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 : 356

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 : 0.12474322319030762
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
Fri May  9 18:35:28 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 : 356
wait 20 seconds
l 3637 free memory gpu now : 356  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
2025-05-09 18:35:51.349563: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2025-05-09 18:35:51.375141: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz
2025-05-09 18:35:51.377111: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fc714000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2025-05-09 18:35:51.377192: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2025-05-09 18:35:51.381257: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2025-05-09 18:35:51.632686: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x27516a90 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2025-05-09 18:35:51.632773: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5
2025-05-09 18:35:51.634004: 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
2025-05-09 18:35:51.634963: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-09 18:35:51.639785: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-09 18:35:51.643494: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-09 18:35:51.643966: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-09 18:35:51.647023: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-09 18:35:51.648417: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-09 18:35:51.654254: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-09 18:35:51.655391: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-09 18:35:51.655494: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-09 18:35:51.656061: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2025-05-09 18:35:51.656081: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2025-05-09 18:35:51.656092: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 
2025-05-09 18:35:51.657006: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 204 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
2025-05-09 18:35:52.229862: 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
2025-05-09 18:35:52.229938: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-09 18:35:52.229959: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-09 18:35:52.229978: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-09 18:35:52.229996: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-09 18:35:52.230014: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-09 18:35:52.230044: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-09 18:35:52.230064: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-09 18:35:52.230883: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-09 18:35:52.231790: 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
2025-05-09 18:35:52.231833: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-09 18:35:52.231852: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-09 18:35:52.231870: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-09 18:35:52.231888: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-09 18:35:52.231906: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-09 18:35:52.231923: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-09 18:35:52.231941: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-09 18:35:52.232723: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-09 18:35:52.232754: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2025-05-09 18:35:52.232765: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2025-05-09 18:35:52.232774: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 
2025-05-09 18:35:52.233610: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 204 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5)
2025-05-09 18:35:53.135817: 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
2025-05-09 18:35:53.136401: 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
2025-05-09 18:35:53.136952: 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
2025-05-09 18:35:53.137482: 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
2025-05-09 18:35:53.137965: 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
2025-05-09 18:35:53.138475: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 18.90M (19814144 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-09 18:35:53.283839: 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
2025-05-09 18:35:53.284351: 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
2025-05-09 18:36:03.285438: 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
2025-05-09 18:36:03.286313: 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
2025-05-09 18:36:03.286349: 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.
2025-05-09 18:36:03.286376: I tensorflow/core/common_runtime/bfc_allocator.cc:934] BFCAllocator dump for GPU_0_bfc
2025-05-09 18:36:03.286395: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (256): 	Total Chunks: 60, Chunks in use: 60. 15.0KiB allocated for chunks. 15.0KiB in use in bin. 8.8KiB client-requested in use in bin.
2025-05-09 18:36:03.286410: 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.
2025-05-09 18:36:03.286426: 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.
2025-05-09 18:36:03.286440: 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.
2025-05-09 18:36:03.286456: 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.
2025-05-09 18:36:03.286470: 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.
2025-05-09 18:36:03.286485: 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.
2025-05-09 18:36:03.286500: 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.
2025-05-09 18:36:03.286515: 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.
2025-05-09 18:36:03.286530: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (131072): 	Total Chunks: 5, Chunks in use: 4. 768.8KiB allocated for chunks. 560.0KiB in use in bin. 560.0KiB client-requested in use in bin.
2025-05-09 18:36:03.286544: 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.
2025-05-09 18:36:03.286559: 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.
2025-05-09 18:36:03.286574: 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.
2025-05-09 18:36:03.286588: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2097152): 	Total Chunks: 9, Chunks in use: 9. 21.76MiB allocated for chunks. 21.76MiB in use in bin. 20.00MiB client-requested in use in bin.
2025-05-09 18:36:03.286602: 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.
2025-05-09 18:36:03.286615: 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.
2025-05-09 18:36:03.286638: 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.
2025-05-09 18:36:03.286652: 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.
2025-05-09 18:36:03.286665: 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.
2025-05-09 18:36:03.286678: 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.
2025-05-09 18:36:03.286691: 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.
