python /home/admin/mtr/script_for_cron.py -j python_test3 -m 12 -a ' --short_python3 -v ' -s python_test3 -M 0 -S 0 -U 100,100,120
 import MySQLdb succeeded 
Import error (python version)
python version = 3
warning , we can't find thcl infos in json_data
warning , we can't find pdt infos in json_data
 list_job_run_as_list :  ['mask_detection', 'datou', 'CacheModelData_queries', 'CachePhotoData_queries', 'test_fork', 'prepare_maskdata', 'portfolio_queries', 'sla_mensuel']
python version used : 3
 liste_fichiers : [('tests/mask_test', True, 'Test mask-detection ', 'mask_detection'), ('tests/datou_test', True, 'Datou All Test', 'datou', 'all'), ('mtr/database_queries/CacheModelData_queries', True, 'Test Cache Model Data', 'CacheModelData_queries'), ('tests/cache_photo_data_test', True, 'Test local_cache_photo ', 'CachePhotoData_queries'), ('mtr/mask_rcnn/prepare_maskdata', True, 'test prepare mask data', 'prepare_maskdata', 'all'), ('mtr/database_queries/portfolio_queries', True, 'test portfolio queries', 'portfolio_queries'), ('prod/memo/memo', True, 'SLA Mensuel', 'sla_mensuel', 'all')]


#&_# BEGIN OF TEST : tests/mask_test #&_# 


/home/admin/workarea/git/Velours/python/tests/mask_test.py
<module 'tests.mask_test' from '/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 : 358

