py 3 0 100% /usr/lib/python3/dist-packages/chardet/latin1prober.py 52 29 44% 98-101, 104-106, 110, 114, 117-128, 131-145 /usr/lib/python3/dist-packages/chardet/mbcharsetprober.py 44 33 25% 40-43, 46-51, 55, 59, 62-88, 91 /usr/lib/python3/dist-packages/chardet/mbcsgroupprober.py 14 3 79% 43-54 /usr/lib/python3/dist-packages/chardet/mbcssm.py 41 0 100% /usr/lib/python3/dist-packages/chardet/sbcharsetprober.py 75 60 20% 40-51, 54-61, 65-68, 72-75, 78-122, 125-132 /usr/lib/python3/dist-packages/chardet/sbcsgroupprober.py 19 8 58% 45-73 /usr/lib/python3/dist-packages/chardet/sjisprober.py 49 34 31% 38-42, 45-46, 50, 54, 57-87, 90-92 /usr/lib/python3/dist-packages/chardet/universaldetector.py 124 104 16% 82-92, 100-109, 125-218, 229-286 /usr/lib/python3/dist-packages/chardet/utf8prober.py 43 29 33% 39-42, 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37, 40, 47-48, 53-54, 57, 73, 82-83, 100, 103, 111, 127-156, 160-181, 197, 208-214, 221-225, 242-243 /usr/lib/python3/dist-packages/idna/__init__.py 2 0 100% /usr/lib/python3/dist-packages/idna/core.py 282 244 13% 37-41, 44, 47, 50, 55-57, 62-64, 70-124, 129-131, 136-140, 145-146, 151-194, 199-235, 240-267, 272-292, 297-313, 318-339, 346-372, 377-400 /usr/lib/python3/dist-packages/idna/idnadata.py 4 0 100% /usr/lib/python3/dist-packages/idna/intranges.py 29 24 17% 18-29, 32, 35, 40-53 /usr/lib/python3/dist-packages/idna/package_data.py 1 0 100% /usr/lib/python3/dist-packages/iso8601/__init__.py 1 0 100% /usr/lib/python3/dist-packages/iso8601/iso8601.py 79 64 19% 22, 76-134, 144-151, 158-172, 191-214 /usr/lib/python3/dist-packages/keyring/__init__.py 3 0 100% /usr/lib/python3/dist-packages/keyring/backend.py 84 20 76% 85-87, 90-91, 99, 108, 119, 133-140, 151, 157, 165, 168, 196-198 /usr/lib/python3/dist-packages/keyring/backends/OS_X.py 46 25 46% 30, 33-43, 47-58, 62-69 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16 1 94% 39 /usr/lib/python3/dist-packages/keystoneauth1/exceptions/http.py 147 55 63% 72-83, 254-259, 394-460 /usr/lib/python3/dist-packages/keystoneauth1/exceptions/oidc.py 14 0 100% /usr/lib/python3/dist-packages/keystoneauth1/exceptions/response.py 7 2 71% 24-25 /usr/lib/python3/dist-packages/keystoneauth1/exceptions/service_providers.py 7 3 57% 22-24 /usr/lib/python3/dist-packages/keystoneauth1/plugin.py 48 29 40% 33, 62, 95-100, 124-131, 149-154, 176-180, 193, 209, 224, 239, 254, 268, 287, 304, 315 /usr/lib/python3/dist-packages/keystoneauth1/session.py 539 443 18% 36-37, 65-70, 81-86, 91-106, 114, 118, 124-131, 138-139, 142-153, 162-195, 208-222, 238-240, 247-248, 251-254, 257-260, 352-388, 392-399, 403, 407, 410, 413-429, 434-441, 452-459, 464-517, 522-580, 593-623, 751-983, 1001-1107, 1115, 1123, 1131, 1139, 1147, 1155, 1158-1165, 1182-1183, 1205, 1220-1225, 1241-1242, 1257-1258, 1284-1285, 1325-1343, 1353-1354, 1371-1372, 1389-1390, 1397, 1401, 1416-1451 /usr/lib/python3/dist-packages/keystoneclient/__init__.py 15 0 100% /usr/lib/python3/dist-packages/keystoneclient/_discover.py 137 109 20% 36-70, 76-106, 125-132, 142, 161-183, 199-241, 255-262, 274-275, 307-312, 329 /usr/lib/python3/dist-packages/keystoneclient/access.py 435 225 48% 52-85, 88-89, 94, 103-110, 121, 128, 138, 142, 146-149, 157, 165, 177, 185, 196, 207, 215, 223, 231, 239, 247, 252, 268, 276, 284, 292, 302, 310, 318, 328, 333, 344, 355, 372, 388, 396, 404, 412, 420, 428, 440, 449, 456-458, 465-470, 473, 477-480, 484, 488, 492, 496, 500, 504, 508, 512, 516, 520, 524-544, 553-561, 565, 569, 573, 577, 581, 586, 590-610, 614-615, 619-620, 629-638, 647-656, 660, 664, 668, 672-675, 679-682, 689-696, 700-705, 708, 712, 716, 720, 724, 728-733, 737-742, 746, 750, 754, 758-760, 764-766, 770-772, 776-778, 782-784, 788-790, 799-803, 807, 811, 815, 819, 823, 827, 836-845, 854-864, 868, 872, 876-879, 883-886 /usr/lib/python3/dist-packages/keystoneclient/auth/__init__.py 4 0 100% /usr/lib/python3/dist-packages/keystoneclient/auth/base.py 82 45 45% 46-48, 63-67, 86-93, 126, 159-164, 186, 199, 215, 230, 245, 257, 267, 285-297, 315-318, 328-329, 344-347, 366-374 /usr/lib/python3/dist-packages/keystoneclient/auth/cli.py 29 21 28% 43-65, 87-95 /usr/lib/python3/dist-packages/keystoneclient/auth/conf.py 28 14 50% 41, 57, 83-93, 123-132 /usr/lib/python3/dist-packages/keystoneclient/auth/identity/__init__.py 12 0 100% /usr/lib/python3/dist-packages/keystoneclient/auth/identity/base.py 123 80 35% 29, 49-66, 74-78, 86-90, 98-102, 110-114, 122-126, 134-138, 146-150, 158-162, 206, 215-228, 250-254, 270-274, 312-360, 363, 366, 395-414, 418-420 /usr/lib/python3/dist-packages/keystoneclient/auth/identity/generic/__init__.py 4 0 100% /usr/lib/python3/dist-packages/keystoneclient/auth/identity/generic/base.py 74 44 41% 30, 63-73, 78, 83, 112, 118, 125, 134-180, 183-186, 190-192 /usr/lib/python3/dist-packages/keystoneclient/auth/identity/generic/password.py 33 19 42% 23, 46-52, 55-67, 77-79, 83-86 /usr/lib/python3/dist-packages/keystoneclient/auth/identity/generic/token.py 21 10 52% 22, 34-35, 38-42, 46-48 /usr/lib/python3/dist-packages/keystoneclient/auth/identity/v2.py 108 62 43% 41-49, 56-61, 66, 71, 74-94, 131-144, 149, 154, 159, 164, 