2025-05-09 18:36:03.286705: I tensorflow/core/common_runtime/bfc_allocator.cc:957] Bin for 2.25MiB was 2.00MiB, Chunk State: 
2025-05-09 18:36:03.286716: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 17832960
2025-05-09 18:36:03.286735: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52c000000 of size 2359296 next 245
2025-05-09 18:36:03.286747: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52c240000 of size 1048576 next 269
2025-05-09 18:36:03.286759: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc52c340000 of size 1310720 next 263
2025-05-09 18:36:03.286771: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52c480000 of size 2359296 next 262
2025-05-09 18:36:03.286782: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52c6c0000 of size 1048576 next 287
2025-05-09 18:36:03.286794: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52c7c0000 of size 1310720 next 281
2025-05-09 18:36:03.286806: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52c900000 of size 2359296 next 280
2025-05-09 18:36:03.286818: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52cb40000 of size 1048576 next 303
2025-05-09 18:36:03.286829: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52cc40000 of size 1310720 next 298
2025-05-09 18:36:03.286841: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52cd80000 of size 3677184 next 18446744073709551615
2025-05-09 18:36:03.286853: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 16777216
2025-05-09 18:36:03.286864: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52e000000 of size 2359296 next 181
2025-05-09 18:36:03.286876: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52e240000 of size 2097152 next 196
2025-05-09 18:36:03.286888: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52e440000 of size 1048576 next 216
2025-05-09 18:36:03.286913: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52e540000 of size 1310720 next 209
2025-05-09 18:36:03.286927: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52e680000 of size 2359296 next 208
2025-05-09 18:36:03.286939: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52e8c0000 of size 1048576 next 234
2025-05-09 18:36:03.286950: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52e9c0000 of size 1310720 next 228
2025-05-09 18:36:03.286962: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52eb00000 of size 2359296 next 227
2025-05-09 18:36:03.286974: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52ed40000 of size 2883584 next 18446744073709551615
2025-05-09 18:36:03.286985: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 2097152
2025-05-09 18:36:03.286997: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530600000 of size 147456 next 55
2025-05-09 18:36:03.287018: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530624000 of size 65536 next 78
2025-05-09 18:36:03.287030: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530634000 of size 4096 next 191
2025-05-09 18:36:03.287042: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530635000 of size 4096 next 192
2025-05-09 18:36:03.287054: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530636000 of size 4096 next 193
2025-05-09 18:36:03.287066: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530637000 of size 256 next 194
2025-05-09 18:36:03.287077: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530637100 of size 256 next 195
2025-05-09 18:36:03.287089: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530637200 of size 4096 next 197
2025-05-09 18:36:03.287100: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530638200 of size 4096 next 198
2025-05-09 18:36:03.287112: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530639200 of size 4096 next 199
2025-05-09 18:36:03.287123: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063a200 of size 4096 next 200
2025-05-09 18:36:03.287135: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063b200 of size 4096 next 201
2025-05-09 18:36:03.287147: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063c200 of size 1024 next 202
2025-05-09 18:36:03.287158: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063c600 of size 1024 next 204
2025-05-09 18:36:03.287170: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063ca00 of size 1024 next 205
2025-05-09 18:36:03.287181: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063ce00 of size 1024 next 206
2025-05-09 18:36:03.287193: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063d200 of size 1024 next 207
2025-05-09 18:36:03.287204: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063d600 of size 1024 next 210
2025-05-09 18:36:03.287216: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063da00 of size 1024 next 211
2025-05-09 18:36:03.287227: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063de00 of size 1024 next 212
2025-05-09 18:36:03.287239: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063e200 of size 1024 next 213
2025-05-09 18:36:03.287250: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063e600 of size 1024 next 214
2025-05-09 18:36:03.287262: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063ea00 of size 4096 next 215
2025-05-09 18:36:03.287274: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53063fa00 of size 4096 next 217
2025-05-09 18:36:03.287285: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530640a00 of size 4096 next 218
2025-05-09 18:36:03.287297: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530641a00 of size 4096 next 219
2025-05-09 18:36:03.287308: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530642a00 of size 4096 next 220
2025-05-09 18:36:03.287320: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530643a00 of size 1024 next 221
2025-05-09 18:36:03.287331: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530643e00 of size 1024 next 223
2025-05-09 18:36:03.287343: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530644200 of size 1024 next 224
2025-05-09 18:36:03.287354: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530644600 of size 1024 next 225
2025-05-09 18:36:03.287366: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530644a00 of size 1024 next 226
2025-05-09 18:36:03.287378: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530644e00 of size 1024 next 229