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 : 0.12140941619873047
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
Sun May 11 00:35:28 2025
VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next
VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case
VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec 
VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec
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 : 358
wait 20 seconds
l 3637 free memory gpu now : 358  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
2025-05-11 00:35:51.171635: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2025-05-11 00:35:51.199286: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz
2025-05-11 00:35:51.200953: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fc7b8000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2025-05-11 00:35:51.201021: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2025-05-11 00:35:51.203652: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2025-05-11 00:35:51.426918: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2a315cf0 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2025-05-11 00:35:51.426969: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5
2025-05-11 00:35:51.427846: 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
2025-05-11 00:35:51.428270: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-11 00:35:51.435028: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-11 00:35:51.437371: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-11 00:35:51.437748: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-11 00:35:51.440364: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-11 00:35:51.441593: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-11 00:35:51.446128: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-11 00:35:51.447010: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-11 00:35:51.447111: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-11 00:35:51.447559: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2025-05-11 00:35:51.447575: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2025-05-11 00:35:51.447584: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 
2025-05-11 00:35:51.448297: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 206 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
2025-05-11 00:35:51.987176: 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
2025-05-11 00:35:51.987254: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-11 00:35:51.987275: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-11 00:35:51.987293: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-11 00:35:51.987311: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-11 00:35:51.987329: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-11 00:35:51.987359: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-11 00:35:51.987378: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-11 00:35:51.988178: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-11 00:35:51.989064: 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
2025-05-11 00:35:51.989103: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-11 00:35:51.989125: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-11 00:35:51.989145: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-11 00:35:51.989191: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-11 00:35:51.989215: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-11 00:35:51.989236: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-11 00:35:51.989257: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-11 00:35:51.990049: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-11 00:35:51.990082: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2025-05-11 00:35:51.990092: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2025-05-11 00:35:51.990102: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 
2025-05-11 00:35:51.991014: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 206 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5)
2025-05-11 00:35:52.808265: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 32.00M (33554432 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:35:52.808811: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 28.80M (30199040 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:35:52.809267: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 25.92M (27179264 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:35:52.809737: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 23.33M (24461568 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:35:52.810231: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 21.00M (22015488 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:35:52.960363: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 64.00M (67108864 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:35:52.960909: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 64.00M (67108864 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:02.962033: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 64.00M (67108864 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:02.962882: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 64.00M (67108864 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:02.962953: W tensorflow/core/common_runtime/bfc_allocator.cc:434] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.25MiB (rounded to 2359296)
Current allocation summary follows.
2025-05-11 00:36:02.962981: I tensorflow/core/common_runtime/bfc_allocator.cc:934] BFCAllocator dump for GPU_0_bfc
2025-05-11 00:36:02.963000: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (256): 	Total Chunks: 59, Chunks in use: 59. 14.8KiB allocated for chunks. 14.8KiB in use in bin. 8.8KiB client-requested in use in bin.
2025-05-11 00:36:02.963016: 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.
2025-05-11 00:36:02.963031: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1024): 	Total Chunks: 96, Chunks in use: 96. 96.2KiB allocated for chunks. 96.2KiB in use in bin. 96.0KiB client-requested in use in bin.
2025-05-11 00:36:02.963046: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2048): 	Total Chunks: 25, Chunks in use: 25. 50.0KiB allocated for chunks. 50.0KiB in use in bin. 50.0KiB client-requested in use in bin.
2025-05-11 00:36:02.963062: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (4096): 	Total Chunks: 40, Chunks in use: 40. 165.5KiB allocated for chunks. 165.5KiB in use in bin. 160.0KiB client-requested in use in bin.
2025-05-11 00:36:02.963076: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (8192): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2025-05-11 00:36:02.963091: 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.
2025-05-11 00:36:02.963106: 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.
2025-05-11 00:36:02.963121: 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.
2025-05-11 00:36:02.963136: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (131072): 	Total Chunks: 5, Chunks in use: 4. 769.0KiB allocated for chunks. 560.0KiB in use in bin. 560.0KiB client-requested in use in bin.
2025-05-11 00:36:02.963151: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (262144): 	Total Chunks: 8, Chunks in use: 7. 2.16MiB allocated for chunks. 1.91MiB in use in bin. 1.75MiB client-requested in use in bin.
2025-05-11 00:36:02.963165: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (524288): 	Total Chunks: 8, Chunks in use: 6. 4.95MiB allocated for chunks. 3.44MiB in use in bin. 3.25MiB client-requested in use in bin.