167-174, 178-181, 186-197, 213-214, 219, 224, 227-229, 233-239 /usr/lib/python3/dist-packages/keystoneclient/auth/identity/v3/__init__.py 5 0 100% /usr/lib/python3/dist-packages/keystoneclient/auth/identity/v3/base.py 107 68 36% 59-68, 73, 78, 83, 91-105, 130-132, 135-197, 217-222, 227, 261-263 /usr/lib/python3/dist-packages/keystoneclient/auth/identity/v3/federated.py 35 17 51% 46-48, 52-65, 70-79, 82, 106-116 /usr/lib/python3/dist-packages/keystoneclient/auth/identity/v3/password.py 29 16 45% 39-51, 78-89, 93-96 /usr/lib/python3/dist-packages/keystoneclient/auth/identity/v3/token.py 17 6 65% 30-31, 53, 57-65 /usr/lib/python3/dist-packages/keystoneclient/base.py 274 195 29% 38-49, 58-61, 66, 72-86, 103-104, 116-119, 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187-208, 255-294, 315-316, 323, 326-329, 332, 335, 338-346, 351-362, 372-374, 381, 384-387, 390-393, 396, 399-412, 417-427 /usr/lib/python3/dist-packages/keystoneclient/session.py 348 276 21% 48-58, 62, 66-82, 139-164, 169-178, 182-222, 225-255, 337-445, 460-519, 527, 535, 543, 551, 559, 567, 589-593, 597-607, 618-632, 635-641, 658-660, 686, 701-703, 737-757, 767-769, 785-787, 803-805, 834-837, 882-885, 901-909, 917-943, 961-967, 979-1018 /usr/lib/python3/dist-packages/keystoneclient/utils.py 56 41 27% 27-46, 50-52, 60-71, 80-91, 111-118, 122-123 /usr/lib/python3/dist-packages/keystoneclient/v2_0/__init__.py 2 0 100% /usr/lib/python3/dist-packages/keystoneclient/v2_0/certificates.py 9 5 44% 19, 28-29, 38-40 /usr/lib/python3/dist-packages/keystoneclient/v2_0/client.py 53 33 38% 150-176, 193-219 /usr/lib/python3/dist-packages/keystoneclient/v2_0/ec2.py 17 7 59% 22, 25, 36-38, 46, 54, 59 /usr/lib/python3/dist-packages/keystoneclient/v2_0/endpoints.py 13 5 62% 24, 34, 39-44, 48 /usr/lib/python3/dist-packages/keystoneclient/v2_0/extensions.py 8 2 75% 21, 31 /usr/lib/python3/dist-packages/keystoneclient/v2_0/roles.py 42 29 31% 25, 28, 37, 41-42, 46, 50, 53-59, 67-75, 83-91 /usr/lib/python3/dist-packages/keystoneclient/v2_0/services.py 15 6 60% 25, 35, 39, 43-46, 50 /usr/lib/python3/dist-packages/keystoneclient/v2_0/tenants.py 76 54 29% 37, 40, 44-58, 61, 66, 71, 80-82, 85, 89-98, 110-130, 135-149, 153, 157, 161, 167 /usr/lib/python3/dist-packages/keystoneclient/v2_0/tokens.py 58 36 38% 24, 28, 32, 36, 44-69, 72, 75, 85, 94-96, 108-115, 124-125 /usr/lib/python3/dist-packages/keystoneclient/v2_0/users.py 51 32 37% 27, 30, 33, 42-43, 46, 55-57, 61-63, 68-70, 75-78, 87-91, 97-102, 106, 113-126, 130 /usr/lib/python3/dist-packages/keystoneclient/v3/__init__.py 2 0 100% /usr/lib/python3/dist-packages/keystoneclient/v3/access_rules.py 29 14 52% 58-61, 73-76, 87-90, 104-107, 111, 116 /usr/lib/python3/dist-packages/keystoneclient/v3/application_credentials.py 49 32 35% 72-98, 121-124, 136-139, 150-153, 166-169, 173 /usr/lib/python3/dist-packages/keystoneclient/v3/auth.py 22 10 55% 42-48, 60-66 /usr/lib/python3/dist-packages/keystoneclient/v3/client.py 104 64 38% 218-267, 270, 277-286, 313-352 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/__init__.py 1 0 100% /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/endpoint_filter.py 82 62 24% 34-47, 50-64, 68-73, 77-82, 86-91, 95-99, 106-110, 117-122, 126-131, 135-140, 144-149, 156-160 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/endpoint_policy.py 59 39 34% 28-38, 42, 47, 52, 56-66, 70, 75, 80, 85-97, 102, 108, 114, 125-134, 146-153 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/federation/__init__.py 1 0 100% /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/federation/base.py 19 8 58% 30, 33-40 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/federation/core.py 16 7 56% 24-31 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/federation/domains.py 5 0 100% /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/federation/identity_providers.py 22 8 64% 36-38, 54, 69, 82, 96, 109 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/federation/mappings.py 22 8 64% 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 11 45% 22-31, 36-38, 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 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/oauth1/utils.py 14 10 29% 28-38 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/simple_cert.py 11 6 45% 21-22, 31-33, 42-44 /usr/lib/python3/dist-packages/keystoneclient/v3/contrib/trusts.py 33 17 48% 59-74, 85, 90-92, 98, 102 /usr/lib/python3/dist-packages/keystoneclient/v3/credentials.py 17 5 71% 62, 80, 93, 119, 138 /usr/lib/python3/dist-packages/keystoneclient/v3/domain_configs.py 28 13 54% 37, 63-65, 78-79, 105-107, 121-122, 125, 129 /usr/lib/python3/dist-packages/keystoneclient/v3/domains.py 19 7 63% 54, 70, 85-87, 105, 122 /usr/lib/python3/dist-packages/keystoneclient/v3/ec2.py 15 6 60% 30, 51, 68-69, 81, 97 /usr/lib/python3/dist-packages/keystoneclient/v3/endpoint_groups.py 20 6 70% 54, 72, 86, 99, 117, 135 /usr/lib/python3/dist-packages/keystoneclient/v3/endpoints.py 28 12 57% 50-53, 75-76, 94, 119-120, 149-150, 169 /usr/lib/python3/dist-packages/keystoneclient/v3/groups.py 27 15 44% 31-44, 68, 87-91, 106, 122, 138 /usr/lib/python3/dist-packages/keystoneclient/v3/limits.py 