2025-05-09 18:36:03.287397: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530645200 of size 1024 next 230
2025-05-09 18:36:03.287409: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530645600 of size 1024 next 231
2025-05-09 18:36:03.287420: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530645a00 of size 1024 next 232
2025-05-09 18:36:03.287432: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530645e00 of size 1024 next 233
2025-05-09 18:36:03.287444: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530646200 of size 7680 next 72
2025-05-09 18:36:03.287455: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530648000 of size 147456 next 71
2025-05-09 18:36:03.287467: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53066c000 of size 131072 next 87
2025-05-09 18:36:03.287479: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53068c000 of size 4096 next 289
2025-05-09 18:36:03.287490: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53068d000 of size 4096 next 290
2025-05-09 18:36:03.287502: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53068e000 of size 4096 next 291
2025-05-09 18:36:03.287513: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53068f000 of size 1024 next 292
2025-05-09 18:36:03.287525: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53068f400 of size 1024 next 293
2025-05-09 18:36:03.287536: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53068f800 of size 1024 next 294
2025-05-09 18:36:03.287548: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc53068fc00 of size 1024 next 295
2025-05-09 18:36:03.287559: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530690000 of size 1024 next 296
2025-05-09 18:36:03.287571: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530690400 of size 1024 next 297
2025-05-09 18:36:03.287582: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530690800 of size 1024 next 299
2025-05-09 18:36:03.287594: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530690c00 of size 1024 next 300
2025-05-09 18:36:03.287605: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530691000 of size 1024 next 301
2025-05-09 18:36:03.287617: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530691400 of size 1024 next 302
2025-05-09 18:36:03.287628: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530691800 of size 4096 next 304
2025-05-09 18:36:03.287640: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530692800 of size 4096 next 305
2025-05-09 18:36:03.287651: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530693800 of size 4096 next 306
2025-05-09 18:36:03.287663: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530694800 of size 4096 next 307
2025-05-09 18:36:03.287674: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530695800 of size 4096 next 308
2025-05-09 18:36:03.287686: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530696800 of size 1024 next 309
2025-05-09 18:36:03.287697: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530696c00 of size 1024 next 310
2025-05-09 18:36:03.287709: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530697000 of size 1024 next 311
2025-05-09 18:36:03.287720: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530697400 of size 1024 next 312
2025-05-09 18:36:03.287732: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530697800 of size 1024 next 313
2025-05-09 18:36:03.287743: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530697c00 of size 256 next 314
2025-05-09 18:36:03.287755: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc530697d00 of size 213760 next 103
2025-05-09 18:36:03.287774: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5306cc000 of size 262144 next 102
2025-05-09 18:36:03.287787: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc53070c000 of size 999424 next 18446744073709551615
2025-05-09 18:36:03.287798: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 4194304
2025-05-09 18:36:03.287810: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530800000 of size 589824 next 96
2025-05-09 18:36:03.287822: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530890000 of size 262144 next 117
2025-05-09 18:36:03.287833: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc5308d0000 of size 262144 next 112
2025-05-09 18:36:03.287845: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530910000 of size 524288 next 111
2025-05-09 18:36:03.287857: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530990000 of size 262144 next 135
2025-05-09 18:36:03.287869: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5309d0000 of size 327680 next 124
2025-05-09 18:36:03.287880: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530a20000 of size 589824 next 123
2025-05-09 18:36:03.287892: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530ab0000 of size 262144 next 152
2025-05-09 18:36:03.287904: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530af0000 of size 327680 next 142
2025-05-09 18:36:03.287916: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530b40000 of size 786432 next 18446744073709551615
2025-05-09 18:36:03.287927: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 8388608
2025-05-09 18:36:03.287939: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc530c00000 of size 589824 next 160
2025-05-09 18:36:03.287950: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530c90000 of size 589824 next 158
2025-05-09 18:36:03.287962: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530d20000 of size 524288 next 171
2025-05-09 18:36:03.287974: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc530da0000 of size 1048576 next 222
2025-05-09 18:36:03.287985: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530ea0000 of size 1048576 next 190
2025-05-09 18:36:03.287997: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc530fa0000 of size 1048576 next 189
2025-05-09 18:36:03.288009: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5310a0000 of size 1048576 next 203
2025-05-09 18:36:03.288020: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5311a0000 of size 1048576 next 251
2025-05-09 18:36:03.288032: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc5312a0000 of size 1441792 next 18446744073709551615