2025-05-11 00:36:02.963181: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1048576): 	Total Chunks: 16, Chunks in use: 14. 17.62MiB allocated for chunks. 15.38MiB in use in bin. 14.00MiB client-requested in use in bin.
2025-05-11 00:36:02.963195: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2097152): 	Total Chunks: 10, Chunks in use: 10. 23.65MiB allocated for chunks. 23.65MiB in use in bin. 22.25MiB client-requested in use in bin.
2025-05-11 00:36:02.963209: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (4194304): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2025-05-11 00:36:02.963222: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (8388608): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2025-05-11 00:36:02.963235: 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.
2025-05-11 00:36:02.963257: 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.
2025-05-11 00:36:02.963271: 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.
2025-05-11 00:36:02.963284: 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.
2025-05-11 00:36:02.963297: 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.
2025-05-11 00:36:02.963311: I tensorflow/core/common_runtime/bfc_allocator.cc:957] Bin for 2.25MiB was 2.00MiB, Chunk State: 
2025-05-11 00:36:02.963323: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 19814144
2025-05-11 00:36:02.963341: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ce000000 of size 2359296 next 245
2025-05-11 00:36:02.963353: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ce240000 of size 1048576 next 269
2025-05-11 00:36:02.963365: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc5ce340000 of size 1310720 next 263
2025-05-11 00:36:02.963377: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ce480000 of size 2359296 next 262
2025-05-11 00:36:02.963389: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ce6c0000 of size 1048576 next 287
2025-05-11 00:36:02.963401: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ce7c0000 of size 1310720 next 281
2025-05-11 00:36:02.963412: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ce900000 of size 2359296 next 280
2025-05-11 00:36:02.963424: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ceb40000 of size 1048576 next 304
2025-05-11 00:36:02.963435: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5cec40000 of size 1310720 next 298
2025-05-11 00:36:02.963447: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ced80000 of size 2359296 next 297
2025-05-11 00:36:02.963459: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5cefc0000 of size 3299072 next 18446744073709551615
2025-05-11 00:36:02.963471: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 16777216
2025-05-11 00:36:02.963482: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d0000000 of size 2359296 next 181
2025-05-11 00:36:02.963494: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d0240000 of size 2097152 next 196
2025-05-11 00:36:02.963505: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d0440000 of size 1048576 next 216
2025-05-11 00:36:02.963517: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d0540000 of size 1310720 next 209
2025-05-11 00:36:02.963529: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d0680000 of size 2359296 next 208
2025-05-11 00:36:02.963540: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d08c0000 of size 1048576 next 234
2025-05-11 00:36:02.963552: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d09c0000 of size 1310720 next 228
2025-05-11 00:36:02.963563: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d0b00000 of size 2359296 next 227
2025-05-11 00:36:02.963575: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d0d40000 of size 2883584 next 18446744073709551615
2025-05-11 00:36:02.963586: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 2097152
2025-05-11 00:36:02.963598: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2600000 of size 147456 next 55
2025-05-11 00:36:02.963619: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2624000 of size 65536 next 78
2025-05-11 00:36:02.963631: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2634000 of size 4096 next 191
2025-05-11 00:36:02.963643: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2635000 of size 4096 next 192
2025-05-11 00:36:02.963654: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2636000 of size 4096 next 193
2025-05-11 00:36:02.963666: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2637000 of size 256 next 194
2025-05-11 00:36:02.963678: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2637100 of size 256 next 195
2025-05-11 00:36:02.963689: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2637200 of size 4096 next 197
2025-05-11 00:36:02.963701: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2638200 of size 4096 next 198
2025-05-11 00:36:02.963712: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2639200 of size 4096 next 199
2025-05-11 00:36:02.963724: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263a200 of size 4096 next 200
2025-05-11 00:36:02.963735: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263b200 of size 4096 next 201
2025-05-11 00:36:02.963747: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263c200 of size 1024 next 202
2025-05-11 00:36:02.963759: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263c600 of size 1024 next 204
2025-05-11 00:36:02.963770: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263ca00 of size 1024 next 205
2025-05-11 00:36:02.963782: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263ce00 of size 1024 next 206
2025-05-11 00:36:02.963793: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263d200 of size 1024 next 207
2025-05-11 00:36:02.963805: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263d600 of size 1024 next 210
2025-05-11 00:36:02.963816: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263da00 of size 1024 next 211
2025-05-11 00:36:02.963828: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263de00 of size 1024 next 212
2025-05-11 00:36:02.963839: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263e200 of size 1024 next 213
2025-05-11 00:36:02.963851: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263e600 of size 1024 next 214
2025-05-11 00:36:02.963862: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263ea00 of size 4096 next 215
2025-05-11 00:36:02.963874: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d263fa00 of size 4096 next 217
2025-05-11 00:36:02.963885: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2640a00 of size 4096 next 218
2025-05-11 00:36:02.963897: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2641a00 of size 4096 next 219
2025-05-11 00:36:02.963908: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2642a00 of size 4096 next 220
2025-05-11 00:36:02.963920: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2643a00 of size 1024 next 221
2025-05-11 00:36:02.963931: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2643e00 of size 1024 next 223
2025-05-11 00:36:02.963943: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2644200 of size 1024 next 224
2025-05-11 00:36:02.963954: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2644600 of size 1024 next 225
2025-05-11 00:36:02.963966: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2644a00 of size 1024 next 226
2025-05-11 00:36:02.963977: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2644e00 of size 1024 next 229
2025-05-11 00:36:02.963997: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2645200 of size 1024 next 230
2025-05-11 00:36:02.964009: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2645600 of size 1024 next 231
2025-05-11 00:36:02.964021: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2645a00 of size 1024 next 232