21 9 57% 61-73, 93, 115, 133, 150 /usr/lib/python3/dist-packages/keystoneclient/v3/policies.py 24 12 50% 31-42, 64, 79, 92, 108, 124 /usr/lib/python3/dist-packages/keystoneclient/v3/projects.py 106 76 28% 41-55, 58, 61, 64, 67, 70, 73, 105-108, 136-157, 161-164, 168-171, 201-222, 225-227, 246, 264, 274, 283-285, 298-302, 311, 323-326, 337-345 /usr/lib/python3/dist-packages/keystoneclient/v3/regions.py 20 5 75% 61, 75, 87, 112, 129 /usr/lib/python3/dist-packages/keystoneclient/v3/registered_limits.py 22 10 55% 61-72, 99, 120, 140, 157-158 /usr/lib/python3/dist-packages/keystoneclient/v3/role_assignments.py 69 48 30% 40-42, 45-47, 50-52, 55-57, 60-62, 95-124, 127, 131, 135, 139, 143, 147 /usr/lib/python3/dist-packages/keystoneclient/v3/roles.py 149 101 32% 61-92, 95-113, 116-121, 137-141, 156, 190-203, 217, 235, 275-284, 327-336, 377-386, 395, 401, 407, 413, 419, 430-433, 456-458, 481-482, 501-503, 521-523, 543-544, 559, 562, 566, 570 /usr/lib/python3/dist-packages/keystoneclient/v3/services.py 23 11 52% 57-58, 75, 89-90, 111-112, 130-134 /usr/lib/python3/dist-packages/keystoneclient/v3/tokens.py 37 28 24% 18-21, 28, 37-39, 54-58, 78-94, 116-121 /usr/lib/python3/dist-packages/keystoneclient/v3/users.py 57 34 40% 43-45, 82-92, 126-132, 148, 187-197, 213-226, 240-243, 259-262, 278-281, 295 /usr/lib/python3/dist-packages/netaddr/__init__.py 19 1 95% 16 /usr/lib/python3/dist-packages/netaddr/compat.py 60 37 38% 39, 50-53, 56-59, 62-113 /usr/lib/python3/dist-packages/netaddr/contrib/__init__.py 1 0 100% /usr/lib/python3/dist-packages/netaddr/contrib/subnet_splitter.py 17 11 35% 23, 27-38, 42, 46 /usr/lib/python3/dist-packages/netaddr/core.py 73 40 45% 61-74, 89, 112-113, 122-124, 136, 145-149, 158-161, 169-170, 184-196, 199-200, 203, 206 /usr/lib/python3/dist-packages/netaddr/eui/__init__.py 361 276 24% 24, 28, 32, 37-39, 44, 52, 72-101, 104-109, 112-117, 121, 125, 129-152, 157, 169, 173-174, 181, 202-216, 230-268, 271-276, 279-284, 288, 292, 296-308, 312, 316-318, 327, 357-390, 394, 401-413, 416, 419-450, 456, 459-468, 477-480, 485-488, 492, 500-501, 506, 515-525, 529-548, 552, 559-564, 571-576, 583-588, 595-600, 607-612, 619-624, 633, 638, 643, 652, 663-671, 685-687, 699-700, 710, 718-722, 726, 730 /usr/lib/python3/dist-packages/netaddr/ip/__init__.py 822 596 27% 33-38, 47, 54, 60, 69-72, 81-84, 93-96, 105-108, 117-120, 129-132, 136, 140-143, 151-154, 162-174, 181-184, 191-199, 206, 213, 222-223, 228, 262-266, 275, 278, 285-293, 305, 316-319, 323, 330-339, 348-371, 377-378, 384-385, 396-400, 411-415, 426-429, 442-445, 456-459, 468, 472, 480, 485-487, 492, 500, 508, 513, 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32-42, 49-61 /usr/lib/python3/dist-packages/netaddr/ip/sets.py 350 300 14% 27-53, 65-81, 105-122, 126, 133, 145-210, 216-217, 226, 238-245, 249, 257, 263, 281-296, 317-350, 361, 371-372, 376-378, 392-413, 417, 426-429, 438-441, 450-453, 462-465, 476-479, 488-494, 505-507, 518-551, 566-619, 631-673, 683-688, 696, 700, 711-718, 729-735, 744-748 /usr/lib/python3/dist-packages/netaddr/strategy/__init__.py 113 90 20% 44-56, 70-83, 97-106, 121-138, 154-160, 177-194, 207-226, 238-257, 270-273 /usr/lib/python3/dist-packages/netaddr/strategy/eui48.py 135 70 48% 144-152, 163-197, 209-216, 226, 237-245, 249-251, 255-257, 261-263, 267-269, 273-275, 279-281, 286-288, 292, 296 /usr/lib/python3/dist-packages/netaddr/strategy/eui64.py 122 66 46% 121-124, 133-139, 149-176, 187-192, 202-203, 214-222, 226-228, 232-234, 238-240, 244-246, 250-252, 256-258, 263-265, 269, 273 /usr/lib/python3/dist-packages/netaddr/strategy/ipv4.py 103 51 50% 16, 91-107, 121, 141-148, 158-161, 171, 182, 186, 196-199, 212-214, 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/usr/lib/python3/dist-packages/oslo_i18n/_message.py 95 71 25% 59-69, 94-104, 115-132, 137-179, 194-215, 221-227, 238-251, 254-259, 262-264, 267 /usr/lib/python3/dist-packages/oslo_i18n/_translate.py 17 13 24% 39-49, 67-73 /usr/lib/python3/dist-packages/oslo_log/__init__.py 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 53 35% 85-181, 201, 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 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/usr/lib/python3/dist-packages/simplejson/scanner.py 64 53 17% 9-10, 21-83 /usr/lib/python3/dist-packages/six.py 491 239 51% 49-72, 98-99, 112, 120-121, 131-133, 145, 154-157, 192-193, 222-223, 308, 488, 496, 501-507, 519-525, 530-532, 538-540, 545, 550, 554-568, 583, 586, 589, 592, 600-616, 628, 631, 645-647, 653-673, 679, 683, 687, 691, 698-721, 737-738, 743-795, 797-804, 814-834, 845-861, 870-873, 893-898, 912-918, 932-937, 948-955, 976-977 /usr/lib/python3/dist-packages/stevedore/__init__.py 9 0 100% /usr/lib/python3/dist-packages/stevedore/driver.py 29 17 41% 51-53, 66, 100-105, 108-118, 139-141, 147-148 /usr/lib/python3/dist-packages/stevedore/enabled.py 13 7 46% 64-65, 77-84 /usr/lib/python3/dist-packages/stevedore/exception.py 3 0 100% /usr/lib/python3/dist-packages/stevedore/extension.py 104 71 32% 46-49, 58, 99-107, 141-146, 150-152, 155-156, 160-165, 176-179, 183, 187-214, 220-230, 237, 259-265, 269, 290, 294-301, 309, 317, 326, 331 /usr/lib/python3/dist-packages/stevedore/hook.py 11 6 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 959 847 12% 53-63, 71-72, 75-76, 86-89, 128-135, 146-156, 160-190, 194-222, 230-232, 236-245, 250-260, 275-276, 279, 282, 285-288, 291, 294, 320-328, 331-368, 401-441, 445-450, 454, 458-472, 481, 485-521, 524-526, 531-532, 536-567, 573-574, 584-661, 683-745, 749-753, 765-768, 794-839, 857-875, 896-921, 952-1008, 1027-1048, 1068-1092, 1111-1133, 1155-1180, 1210-1242, 1262-1285, 1329-1400, 1420-1439, 1465-1503, 1529-1557, 1568-1578, 1641-1672, 1675-1679, 1682-1691, 1694-1702, 1712, 1721-1727, 1730-1791, 1795, 1804, 1812, 1818, 1827, 1836, 1842, 1848, 1855, 1861-1878, 1885-1906, 1914, 1920, 1927, 1933-1944, 1947-1950 /usr/lib/python3/dist-packages/swiftclient/exceptions.py 51 45 12% 25-36, 40-43, 48-81 /usr/lib/python3/dist-packages/swiftclient/utils.py 229 178 22% 41, 51-68, 100-197, 201-205, 209-216, 220-239, 248-253, 258, 261, 264, 285-287, 290, 298-307, 310, 313, 332-339, 342, 345, 348, 351-363, 367-369, 373-378, 382-387, 391-392, 396-397, 401-405, 410-416, 419, 424-427 /usr/lib/python3/dist-packages/swiftclient/version.py 6 3 50% 24-28 /usr/lib/python3/dist-packages/urllib3/__init__.py 33 8 76% 56-62, 86 /usr/lib/python3/dist-packages/urllib3/_collections.py 187 137 27% 5-6, 9-16, 47-51, 55-58, 61-73, 76-80, 83-84, 87, 92-99, 102-103, 141-149, 152-153, 156-157, 160, 163, 166-170, 175, 178-179, 184, 188-189, 198-206, 209-212, 223-228, 235-256, 261-268, 275-286, 297, 300-305, 308-310, 314-317, 321-323, 326, 334-354 /usr/lib/python3/dist-packages/urllib3/connection.py 173 116 33% 17-21, 27-30, 105-115, 134, 144, 151-175, 178-184, 187-188, 192-199, 206-234, 256-266, 297-310, 314-402, 409-420, 428 /usr/lib/python3/dist-packages/urllib3/connectionpool.py 318 257 19% 75-80, 83, 86, 89-91, 97, 182-215, 221-236, 250-275, 291-303, 309, 313, 317-325, 330-348, 369-451, 454, 460-472, 479-493, 601-854, 904-927, 935-947, 954-955, 961-991, 997-1004, 1035-1040, 1048-1058 /usr/lib/python3/dist-packages/urllib3/contrib/__init__.py 0 0 100% /usr/lib/python3/dist-packages/urllib3/contrib/_appengine_environ.py 11 1 91% 36 /usr/lib/python3/dist-packages/urllib3/contrib/socks.py 75 66 12% 55-210 /usr/lib/python3/dist-packages/urllib3/exceptions.py 96 21 78% 21-22, 26, 33-34, 38, 79-83, 90-92, 147-150, 222, 225, 241-242, 249-250 /usr/lib/python3/dist-packages/urllib3/fields.py 90 70 22% 18-20, 38-61, 82-91, 113-118, 150-156, 176-192, 205, 218-227, 233-246, 263-273 /usr/lib/python3/dist-packages/urllib3/filepost.py 43 30 30% 19-22, 33-42, 57-60, 74-98 /usr/lib/python3/dist-packages/urllib3/packages/__init__.py 8 2 75% 10-11 /usr/lib/python3/dist-packages/urllib3/packages/ssl_match_hostname/__init__.py 11 6 45% 7, 10-16 /usr/lib/python3/dist-packages/urllib3/poolmanager.py 172 132 23% 89-114, 160-167, 170, 173-175, 187-202, 211, 224-234, 243-247, 257-271, 284-285, 297-307, 318-372, 411-431, 434-439, 448-456, 460-469, 473 /usr/lib/python3/dist-packages/urllib3/request.py 39 28 28% 42, 54, 70-79, 88-97, 144-171 /usr/lib/python3/dist-packages/urllib3/response.py 399 322 19% 34-36, 39, 42-61, 73-74, 77, 80-98, 103-118, 131, 134, 137-139, 143-152, 190, 214-258, 268-271, 274-278, 283-287, 291, 294, 302, 308-354, 362-373, 377, 383-399, 406-410, 421-467, 490-541, 559-567, 578-599, 603, 606, 610, 614-621, 625-634, 637-642, 648-653, 657, 661-666, 675, 680-689, 692-711, 727-781, 789-792, 795-809 /usr/lib/python3/dist-packages/urllib3/util/__init__.py 10 0 100% /usr/lib/python3/dist-packages/urllib3/util/connection.py 66 45 32% 17-26, 51-86, 90-94, 102-105, 118, 130-131 /usr/lib/python3/dist-packages/urllib3/util/queue.py 14 5 64% 7, 12, 15, 18, 21 /usr/lib/python3/dist-packages/urllib3/util/request.py 50 25 50% 13, 63, 65, 71, 74, 77, 80, 85, 95-105, 119-133 /usr/lib/python3/dist-packages/urllib3/util/response.py 35 29 17% 15-35, 54-71, 83-86 /usr/lib/python3/dist-packages/urllib3/util/retry.py 150 102 32% 186-187, 202-218, 223-232, 240-249, 253-265, 270-275, 278-283, 286-289, 300-305, 311, 317, 323-326, 335-341, 350-355, 376-442, 445 /usr/lib/python3/dist-packages/urllib3/util/ssl_.py 148 112 24% 31-34, 43-44, 50-56, 61-63, 104-149, 162-174, 192-201, 208-217, 256-293, 327-383, 393-396, 401-407 /usr/lib/python3/dist-packages/urllib3/util/timeout.py 63 42 33% 96-99, 102, 120-153, 169, 183, 191-194, 204-208, 220-226, 245-258 /usr/lib/python3/dist-packages/urllib3/util/url.py 205 152 26% 101-105, 112, 117-122, 127-129, 150-169, 172, 193-207, 214-241, 246-271, 275-299, 303-317, 322-327, 352-416, 431-432 /usr/lib/python3/dist-packages/urllib3/util/wait.py 76 58 24% 8-9, 43-68, 72-87, 91-107, 111, 118-124, 133-139, 146, 153 /usr/local/lib/python3.8/dist-packages/MySQLdb/__init__.py 46 13 72% 21, 36-37, 44-46, 63, 66, 69, 72, 75-76, 79 /usr/local/lib/python3.8/dist-packages/MySQLdb/_exceptions.py 12 0 100% /usr/local/lib/python3.8/dist-packages/MySQLdb/compat.py 12 5 58% 4-8 /usr/local/lib/python3.8/dist-packages/MySQLdb/connections.py 146 34 77% 42, 138, 140, 143, 150, 161, 197, 204, 245, 249, 260, 262, 265, 269, 282, 286-293, 304-308, 314-317, 324-328 /usr/local/lib/python3.8/dist-packages/MySQLdb/constants/CLIENT.py 18 0 100% /usr/local/lib/python3.8/dist-packages/MySQLdb/constants/FIELD_TYPE.py 29 0 100% /usr/local/lib/python3.8/dist-packages/MySQLdb/constants/FLAG.py 16 0 100% /usr/local/lib/python3.8/dist-packages/MySQLdb/constants/__init__.py 1 0 100% /usr/local/lib/python3.8/dist-packages/MySQLdb/converters.py 35 13 63% 47-48, 52, 56, 63-68, 79, 82, 85 /usr/local/lib/python3.8/dist-packages/MySQLdb/cursors.py 261 96 63% 83-90, 93, 96-97, 107, 109, 114-120, 127, 135, 142-144, 160, 171, 187, 194-206, 227, 239-240, 259-260, 296-310, 328, 358-363, 368-372, 378, 391-400, 403-405, 417, 421-426, 431-434, 438-441, 444, 447-450 /usr/local/lib/python3.8/dist-packages/MySQLdb/release.py 3 0 100% /usr/local/lib/python3.8/dist-packages/MySQLdb/times.py 76 49 36% 21, 25, 29, 34-37, 43-47, 53, 60-64, 75-76, 79-99, 102-113, 116-123, 127, 131 /usr/local/lib/python3.8/dist-packages/appdirs.py 257 211 18% 29-39, 77-97, 131-163, 195-203, 236-254, 291-300, 302-304, 310, 345-353, 388-404, 411-415, 419, 424, 429, 434, 439, 444, 449, 460-476, 480-503, 507-530, 533-556, 559-571, 577-608 /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, 519-525, 536-582, 592-595, 598-601, 606-611, 617-622, 625-629, 636-645, 658-690, 696, 703-738, 741-744, 747-753, 764-806, 825, 828-834, 837-845, 856-874, 885-896, 908-910, 913-924, 935-955, 967-982, 1007-1033, 1037-1054, 1059-1098 /usr/local/lib/python3.8/dist-packages/boto/auth_handler.py 10 2 80% 52, 60 /usr/local/lib/python3.8/dist-packages/boto/cacerts/__init__.py 0 0 100% /usr/local/lib/python3.8/dist-packages/boto/compat.py 47 26 45% 28-29, 35-36, 45-47, 68-102 /usr/local/lib/python3.8/dist-packages/boto/connection.py 605 493 19% 79-80, 84-85, 123, 131, 138, 146-158, 173-181, 189-190, 197-199, 234-238, 243-246, 249, 255, 264-269, 276-280, 290-300, 341-358, 361, 367-384, 390-391, 402-413, 474-572, 575, 578, 581, 587, 591, 594, 598, 602, 608, 614, 622-642, 645-662, 665-698, 701-705, 708-721, 724-778, 781, 784-851, 854-855, 858-859, 863-874, 877-881, 884, 897-1033, 1037-1059, 1066-1070, 1077-1078, 1091, 1103, 1106, 1109-1116, 1119-1122, 1158-1162, 1168-1186, 1190-1208, 1211-1227 /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/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/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/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 2 80% 9-10 /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 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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 56 26% 28-31, 35-36, 40-44, 48-57, 74, 77, 81, 85, 96-124, 136-156 /usr/local/lib/python3.8/dist-packages/joblib/memory.py 374 296 21% 57-63, 92-100, 105-141, 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, 352, 355, 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, 872-907, 914-921, 949-962, 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/pooch/__init__.py 20 14 30% 36-50 /usr/local/lib/python3.8/dist-packages/pooch/_version.py 4 0 100% /usr/local/lib/python3.8/dist-packages/pooch/core.py 120 84 30% 197-230, 410, 413, 424, 545-568, 575-576, 589-590, 610-637, 658-673, 702-711, 725-733 /usr/local/lib/python3.8/dist-packages/pooch/downloaders.py 82 69 16% 14-15, 47-60, 139-143, 161-203, 253-261, 277-310 /usr/local/lib/python3.8/dist-packages/pooch/processors.py 75 50 33% 38, 64-81, 88, 117-133, 162-182, 213, 240-252, 262-279 /usr/local/lib/python3.8/dist-packages/pooch/utils.py 101 54 47% 33, 96, 150, 173-193, 214-216, 246, 248, 255-256, 261-271, 308-315, 346-362, 386-393, 430-436 /usr/local/lib/python3.8/dist-packages/pooch/version.py 4 0 100% /usr/local/lib/python3.8/dist-packages/pyparsing.py 3062 1772 42% 122-123, 127-128, 134-137, 141-145, 149-150, 191-194, 233-266, 274-278, 295-296, 307-308, 321, 329-336, 339-346, 349, 354-359, 361, 410-453, 487, 490, 498, 500, 563, 567, 576, 580, 588-591, 606-611, 616-634, 650, 653-656, 659, 662, 675-694, 738-754, 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4863, 4936, 4942-4986, 5016, 5019-5029, 5032, 5035-5036, 5039-5043, 5046-5053, 5056-5073, 5076-5081, 5084-5092, 5131-5135, 5138-5145, 5213-5234, 5263, 5270-5271, 5273-5277, 5279, 5306-5324, 5346, 5373-5384, 5387-5393, 5410-5423, 5440-5452, 5494-5547, 5586, 5617-5628, 5634, 5661-5662, 5708-5709, 5715-5718, 5733, 5748, 5787, 5792-5793, 5811-5812, 5818-5819, 5873, 5931-5943, 5981-5982, 6060-6115, 6192-6229, 6312-6355, 6365, 6622-6627, 6647-6652, 6680, 6705-6713, 6734-6740, 6745, 6750, 6755, 6760, 6886, 6889-6902, 6906-6921, 6924, 6927, 6940-6943, 6952-6955, 6964-6967, 6981-7028, 7034-7035, 7040-7105 /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 166 118 29% 19-24, 42-60, 90-100, 111-126, 134-136, 164, 167-170, 186-196, 235-253, 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 177 113 36% 43-65, 75-76, 87-92, 106-114, 119-121, 127, 132-142, 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/constants/__init__.py 13 0 100% /usr/local/lib/python3.8/dist-packages/scipy/constants/codata.py 97 15 85% 1566, 1616-1617, 1641-1642, 1692-1704, 1725 /usr/local/lib/python3.8/dist-packages/scipy/constants/constants.py 142 21 85% 