2025-05-09 18:36:03.288043: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 1048576
2025-05-09 18:36:03.288055: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce00000 of size 1280 next 1
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2025-05-09 18:36:03.289875: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce2a000 of size 256 next 188
2025-05-09 18:36:03.289886: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce2a100 of size 4096 next 186
2025-05-09 18:36:03.289898: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce2b100 of size 4096 next 42
2025-05-09 18:36:03.289910: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce2c100 of size 65536 next 36
2025-05-09 18:36:03.289921: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce3c100 of size 65536 next 35
2025-05-09 18:36:03.289933: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce4c100 of size 4096 next 235
2025-05-09 18:36:03.289944: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce4d100 of size 4096 next 236
2025-05-09 18:36:03.289956: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce4e100 of size 4096 next 237
2025-05-09 18:36:03.289967: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce4f100 of size 4096 next 238
2025-05-09 18:36:03.289979: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce50100 of size 1024 next 239
2025-05-09 18:36:03.289990: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce50500 of size 1024 next 240
2025-05-09 18:36:03.290002: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce50900 of size 1024 next 241
2025-05-09 18:36:03.290014: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce50d00 of size 1024 next 242
2025-05-09 18:36:03.290025: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce51100 of size 1024 next 243
2025-05-09 18:36:03.290037: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce51500 of size 1024 next 246
2025-05-09 18:36:03.290048: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce51900 of size 1024 next 247
2025-05-09 18:36:03.290059: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce51d00 of size 1024 next 248
2025-05-09 18:36:03.290078: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce52100 of size 1024 next 249
2025-05-09 18:36:03.290090: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce52500 of size 1024 next 250
2025-05-09 18:36:03.290102: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce52900 of size 4096 next 252
2025-05-09 18:36:03.290113: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce53900 of size 4096 next 253
2025-05-09 18:36:03.290125: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce54900 of size 4096 next 254
2025-05-09 18:36:03.290136: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce55900 of size 4096 next 255
2025-05-09 18:36:03.290148: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce56900 of size 4096 next 256
2025-05-09 18:36:03.290159: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce57900 of size 1024 next 257
2025-05-09 18:36:03.290171: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce57d00 of size 1024 next 258
2025-05-09 18:36:03.290182: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce58100 of size 1024 next 259
2025-05-09 18:36:03.290194: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce58500 of size 1024 next 260
2025-05-09 18:36:03.290205: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce58900 of size 1024 next 261
2025-05-09 18:36:03.290217: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce58d00 of size 1024 next 264
2025-05-09 18:36:03.290228: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce59100 of size 1024 next 265
2025-05-09 18:36:03.290240: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce59500 of size 1024 next 266
2025-05-09 18:36:03.290251: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce59900 of size 1024 next 267
2025-05-09 18:36:03.290263: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce59d00 of size 1024 next 268
2025-05-09 18:36:03.290274: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce5a100 of size 4096 next 270
2025-05-09 18:36:03.290286: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce5b100 of size 4096 next 271
2025-05-09 18:36:03.290297: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce5c100 of size 4096 next 272
2025-05-09 18:36:03.290309: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce5d100 of size 4096 next 273
2025-05-09 18:36:03.290320: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce5e100 of size 4096 next 274
2025-05-09 18:36:03.290332: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce5f100 of size 1024 next 275
2025-05-09 18:36:03.290343: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce5f500 of size 1024 next 276
2025-05-09 18:36:03.290355: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce5f900 of size 1024 next 277
2025-05-09 18:36:03.290366: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce5fd00 of size 1024 next 278
2025-05-09 18:36:03.290378: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce60100 of size 1024 next 279
2025-05-09 18:36:03.290390: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce60500 of size 1024 next 282
2025-05-09 18:36:03.290401: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce60900 of size 1024 next 283
2025-05-09 18:36:03.290413: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce60d00 of size 1024 next 284
2025-05-09 18:36:03.290424: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce61100 of size 1024 next 285
2025-05-09 18:36:03.290436: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce61500 of size 1024 next 286
2025-05-09 18:36:03.290464: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce61900 of size 4096 next 288
2025-05-09 18:36:03.290477: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce62900 of size 6144 next 27
2025-05-09 18:36:03.290489: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce64100 of size 147456 next 26
2025-05-09 18:36:03.290500: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce88100 of size 65536 next 47
2025-05-09 18:36:03.290512: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce98100 of size 65536 next 59
2025-05-09 18:36:03.290523: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66cea8100 of size 65536 next 65