2025-05-11 00:36:02.964032: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2645e00 of size 1024 next 233
2025-05-11 00:36:02.964044: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2646200 of size 7680 next 72
2025-05-11 00:36:02.964056: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2648000 of size 147456 next 71
2025-05-11 00:36:02.964067: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d266c000 of size 131072 next 87
2025-05-11 00:36:02.964079: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d268c000 of size 4096 next 289
2025-05-11 00:36:02.964091: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d268d000 of size 4096 next 290
2025-05-11 00:36:02.964102: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d268e000 of size 4096 next 291
2025-05-11 00:36:02.964114: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d268f000 of size 1024 next 292
2025-05-11 00:36:02.964125: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d268f400 of size 1024 next 293
2025-05-11 00:36:02.964137: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d268f800 of size 1024 next 294
2025-05-11 00:36:02.964148: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d268fc00 of size 1024 next 295
2025-05-11 00:36:02.964160: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2690000 of size 1024 next 296
2025-05-11 00:36:02.964171: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2690400 of size 1024 next 299
2025-05-11 00:36:02.964183: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2690800 of size 1024 next 300
2025-05-11 00:36:02.964194: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2690c00 of size 1024 next 301
2025-05-11 00:36:02.964206: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2691000 of size 1024 next 302
2025-05-11 00:36:02.964217: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2691400 of size 1024 next 303
2025-05-11 00:36:02.964229: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2691800 of size 4096 next 305
2025-05-11 00:36:02.964240: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2692800 of size 4096 next 306
2025-05-11 00:36:02.964252: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2693800 of size 4096 next 307
2025-05-11 00:36:02.964263: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2694800 of size 4096 next 308
2025-05-11 00:36:02.964275: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2695800 of size 4096 next 309
2025-05-11 00:36:02.964286: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2696800 of size 1024 next 310
2025-05-11 00:36:02.964298: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2696c00 of size 1024 next 311
2025-05-11 00:36:02.964309: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2697000 of size 1024 next 312
2025-05-11 00:36:02.964321: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2697400 of size 1024 next 313
2025-05-11 00:36:02.964332: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2697800 of size 1024 next 314
2025-05-11 00:36:02.964344: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc5d2697c00 of size 214016 next 103
2025-05-11 00:36:02.964356: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d26cc000 of size 262144 next 102
2025-05-11 00:36:02.964367: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc5d270c000 of size 999424 next 18446744073709551615
2025-05-11 00:36:02.964386: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 4194304
2025-05-11 00:36:02.964399: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2800000 of size 589824 next 96
2025-05-11 00:36:02.964410: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2890000 of size 262144 next 117
2025-05-11 00:36:02.964422: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc5d28d0000 of size 262144 next 112
2025-05-11 00:36:02.964434: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2910000 of size 524288 next 111
2025-05-11 00:36:02.964445: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2990000 of size 262144 next 135
2025-05-11 00:36:02.964458: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d29d0000 of size 327680 next 124
2025-05-11 00:36:02.964469: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2a20000 of size 589824 next 123
2025-05-11 00:36:02.964481: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2ab0000 of size 262144 next 152
2025-05-11 00:36:02.964492: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2af0000 of size 327680 next 142
2025-05-11 00:36:02.964504: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2b40000 of size 786432 next 18446744073709551615
2025-05-11 00:36:02.964515: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 8388608
2025-05-11 00:36:02.964527: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc5d2c00000 of size 589824 next 160
2025-05-11 00:36:02.964539: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2c90000 of size 589824 next 158
2025-05-11 00:36:02.964551: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2d20000 of size 524288 next 171
2025-05-11 00:36:02.964562: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc5d2da0000 of size 1048576 next 222
2025-05-11 00:36:02.964574: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2ea0000 of size 1048576 next 190
2025-05-11 00:36:02.964585: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d2fa0000 of size 1048576 next 189
2025-05-11 00:36:02.964597: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d30a0000 of size 1048576 next 203
2025-05-11 00:36:02.964608: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d31a0000 of size 1048576 next 251
2025-05-11 00:36:02.964620: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5d32a0000 of size 1441792 next 18446744073709551615
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2025-05-11 00:36:02.966403: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e29300 of size 1024 next 183
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2025-05-11 00:36:02.966437: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e29f00 of size 256 next 187
2025-05-11 00:36:02.966448: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e2a000 of size 256 next 188
2025-05-11 00:36:02.966460: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e2a100 of size 4096 next 186
2025-05-11 00:36:02.966471: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e2b100 of size 4096 next 42
2025-05-11 00:36:02.966482: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e2c100 of size 65536 next 36
2025-05-11 00:36:02.966494: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e3c100 of size 65536 next 35
2025-05-11 00:36:02.966505: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e4c100 of size 4096 next 235
2025-05-11 00:36:02.966516: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e4d100 of size 4096 next 236
2025-05-11 00:36:02.966528: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e4e100 of size 4096 next 237
2025-05-11 00:36:02.966539: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e4f100 of size 4096 next 238
2025-05-11 00:36:02.966550: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e50100 of size 1024 next 239
2025-05-11 00:36:02.966561: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e50500 of size 1024 next 240
2025-05-11 00:36:02.966573: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e50900 of size 1024 next 241
2025-05-11 00:36:02.966584: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e50d00 of size 1024 next 242
2025-05-11 00:36:02.966595: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e51100 of size 1024 next 243
2025-05-11 00:36:02.966607: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e51500 of size 1024 next 246
2025-05-11 00:36:02.966618: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e51900 of size 1024 next 247