220-246, 278, 307 /usr/local/lib/python3.8/dist-packages/scipy/fft/__init__.py 27 2 93% 112-113 /usr/local/lib/python3.8/dist-packages/scipy/fft/_backend.py 33 13 61% 19-23, 36-37, 40, 90-91, 122-123, 151-152 /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/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 385 358 7% 27-37, 137-258, 330-359, 433-472, 568-596, 669-702, 706-711, 862-907, 950-983, 1034-1043, 1157-1246, 1304-1318, 1373-1391, 1451-1470, 1575-1619 /usr/local/lib/python3.8/dist-packages/scipy/linalg/blas.py 86 18 79% 296-310, 341, 352, 362, 377, 381-384, 387 /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 74 16% 109-139, 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 14 69% 776, 805-814, 823-832 /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 32 24% 141-181, 190-194 /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 36 16% 41-52, 60-68, 72-84, 88-92 /usr/local/lib/python3.8/dist-packages/scipy/ndimage/filters.py 399 336 16% 51, 79-96, 129-133, 140-164, 212-217, 288-303, 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 403 373 7% 50-53, 106-122, 207-213, 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 455 345 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, 1219 /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 633 560 12% 132-165, 170-172, 176-178, 182-183, 187, 192-195, 200-220, 224-240, 244-259, 263-269, 273-286, 290-292, 296-310, 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, 1714-1733, 1991-2094, 2149-2212, 2254-2302, 2330-2359, 2378-2380, 2399-2409, 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, 888, 926-928, 941-943, 956-958, 971-973, 988, 1032-1034, 1072-1093, 1129-1150, 1201-1226, 1284-1307, 1343-1360, 1373-1380, 1424-1431, 1449-1460, 1476-1487, 1535-1538, 1586-1589, 1624-1639, 1666-1676, 1703-1713, 1740-1749, 1762-1764, 1777-1779, 1792-1794, 1800-1802, 1815-1817, 1830-1832, 1845-1847, 1860-1862, 1878-1880, 1904-1911, 1928-1935, 1984-1996, 2035-2050, 2065-2070, 2120-2158, 2195-2215, 2260-2270, 2333-2336 /usr/local/lib/python3.8/dist-packages/scipy/special/_ellip_harm.py 16 6 62% 97, 155-156, 160, 208-209 /usr/local/lib/python3.8/dist-packages/scipy/special/_logsumexp.py 34 28 18% 94-129, 215 /usr/local/lib/python3.8/dist-packages/scipy/special/_spherical_bessel.py 18 12 33% 53-56, 104-107, 153-156, 202-205 /usr/local/lib/python3.8/dist-packages/scipy/special/lambertw.py 4 1 75% 107 /usr/local/lib/python3.8/dist-packages/scipy/special/orthogonal.py 525 464 12% 128-151, 154-157, 160-173, 191-216, 264-290, 331-346, 394-404, 442-457, 503-524, 569-586, 630, 662-676, 744-760, 789-796, 825-831, 860-871, 898-910, 947-1020, 1050-1067, 1113-1124, 1157-1172, 1229-1248, 1282-1297, 1345-1364, 1400-1408, 1455-1463, 1499-1512, 1557-1566, 1603-1608, 1652-1659, 1696-1714, 1758-1765, 1802-1821, 1865-1866, 1894-1902, 1945-1952, 1980-1985, 2029-2039, 2080-2094, 2137-2143, 2170-2182 /usr/local/lib/python3.8/dist-packages/scipy/special/sf_error.py 6 0 100% /usr/local/lib/python3.8/dist-packages/scipy/special/spfun_stats.py 14 8 43% 86-95 /usr/local/lib/python3.8/dist-packages/scipy/stats/__init__.py 13 0 100% /usr/local/lib/python3.8/dist-packages/scipy/stats/_binned_statistic.py 159 145 9% 167-182, 336-349, 514-634, 640-675, 681-706 /usr/local/lib/python3.8/dist-packages/scipy/stats/_constants.py 8 0 100% /usr/local/lib/python3.8/dist-packages/scipy/stats/_continuous_distns.py 2994 1970 34% 35-36, 50-54, 97, 100, 103, 106, 109, 152, 155, 158, 161, 164, 180, 184, 188, 192, 196, 200, 204, 208, 235, 239, 242, 245, 248, 251, 254, 257, 260, 263, 266, 273-300, 342, 345, 348, 351, 354, 382, 385, 388, 391, 394, 422, 425, 428, 431-435, 438, 449, 461-463, 470-472, 482-486, 514, 520, 523-525, 528, 531, 534-539, 542-553, 563-658, 690-693, 697, 700, 703, 706-724, 754, 757, 760, 763-775, 778-779, 834-840, 843-852, 855, 858, 861, 864, 867, 870-887, 890-894, 948, 951, 954, 957, 960, 963, 969, 972-973, 1011, 1014, 1017, 1021, 1024, 1027, 1030, 1033, 1036, 1039, 1068, 1071, 1074, 1077, 1080, 1083, 1086, 1090-1091, 1130-1131, 1137, 1140-1141, 1144, 1147, 1150-1155, 1187, 1191, 1194, 1197, 1200, 1203, 1206, 1209-1213, 1242, 1245, 1248, 1251, 1281-1284, 1288-1289, 1292-1293, 1296-1297, 1300-1301, 1304-1305, 1308-1309, 1338-1341, 1345-1347, 1350-1351, 1354-1355, 1358-1360, 1363, 1369, 1401, 1405, 1408, 1411, 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6127-6139, 6142-6146, 6178, 6181, 6184, 6187, 6190, 6193, 6199, 6234, 6238, 6241, 6272, 6275, 6278, 6281, 6323, 6326, 6329, 6332, 6335, 6338-6339, 6370, 6374, 6377, 6380, 6383, 6386, 6389, 6392, 6395-6396, 6402, 6458, 6461, 6465, 6468, 6471, 6474, 6477, 6480, 6517, 6521-6523, 6526, 6529, 6538, 6541-6544, 6579, 6582, 6585-6588, 6591, 6629, 6632, 6635, 6638, 6643-6645, 6648, 6651, 6684, 6687, 6690-6700, 6703, 6706-6710, 6713-6725, 6754, 6757-6759, 6768, 6778-6783, 6812, 6815, 6823-6832, 6835-6844, 6847, 6850, 6856, 6885, 6888, 6892, 6895, 6898, 6901, 6906-6913, 6916-6917, 6933, 6939-6946, 6950-6967, 6972-6973, 6978-6981, 6986-7004, 7010-7013, 7018-7037, 7042-7045, 7050-7063, 7069-7072, 7077-7114, 7139, 7142, 7145, 7148, 7151, 7154, 7157, 7160, 7163, 