2025-05-11 00:36:02.966630: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e51d00 of size 1024 next 248
2025-05-11 00:36:02.966641: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e52100 of size 1024 next 249
2025-05-11 00:36:02.966660: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e52500 of size 1024 next 250
2025-05-11 00:36:02.966672: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e52900 of size 4096 next 252
2025-05-11 00:36:02.966684: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e53900 of size 4096 next 253
2025-05-11 00:36:02.966695: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e54900 of size 4096 next 254
2025-05-11 00:36:02.966706: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e55900 of size 4096 next 255
2025-05-11 00:36:02.966718: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e56900 of size 4096 next 256
2025-05-11 00:36:02.966729: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e57900 of size 1024 next 257
2025-05-11 00:36:02.966740: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e57d00 of size 1024 next 258
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2025-05-11 00:36:02.966797: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e59100 of size 1024 next 265
2025-05-11 00:36:02.966808: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e59500 of size 1024 next 266
2025-05-11 00:36:02.966819: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e59900 of size 1024 next 267
2025-05-11 00:36:02.966831: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e59d00 of size 1024 next 268
2025-05-11 00:36:02.966842: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e5a100 of size 4096 next 270
2025-05-11 00:36:02.966853: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e5b100 of size 4096 next 271
2025-05-11 00:36:02.966865: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e5c100 of size 4096 next 272
2025-05-11 00:36:02.966876: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e5d100 of size 4096 next 273
2025-05-11 00:36:02.966887: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e5e100 of size 4096 next 274
2025-05-11 00:36:02.966908: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e5f100 of size 1024 next 275
2025-05-11 00:36:02.966922: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e5f500 of size 1024 next 276
2025-05-11 00:36:02.966933: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e5f900 of size 1024 next 277
2025-05-11 00:36:02.966945: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e5fd00 of size 1024 next 278
2025-05-11 00:36:02.966957: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e60100 of size 1024 next 279
2025-05-11 00:36:02.966968: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e60500 of size 1024 next 282
2025-05-11 00:36:02.966979: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e60900 of size 1024 next 283
2025-05-11 00:36:02.966991: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e60d00 of size 1024 next 284
2025-05-11 00:36:02.967003: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e61100 of size 1024 next 285
2025-05-11 00:36:02.967014: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e61500 of size 1024 next 286
2025-05-11 00:36:02.967025: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e61900 of size 4096 next 288
2025-05-11 00:36:02.967045: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e62900 of size 6144 next 27
2025-05-11 00:36:02.967057: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e64100 of size 147456 next 26
2025-05-11 00:36:02.967069: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e88100 of size 65536 next 47
2025-05-11 00:36:02.967080: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e98100 of size 65536 next 59
2025-05-11 00:36:02.967091: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712ea8100 of size 65536 next 65
2025-05-11 00:36:02.967103: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712eb8100 of size 294656 next 18446744073709551615
2025-05-11 00:36:02.967114: I tensorflow/core/common_runtime/bfc_allocator.cc:995]      Summary of in-use Chunks by size: 
2025-05-11 00:36:02.967129: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 59 Chunks of size 256 totalling 14.8KiB
2025-05-11 00:36:02.967143: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 40 Chunks of size 512 totalling 20.0KiB
2025-05-11 00:36:02.967156: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 95 Chunks of size 1024 totalling 95.0KiB
2025-05-11 00:36:02.967168: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1280 totalling 1.2KiB
2025-05-11 00:36:02.967181: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 25 Chunks of size 2048 totalling 50.0KiB
2025-05-11 00:36:02.967194: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 38 Chunks of size 4096 totalling 152.0KiB
2025-05-11 00:36:02.967207: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 6144 totalling 6.0KiB
2025-05-11 00:36:02.967219: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 7680 totalling 7.5KiB
2025-05-11 00:36:02.967232: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 16384 totalling 16.0KiB
2025-05-11 00:36:02.967245: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 37632 totalling 36.8KiB
2025-05-11 00:36:02.967258: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 6 Chunks of size 65536 totalling 384.0KiB
2025-05-11 00:36:02.967271: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 131072 totalling 128.0KiB
2025-05-11 00:36:02.967284: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 3 Chunks of size 147456 totalling 432.0KiB
2025-05-11 00:36:02.967296: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 4 Chunks of size 262144 totalling 1.00MiB
2025-05-11 00:36:02.967309: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 294656 totalling 287.8KiB
2025-05-11 00:36:02.967322: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 327680 totalling 640.0KiB
2025-05-11 00:36:02.967335: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 524288 totalling 1.00MiB
2025-05-11 00:36:02.967347: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 3 Chunks of size 589824 totalling 1.69MiB
2025-05-11 00:36:02.967360: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 786432 totalling 768.0KiB
2025-05-11 00:36:02.967372: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 9 Chunks of size 1048576 totalling 9.00MiB
2025-05-11 00:36:02.967385: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 4 Chunks of size 1310720 totalling 5.00MiB
2025-05-11 00:36:02.967397: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1441792 totalling 1.38MiB
2025-05-11 00:36:02.967410: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 2097152 totalling 2.00MiB
2025-05-11 00:36:02.967422: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 7 Chunks of size 2359296 totalling 15.75MiB
2025-05-11 00:36:02.967435: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 2883584 totalling 2.75MiB
2025-05-11 00:36:02.967447: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 3299072 totalling 3.15MiB
2025-05-11 00:36:02.967468: I tensorflow/core/common_runtime/bfc_allocator.cc:1002] Sum Total of in-use chunks: 45.68MiB
2025-05-11 00:36:02.967480: I tensorflow/core/common_runtime/bfc_allocator.cc:1004] total_region_allocated_bytes_: 52320000 memory_limit_: 216924160 available bytes: 164604160 curr_region_allocation_bytes_: 67108864
2025-05-11 00:36:02.967496: I tensorflow/core/common_runtime/bfc_allocator.cc:1010] Stats: 
Limit:                   216924160
InUse:                    47895296
MaxInUse:                 47895552
NumAllocs:                    1015
MaxAllocSize:              4325376

2025-05-11 00:36:02.967518: W tensorflow/core/common_runtime/bfc_allocator.cc:439] *******__*************************************************************************_***_*************
2025-05-11 00:36:02.967572: W tensorflow/core/framework/op_kernel.cc:1753] OP_REQUIRES failed at cwise_ops_common.h:134 : Resource exhausted: OOM when allocating tensor with shape[3,3,256,256] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
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[3,3,256,256] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:Add]
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
free memory after detection : 
begin to check gpu status 
inside check gpu memory
l 3610 free memory gpu now : 19

############################### TEST detect object  ################################

run mask_detect

Inside batchDatouExec : verbose : False
Catched exception !
Connect or reconnect !
# 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 : 0.19201326370239258
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
Sun May 11 00:36:04 2025
VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next
VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case
VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec 
VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec
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 : 358
wait 20 seconds
l 3637 free memory gpu now : 358  max_wait_temp :  1 max_wait :  0
 gpu_flag :  0
2025-05-11 00:36:27.360759: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2025-05-11 00:36:27.387071: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz
2025-05-11 00:36:27.389299: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fc7b8000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2025-05-11 00:36:27.389360: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2025-05-11 00:36:27.393425: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2025-05-11 00:36:27.626826: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x29caad40 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2025-05-11 00:36:27.626870: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5
2025-05-11 00:36:27.627785: 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
2025-05-11 00:36:27.628197: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-11 00:36:27.631020: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-11 00:36:27.633584: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-11 00:36:27.634438: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-11 00:36:27.637445: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-11 00:36:27.638454: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-11 00:36:27.642584: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-11 00:36:27.643428: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-11 00:36:27.643492: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-11 00:36:27.643946: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2025-05-11 00:36:27.643961: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2025-05-11 00:36:27.643970: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 
2025-05-11 00:36:27.644760: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 206 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
2025-05-11 00:36:28.197911: 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
2025-05-11 00:36:28.198019: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-11 00:36:28.198049: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-11 00:36:28.198075: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-11 00:36:28.198099: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-11 00:36:28.198125: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-11 00:36:28.198151: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-11 00:36:28.198176: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-11 00:36:28.199081: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-11 00:36:28.200054: 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
2025-05-11 00:36:28.200089: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-11 00:36:28.200115: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-11 00:36:28.200140: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-11 00:36:28.200162: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-11 00:36:28.200187: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-11 00:36:28.200212: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-11 00:36:28.200238: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-11 00:36:28.201095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-11 00:36:28.201127: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2025-05-11 00:36:28.201139: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2025-05-11 00:36:28.201150: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 
2025-05-11 00:36:28.202095: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 206 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5)
2025-05-11 00:36:28.998797: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 32.00M (33554432 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:28.999349: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 28.80M (30199040 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:28.999845: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 25.92M (27179264 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:29.000338: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 23.33M (24461568 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:29.000829: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 21.00M (22015488 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:29.140769: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 64.00M (67108864 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:29.141387: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 64.00M (67108864 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:39.142389: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 64.00M (67108864 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:39.143235: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 64.00M (67108864 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-11 00:36:39.143270: W tensorflow/core/common_runtime/bfc_allocator.cc:434] Allocator (GPU_0_bfc) ran out of memory trying to allocate 2.25MiB (rounded to 2359296)
Current allocation summary follows.
2025-05-11 00:36:39.143293: I tensorflow/core/common_runtime/bfc_allocator.cc:934] BFCAllocator dump for GPU_0_bfc
2025-05-11 00:36:39.143311: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (256): 	Total Chunks: 59, Chunks in use: 59. 14.8KiB allocated for chunks. 14.8KiB in use in bin. 8.8KiB client-requested in use in bin.
2025-05-11 00:36:39.143327: 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.
2025-05-11 00:36:39.143342: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1024): 	Total Chunks: 96, Chunks in use: 96. 96.2KiB allocated for chunks. 96.2KiB in use in bin. 96.0KiB client-requested in use in bin.
2025-05-11 00:36:39.143357: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2048): 	Total Chunks: 25, Chunks in use: 25. 50.0KiB allocated for chunks. 50.0KiB in use in bin. 50.0KiB client-requested in use in bin.
2025-05-11 00:36:39.143372: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (4096): 	Total Chunks: 40, Chunks in use: 40. 165.5KiB allocated for chunks. 165.5KiB in use in bin. 160.0KiB client-requested in use in bin.
2025-05-11 00:36:39.143386: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (8192): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2025-05-11 00:36:39.143401: 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.
2025-05-11 00:36:39.143416: 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.
2025-05-11 00:36:39.143431: 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.
2025-05-11 00:36:39.143446: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (131072): 	Total Chunks: 5, Chunks in use: 4. 769.0KiB allocated for chunks. 560.0KiB in use in bin. 560.0KiB client-requested in use in bin.
2025-05-11 00:36:39.143460: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (262144): 	Total Chunks: 8, Chunks in use: 7. 2.16MiB allocated for chunks. 1.91MiB in use in bin. 1.75MiB client-requested in use in bin.
2025-05-11 00:36:39.143474: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (524288): 	Total Chunks: 8, Chunks in use: 6. 4.95MiB allocated for chunks. 3.44MiB in use in bin. 3.25MiB client-requested in use in bin.
2025-05-11 00:36:39.143490: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1048576): 	Total Chunks: 16, Chunks in use: 14. 17.62MiB allocated for chunks. 15.38MiB in use in bin. 14.00MiB client-requested in use in bin.
2025-05-11 00:36:39.143505: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2097152): 	Total Chunks: 10, Chunks in use: 10. 23.65MiB allocated for chunks. 23.65MiB in use in bin. 22.25MiB client-requested in use in bin.
2025-05-11 00:36:39.143543: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (4194304): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2025-05-11 00:36:39.143557: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (8388608): 	Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin.
2025-05-11 00:36:39.143570: 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.
2025-05-11 00:36:39.143583: 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.
2025-05-11 00:36:39.143595: 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.
2025-05-11 00:36:39.143608: 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.
2025-05-11 00:36:39.143621: 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.
2025-05-11 00:36:39.143635: I tensorflow/core/common_runtime/bfc_allocator.cc:957] Bin for 2.25MiB was 2.00MiB, Chunk State: 
2025-05-11 00:36:39.143647: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 19814144
2025-05-11 00:36:39.143662: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ce000000 of size 2359296 next 245
2025-05-11 00:36:39.143675: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ce240000 of size 1048576 next 269
2025-05-11 00:36:39.143686: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc5ce340000 of size 1310720 next 263
2025-05-11 00:36:39.143698: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ce480000 of size 2359296 next 262
2025-05-11 00:36:39.143709: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ce6c0000 of size 1048576 next 287
2025-05-11 00:36:39.143721: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5ce7c0000 of size 1310720 next 281
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2025-05-11 00:36:39.146775: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e2a100 of size 4096 next 186
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2025-05-11 00:36:39.146798: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e2c100 of size 65536 next 36
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2025-05-11 00:36:39.147318: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e60d00 of size 1024 next 284
2025-05-11 00:36:39.147330: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e61100 of size 1024 next 285
2025-05-11 00:36:39.147341: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e61500 of size 1024 next 286
2025-05-11 00:36:39.147353: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e61900 of size 4096 next 288
2025-05-11 00:36:39.147365: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e62900 of size 6144 next 27
2025-05-11 00:36:39.147376: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e64100 of size 147456 next 26
2025-05-11 00:36:39.147388: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e88100 of size 65536 next 47
2025-05-11 00:36:39.147399: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712e98100 of size 65536 next 59
2025-05-11 00:36:39.147411: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712ea8100 of size 65536 next 65
2025-05-11 00:36:39.147423: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc712eb8100 of size 294656 next 18446744073709551615
2025-05-11 00:36:39.147434: I tensorflow/core/common_runtime/bfc_allocator.cc:995]      Summary of in-use Chunks by size: 
2025-05-11 00:36:39.147449: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 59 Chunks of size 256 totalling 14.8KiB
2025-05-11 00:36:39.147463: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 40 Chunks of size 512 totalling 20.0KiB
2025-05-11 00:36:39.147476: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 95 Chunks of size 1024 totalling 95.0KiB
2025-05-11 00:36:39.147488: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1280 totalling 1.2KiB
2025-05-11 00:36:39.147501: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 25 Chunks of size 2048 totalling 50.0KiB
2025-05-11 00:36:39.147514: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 38 Chunks of size 4096 totalling 152.0KiB
2025-05-11 00:36:39.147527: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 6144 totalling 6.0KiB
2025-05-11 00:36:39.147540: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 7680 totalling 7.5KiB
2025-05-11 00:36:39.147552: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 16384 totalling 16.0KiB
2025-05-11 00:36:39.147565: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 37632 totalling 36.8KiB
2025-05-11 00:36:39.147578: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 6 Chunks of size 65536 totalling 384.0KiB
2025-05-11 00:36:39.147591: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 131072 totalling 128.0KiB
2025-05-11 00:36:39.147603: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 3 Chunks of size 147456 totalling 432.0KiB
2025-05-11 00:36:39.147616: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 4 Chunks of size 262144 totalling 1.00MiB
2025-05-11 00:36:39.147629: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 294656 totalling 287.8KiB
2025-05-11 00:36:39.147642: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 327680 totalling 640.0KiB
2025-05-11 00:36:39.147655: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 524288 totalling 1.00MiB
2025-05-11 00:36:39.147667: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 3 Chunks of size 589824 totalling 1.69MiB
2025-05-11 00:36:39.147680: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 786432 totalling 768.0KiB
2025-05-11 00:36:39.147693: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 9 Chunks of size 1048576 totalling 9.00MiB
2025-05-11 00:36:39.147705: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 4 Chunks of size 1310720 totalling 5.00MiB
2025-05-11 00:36:39.147725: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1441792 totalling 1.38MiB
2025-05-11 00:36:39.147738: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 2097152 totalling 2.00MiB
2025-05-11 00:36:39.147751: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 7 Chunks of size 2359296 totalling 15.75MiB
2025-05-11 00:36:39.147764: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 2883584 totalling 2.75MiB
2025-05-11 00:36:39.147776: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 3299072 totalling 3.15MiB
2025-05-11 00:36:39.147789: I tensorflow/core/common_runtime/bfc_allocator.cc:1002] Sum Total of in-use chunks: 45.68MiB
2025-05-11 00:36:39.147801: I tensorflow/core/common_runtime/bfc_allocator.cc:1004] total_region_allocated_bytes_: 52320000 memory_limit_: 216924160 available bytes: 164604160 curr_region_allocation_bytes_: 67108864
2025-05-11 00:36:39.147816: I tensorflow/core/common_runtime/bfc_allocator.cc:1010] Stats: 
Limit:                   216924160
InUse:                    47895296
MaxInUse:                 47895552
NumAllocs:                    1015
MaxAllocSize:              4325376