7166-7185, 7189-7213, 7244, 7247-7250, 7253, 7256, 7259, 7262-7264, 7272, 7293, 7296, 7299, 7302, 7305, 7308, 7383-7455, 7493, 7497, 7500, 7503, 7506, 7538, 7542, 7545, 7548, 7551, 7580, 7584, 7587-7604, 7607-7610, 7613, 7655, 7658, 7661-7663, 7666-7668, 7671, 7674, 7677-7678, 7681, 7728, 7731, 7734, 7737, 7740, 7743, 7746, 7799-7809, 7815-7824, 7830-7841, 7844-7861, 7867-7885, 7893, 7904, 7952-7953, 7959, 7965, 8053-8070, 8076, 8082, 8088, 8092-8093, 8097-8101, 8107-8109 /usr/local/lib/python3.8/dist-packages/scipy/stats/_discrete_distns.py 446 296 34% 43, 46, 49, 52-54, 58, 61-63, 66-67, 70-73, 76-84, 87-89, 119, 122, 126, 129, 134, 137, 140, 143, 146, 149, 193-194, 197, 200, 203-205, 208, 211-230, 263, 266, 270, 273-274, 277-278, 282-283, 286-289, 292-298, 331, 334, 337, 340, 343-344, 347, 350-351, 354-356, 359-364, 433, 436, 439-441, 444-449, 454, 459-471, 474-476, 483-489, 492-501, 504-513, 545, 548, 552, 555-567, 598, 601, 604-605, 609, 612-613, 616-617, 620-623, 626-631, 666, 669, 672-673, 676, 679-680, 683-686, 690-691, 694-698, 701-702, 731, 734, 739-740, 743-744, 747-751, 754-764, 794, 797, 801-802, 805-806, 809-812, 815-821, 825-836, 839, 871, 874, 878-879, 882, 915, 918-921, 924-929, 932-935, 938, 976-977, 981-985, 988-992, 995-999, 1040-1043, 1046, 1049, 1052, 1055, 1058, 1061, 1064-1077 /usr/local/lib/python3.8/dist-packages/scipy/stats/_distn_infrastructure.py 1393 1036 26% 42, 361-363, 367-395, 402-406, 413-417, 424-432, 436, 440, 443, 446, 449, 452, 455, 458, 461-463, 466, 469, 472-474, 477, 480, 483, 486, 489, 492, 495, 498, 501, 508-512, 516, 541-545, 567-571, 575, 579, 607, 611, 614, 617-620, 640-649, 665, 668, 671, 679, 733-734, 742-751, 768, 771, 778, 785-788, 801-859, 871-874, 895, 898-899, 902-903, 912-914, 917-918, 921, 924-925, 928, 931, 961-995, 1024-1110, 1135-1146, 1165-1192, 1219, 1241-1245, 1267-1271, 1293-1295, 1321-1328, 1349-1351, 1362-1368, 1612, 1621, 1629, 1643-1651, 1654, 1657-1678, 1683, 1686-1687, 1692, 1695, 1698, 1702, 1705-1706, 1709, 1736-1752, 1778-1795, 1819-1837, 1861-1880, 1904-1922, 1949-1968, 1992-2014, 2038-2060, 2063, 2066-2072, 2082-2089, 2092-2102, 2109-2114, 2118-2121, 2132-2176, 2276-2314, 2336-2380, 2402-2412, 2415-2438, 2516-2540, 2546-2550, 2554-2609, 2663-2676, 2822, 2851, 2878, 2885, 2893, 2912-2921, 2924, 2927, 2930, 2933-2935, 2938-2939, 2968-2969, 2991-3006, 3028-3044, 3066-3084, 3106-3125, 3147-3164, 3189-3207, 3229-3248, 3270-3294, 3297-3301, 3356-3386, 3394-3428, 3449-3463, 3475-3517, 3532, 3535, 3539-3541, 3544-3546, 3551-3557, 3560, 3563-3564, 3593-3602 /usr/local/lib/python3.8/dist-packages/scipy/stats/_distr_params.py 2 0 100% /usr/local/lib/python3.8/dist-packages/scipy/stats/_hypotests.py 43 36 16% 80-132 /usr/local/lib/python3.8/dist-packages/scipy/stats/_multivariate.py 972 690 29% 50-53, 81-88, 108, 156-173, 177-179, 203, 207, 210-213, 223, 227, 361, 373-426, 434-444, 469-471, 493-497, 519-523, 550-555, 587-594, 626-633, 657-661, 681-683, 733-741, 744-747, 750, 753, 756-759, 762, 774-776, 938, 948-1005, 1013-1019, 1050-1055, 1078-1085, 1107, 1131-1142, 1175-1179, 1182-1186, 1189, 1192, 1227-1233, 1237-1277, 1299, 1412, 1429-1430, 1448-1452, 1470-1474, 1490-1493, 1510-1514, 1531-1539, 1559-1561, 1569-1570, 1573, 1576, 1579, 1582, 1585, 1588, 1739, 1742-1768, 1775-1805, 1808-1819, 1851-1864, 1887-1894, 1917, 1933, 1948-1950, 1966-1970, 1988-1990, 2006-2010, 2025-2027, 2051-2072, 2098-2118, 2142-2150, 2169, 2197-2199, 2223-2225, 2250-2253, 2256-2260, 2263, 2266-2267, 2270-2271, 2274-2275, 2278-2281, 2284, 2325-2357, 2471, 2495-2515, 2538-2542, 2566, 2582-2586, 2605-2607, 2623, 2639-2641, 2657-2664, 2682-2684, 2708-2733, 2757-2769, 2773, 2798-2812, 2815-2818, 2821, 2824-2825, 2828-2829, 2832-2833, 2836-2841, 2845, 3002, 3011-3023, 3032-3047, 3050-3058, 3061, 3082-3094, 3115, 3130-3132, 3147-3156, 3182-3196, 3218-3220, 3244-3251, 3254, 3257, 3260, 3263, 3266, 3269, 3348, 3355-3359, 3378-3401, 3430-3431, 3434, 3495-3499, 3518-3538, 3601-3615, 3631-3648, 3657-3689, 3718-3730, 3787-3791, 3810-3824 /usr/local/lib/python3.8/dist-packages/scipy/stats/_rvs_sampling.py 33 28 15% 123-169 /usr/local/lib/python3.8/dist-packages/scipy/stats/_stats_mstats_common.py 107 98 8% 93-144, 232-266, 271-285, 374-404 /usr/local/lib/python3.8/dist-packages/scipy/stats/_tukeylambda_stats.py 54 40 26% 68-102, 164-201 /usr/local/lib/python3.8/dist-packages/scipy/stats/contingency.py 36 28 22% 57-62, 99-109, 243-275 /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, 2116-2118, 2195-2199, 2258-2281, 2336-2346, 2408-2419, 2465-2468, 2567-2594, 2727-2764, 2858-2882, 2893-2942, 2961-2986, 3051-3062, 3105-3124, 3156-3177, 3228-3247, 3323-3353, 3360-3363, 3370-3373, 3496-3557, 3624-3719, 3821-3877, 3967-3968, 4059-4169, 4307-4347, 4357-4360, 4363-4369, 4412-4430, 4434, 4640-4713, 4743-4773, 4792-4817, 4842-4869, 4891-4895, 4966-4985, 4990-4994, 4999-5004, 5008-5017, 5021-5024, 5131-5138, 5237-5266, 5333-5367, 5487-5528, 5549-5560, 5721-5763, 5877, 5916-5962, 5989-5998, 6047-6084, 6183-6282, 6323-6328, 6387-6429, 6467-6478, 6550-6601, 6644-6670, 6754-6815, 6890-6927, 7008, 7090, 7138-7177, 7202-7221, 7264, 