2025-05-11 00:36:39.147837: W tensorflow/core/common_runtime/bfc_allocator.cc:439] *******__*************************************************************************_***_*************
2025-05-11 00:36:39.147881: W tensorflow/core/framework/op_kernel.cc:1753] OP_REQUIRES failed at cwise_ops_common.h:134 : Resource exhausted: OOM when allocating tensor with shape[3,3,256,256] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
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[3,3,256,256] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:Add]
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"
/home/admin/workarea/git/Velours/python/tests/python_tests.py refs/heads/master_6b796098f0a7c88b7d6a90fb4c0df56eec821fbf
SQL :INSERT INTO MTRAdmin.monitor_sys (name, type, server, version_code, result_str, result_bool, lien , test_group ,test_name) VALUES ('python_test3','1','marlene','refs/heads/master_6b796098f0a7c88b7d6a90fb4c0df56eec821fbf','{"mask_detection": "fail"}','0','http://marlene.fotonower-preprod.com/job/2025/May/11052025/python_test3//data_2/data_log/job/2025/May/11052025/python_test3/log-python3----short_python3--v--marlene-00:35:01.txt','mask_detection','unknown');

#&_# END OF TEST #&_# : tests/mask_test #&_# 





#&_# BEGIN OF TEST : tests/datou_test #&_# 


/home/admin/workarea/git/Velours/python/tests/datou_test.py
<module 'tests.datou_test' from '/home/admin/workarea/git/Velours/python/tests/datou_test.py'>
Datou All Test
python version used : 3

############################### TEST sam  ################################
TEST SAM
Inside batchDatouExec : verbose : True
##### chargement datou
SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4573

SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output,
mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local
FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt
WHERE mtdt.`id`=mtd.`type`
AND mtd.mtd_id=4573
 
SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type
FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt
WHERE mtd.`type`=msid.`mtr_datou_step_type`
AND mtd.mtd_id= 4573
AND msid.data_type=mdsdt.id
                    

SELECT mts_id_output, id_output, mts_id_input, id_input 
FROM MTRDatou.mtr_datou_step_by_step 
WHERE mtd_id=4573
# 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 !
no param json to modify
List Step Type Loaded in datou : sam
list_input_json : []
##### fin chargement datou
##### chargement data
##### Call load_data_input : nb_thread : 5
origin

        SELECT photo_id, url
        FROM MTRBack.photos ph
        WHERE photo_id IN (1189321094) 
 Found this number of photos: 1
##### Call download_photos : nb_thread : 5
begin to download photo : 1189321094
download finish for photo 1189321094
we have missing 0 photos in the step downloads : 
photo missing : []
try to delete the photos missing in DB
##### After download_photos 
length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1
##### After load_data_input 
time to download the photos : 0.1951122283935547
#### fin chargement data
Blocking on flush ?
No conitnuing 
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 : True
number of steps :  1
step1:sam
Sun May 11 00:36:39 2025
VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next
VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case
VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec 
VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec
After prepare type args : <class 'list'>

Here we display some param of map_info ! 
map_filenames : {'temp/1746916599_1375741_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png': 1189321094}
map_photo_id_path_extension : {1189321094: {'path': 'temp/1746916599_1375741_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png', 'extension': 'png'}}
map_subphoto_mainphoto : {}

Beginning of datou step sam !
pht : 4677
Inside sam : nb paths : 1
ERROR in datou_step_exec, will save and exit !
CUDA error: out of memory
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
  File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2329, in datou_exec
    output = datou_step_exec(sNext, args, cache, context, map_info, verbose, mtr_user_id)
  File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2430, in datou_step_exec
    return lib_process.datou_step_sam(param, json_param, args, cache, context, map_info, verbose)
  File "/home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_process.py", line 367, in datou_step_sam
    sam.to(device=device)
  File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 927, in to
    return self._apply(convert)
  File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 579, in _apply
    module._apply(fn)
  File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 579, in _apply
    module._apply(fn)
  File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 579, in _apply
    module._apply(fn)
  File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 602, in _apply
    param_applied = fn(param)
  File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 925, in convert
    return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)

[1189321094]
 map_info['map_portfolio_photo'] : {}
 final :  True mtd_id 4573 list_pids : [1189321094]


begin to insert list_values into mtr_datou_result : 
length of list_values in save_final : 1
insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id
 list_values : [('4573', None, '1189321094', "[<FrameSummary file /home/admin/workarea/git/Velours/python/tests/python_tests.py, line 245 in <module>>, <FrameSummary file /home/admin/workarea/git/Velours/python/tests/datou_test.py, line 3680 in test>, <FrameSummary file /home/admin/workarea/git/Velours/python/tests/datou_test.py, line 100 in test_sam>, <FrameSummary file /home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py, line 819 in batchDatouExec>, <FrameSummary file /home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py, line 2346 in datou_exec>, 'CUDA error: out of memory\\nCUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.\\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1.']", '-1', '-1.0', '501120777', '1.0', None)]
time used for this insertion : 0.012538671493530273
 save_final 
ERROR in last step sam, CUDA error: out of memory
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.

time spend for datou_step_exec : 3.489168405532837
time spend to save output : 0.013740301132202148
total time spend for step 0 : 3.502908706665039
need to delete datou_research and reload, so keep current state 1
need to delete datou_research and reload, so keep current state 1
caffe_path_current : 
About to save ! 2
After save, about to update current !
 datou_cur_ids : []
 len(datou.list_steps) : 1
 output : None
ERROR
nb objects espect :  98
nb_objects detect : 0
ERROR sam FAILED

############################### TEST frcnn  ################################
test frcnn
Inside batchDatouExec : verbose : True
##### chargement datou
SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4184

SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output,
mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local
FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt
WHERE mtdt.`id`=mtd.`type`
AND mtd.mtd_id=4184
 
SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type
FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt
WHERE mtd.`type`=msid.`mtr_datou_step_type`
AND mtd.mtd_id= 4184
AND msid.data_type=mdsdt.id
                    

SELECT mts_id_output, id_output, mts_id_input, id_input 
FROM MTRDatou.mtr_datou_step_by_step 
WHERE mtd_id=4184
# 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 !
no param json to modify
List Step Type Loaded in datou : frcnn
list_input_json : []
##### fin chargement datou
##### chargement data
##### Call load_data_input : nb_thread : 5
origin

        SELECT photo_id, url
        FROM MTRBack.photos ph
        WHERE photo_id IN (917754606) 
 Found this number of photos: 1
##### Call download_photos : nb_thread : 5
begin to download photo : 917754606
download finish for photo 917754606
we have missing 0 photos in the step downloads : 
photo missing : []
try to delete the photos missing in DB
##### After download_photos 
length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1
##### After load_data_input 
time to download the photos : 0.10353732109069824
#### fin chargement data
Blocking on flush ?
No conitnuing 
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 : True
number of steps :  1
step1:frcnn
Sun May 11 00:36:43 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
After prepare type args : <class 'list'>

Here we display some param of map_info ! 
map_filenames : {'temp/1746916603_1375741_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg': 917754606}
map_photo_id_path_extension : {917754606: {'path': 'temp/1746916603_1375741_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg', 'extension': 'jpg'}}
map_subphoto_mainphoto : {}

Beginning of datou step Faster rcnn !
classes : ['background', 'plaque']
pht : 4370
caffemodel_name (should be vgg16_immat_307 but not used because net loaded outside in the fonction) : {'id': 3375, 'mtr_user_id': 31, 'name': 'detection_plaque_valcor_010622', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,plaque', 'svm_portfolios_learning': '0,0', 'photo_hashtag_type': 4370, 'photo_desc_type': 5676, 'type_classification': 'caffe_faster_rcnn', 'hashtag_id_list': '0,0'}
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
E0511 00:36:44.886025 1375741 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0511 00:36:44.891981 1375741 common.cpp:121] Cannot create Curand generator. Curand won't be available.
F0511 00:36:44.899353 1375741 syncedmem.hpp:22] Check failed: error == cudaSuccess (2 vs. 0)  out of memory
*** Check failure stack trace: ***
Command terminated by signal 6
6.53user 7.54system 1:19.11elapsed 17%CPU (0avgtext+0avgdata 1225796maxresident)k
1408072inputs+3416outputs (3443major+608735minor)pagefaults 0swaps