7290-7291, 7316-7321, 7377-7407 /usr/local/lib/python3.8/dist-packages/scipy/version.py 7 1 86% 10 /usr/local/lib/python3.8/dist-packages/skimage/__init__.py 28 9 68% 93-100, 114, 121-122 /usr/local/lib/python3.8/dist-packages/skimage/_shared/__init__.py 0 0 100% /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/utils.py 123 96 22% 42-45, 48-68, 90-99, 102-115, 135-137, 141-172, 179, 231-246, 251-253, 270-278, 298-304, 330-337, 361-375 /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/data/__init__.py 114 53 54% 98, 143-164, 196-204, 219, 241-244, 264-265, 278, 300, 366, 414, 426-429, 484, 503, 518, 549, 574, 585, 613, 627, 641, 657, 674, 694, 712, 731, 755, 782, 799, 810, 833, 890-892, 926 /usr/local/lib/python3.8/dist-packages/skimage/data/_binary_blobs.py 12 10 17% 47-57 /usr/local/lib/python3.8/dist-packages/skimage/data/_registry.py 4 0 100% /usr/local/lib/python3.8/dist-packages/skimage/measure/__init__.py 15 0 100% /usr/local/lib/python3.8/dist-packages/skimage/measure/_find_contours.py 60 11 82% 118, 121, 124, 126, 128-133, 139, 155 /usr/local/lib/python3.8/dist-packages/skimage/measure/_label.py 3 1 67% 93 /usr/local/lib/python3.8/dist-packages/skimage/measure/_marching_cubes_classic.py 52 44 15% 103-109, 118-152, 188-194, 257-301 /usr/local/lib/python3.8/dist-packages/skimage/measure/_marching_cubes_lewiner.py 70 56 20% 126-143, 260-265, 277-338, 342-346, 363-388 /usr/local/lib/python3.8/dist-packages/skimage/measure/_marching_cubes_lewiner_luts.py 48 0 100% /usr/local/lib/python3.8/dist-packages/skimage/measure/_moments.py 73 60 18% 45, 111-146, 191, 241-250, 296-305, 348, 372-376, 406-428, 461-469 /usr/local/lib/python3.8/dist-packages/skimage/measure/_polygon.py 61 21 66% 32, 134-168 /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/skimage/measure/_regionprops.py 304 167 45% 118-124, 132-135, 147-161, 166, 176, 181, 185, 190, 195-196, 200-201, 207-210, 214-217, 221-224, 228, 232, 237-238, 243, 248-249, 254, 260-262, 265, 269-270, 275, 279, 283, 287-288, 292-293, 298-299, 304-306, 311, 316, 321-328, 333, 337, 341-342, 347-348, 354, 359-360, 366, 371, 374-390, 393-397, 400-411, 499-525, 624-640, 852-896, 935-962 /usr/local/lib/python3.8/dist-packages/skimage/measure/_structural_similarity.py 8 2 75% 10-13 /usr/local/lib/python3.8/dist-packages/skimage/measure/block.py 18 15 17% 62-86 /usr/local/lib/python3.8/dist-packages/skimage/measure/entropy.py 5 2 60% 39-40 /usr/local/lib/python3.8/dist-packages/skimage/measure/fit.py 230 204 11% 9-10, 14-15, 20, 26, 81-100, 120-131, 156-171, 193-194, 216-217, 270-294, 313-320, 339-346, 414-482, 501-544, 564-577, 598-617, 785-876 /usr/local/lib/python3.8/dist-packages/skimage/measure/pnpoly.py 5 2 60% 29, 53 /usr/local/lib/python3.8/dist-packages/skimage/measure/profile.py 35 29 17% 95-127, 154-174 /usr/local/lib/python3.8/dist-packages/skimage/measure/simple_metrics.py 18 6 67% 13-16, 37-40, 61-64 /usr/local/lib/python3.8/dist-packages/skimage/metrics/__init__.py 6 0 100% /usr/local/lib/python3.8/dist-packages/skimage/metrics/_adapted_rand_error.py 19 15 21% 49-76 /usr/local/lib/python3.8/dist-packages/skimage/metrics/_contingency_table.py 15 11 27% 30-40 /usr/local/lib/python3.8/dist-packages/skimage/metrics/_structural_similarity.py 100 92 8% 89-232 /usr/local/lib/python3.8/dist-packages/skimage/metrics/_variation_of_information.py 33 24 27% 43-46, 64-71, 92-117, 133-136 /usr/local/lib/python3.8/dist-packages/skimage/metrics/simple_metrics.py 40 32 20% 15-18, 42-44, 92-105, 139-160 /usr/local/lib/python3.8/dist-packages/skimage/util/__init__.py 19 2 89% 22-25 /usr/local/lib/python3.8/dist-packages/skimage/util/_invert.py 14 11 21% 62-74 /usr/local/lib/python3.8/dist-packages/skimage/util/_map_array.py 70 56 20% 26-58, 107-110, 114, 122-126, 130, 133, 136-153, 156, 159-180, 183-187 /usr/local/lib/python3.8/dist-packages/skimage/util/_montage.py 32 29 9% 90-142 /usr/local/lib/python3.8/dist-packages/skimage/util/_regular_grid.py 27 24 11% 61-83, 112-116 /usr/local/lib/python3.8/dist-packages/skimage/util/apply_parallel.py 50 46 8% 23-44, 48-52, 109-147 /usr/local/lib/python3.8/dist-packages/skimage/util/arraycrop.py 17 14 18% 45-63 /usr/local/lib/python3.8/dist-packages/skimage/util/compare.py 25 21 16% 36-60 /usr/local/lib/python3.8/dist-packages/skimage/util/dtype.py 142 122 14% 51-54, 77, 98-101, 126-173, 224-349, 375, 401, 430, 454, 479, 503, 527 /usr/local/lib/python3.8/dist-packages/skimage/util/lookfor.py 4 1 75% 24 /usr/local/lib/python3.8/dist-packages/skimage/util/noise.py 54 50 7% 87-192 /usr/local/lib/python3.8/dist-packages/skimage/util/shape.py 48 41 15% 74-95, 209-248 /usr/local/lib/python3.8/dist-packages/skimage/util/unique.py 9 7 22% 39-50 /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 ---------------------------------------------------------------------------------------------------------------------------------------- TOTAL 214710 164117 24% ret : 34304 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 48.94user 14.60system 1:49.37elapsed 58%CPU (0avgtext+0avgdata 3363592maxresident)k 3391944inputs+34568outputs (9187major+2136990minor)pagefaults 0swaps