2025-05-09 18:36:03.290536: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ceb8100 of size 294656 next 18446744073709551615
2025-05-09 18:36:03.290547: I tensorflow/core/common_runtime/bfc_allocator.cc:995]      Summary of in-use Chunks by size: 
2025-05-09 18:36:03.290562: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 60 Chunks of size 256 totalling 15.0KiB
2025-05-09 18:36:03.290575: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 40 Chunks of size 512 totalling 20.0KiB
2025-05-09 18:36:03.290588: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 95 Chunks of size 1024 totalling 95.0KiB
2025-05-09 18:36:03.290601: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1280 totalling 1.2KiB
2025-05-09 18:36:03.290614: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 25 Chunks of size 2048 totalling 50.0KiB
2025-05-09 18:36:03.290627: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 38 Chunks of size 4096 totalling 152.0KiB
2025-05-09 18:36:03.290639: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 6144 totalling 6.0KiB
2025-05-09 18:36:03.290652: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 7680 totalling 7.5KiB
2025-05-09 18:36:03.290665: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 16384 totalling 16.0KiB
2025-05-09 18:36:03.290678: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 37632 totalling 36.8KiB
2025-05-09 18:36:03.290690: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 6 Chunks of size 65536 totalling 384.0KiB
2025-05-09 18:36:03.290703: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 131072 totalling 128.0KiB
2025-05-09 18:36:03.290716: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 3 Chunks of size 147456 totalling 432.0KiB
2025-05-09 18:36:03.290729: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 4 Chunks of size 262144 totalling 1.00MiB
2025-05-09 18:36:03.290741: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 294656 totalling 287.8KiB
2025-05-09 18:36:03.290754: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 327680 totalling 640.0KiB
2025-05-09 18:36:03.290767: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 524288 totalling 1.00MiB
2025-05-09 18:36:03.290779: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 3 Chunks of size 589824 totalling 1.69MiB
2025-05-09 18:36:03.290792: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 786432 totalling 768.0KiB
2025-05-09 18:36:03.290805: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 9 Chunks of size 1048576 totalling 9.00MiB
2025-05-09 18:36:03.290817: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 4 Chunks of size 1310720 totalling 5.00MiB
2025-05-09 18:36:03.290829: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1441792 totalling 1.38MiB
2025-05-09 18:36:03.290842: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 2097152 totalling 2.00MiB
2025-05-09 18:36:03.290855: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 6 Chunks of size 2359296 totalling 13.50MiB
2025-05-09 18:36:03.290867: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 2883584 totalling 2.75MiB
2025-05-09 18:36:03.290888: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 3677184 totalling 3.51MiB
2025-05-09 18:36:03.290911: I tensorflow/core/common_runtime/bfc_allocator.cc:1002] Sum Total of in-use chunks: 43.79MiB
2025-05-09 18:36:03.290923: I tensorflow/core/common_runtime/bfc_allocator.cc:1004] total_region_allocated_bytes_: 50338816 memory_limit_: 214827008 available bytes: 164488192 curr_region_allocation_bytes_: 67108864
2025-05-09 18:36:03.290940: I tensorflow/core/common_runtime/bfc_allocator.cc:1010] Stats: 
Limit:                   214827008
InUse:                    45914368
MaxInUse:                 45914368
NumAllocs:                    1014
MaxAllocSize:              4325376

2025-05-09 18:36:03.290963: W tensorflow/core/common_runtime/bfc_allocator.cc:439] *******__************************xx************************************_*********x***_**************
2025-05-09 18:36:03.291017: 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:Mul]
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 : 0.14584922790527344
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
Fri May  9 18:36:04 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 : 356
wait 20 seconds
l 3637 free memory gpu now : 356  max_wait_temp :  1 max_wait :  0
 gpu_flag :  0
2025-05-09 18:36:27.771376: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2025-05-09 18:36:27.799257: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz
2025-05-09 18:36:27.801376: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7fc714000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2025-05-09 18:36:27.801408: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2025-05-09 18:36:27.805559: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2025-05-09 18:36:28.032963: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x26f6a420 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2025-05-09 18:36:28.033036: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5
2025-05-09 18:36:28.034080: 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
2025-05-09 18:36:28.038089: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-09 18:36:28.041641: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-09 18:36:28.044089: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-09 18:36:28.044501: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-09 18:36:28.047231: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-09 18:36:28.048509: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-09 18:36:28.053940: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-09 18:36:28.055025: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-09 18:36:28.055129: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-09 18:36:28.055626: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2025-05-09 18:36:28.055644: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2025-05-09 18:36:28.055654: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 
2025-05-09 18:36:28.056434: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 204 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
2025-05-09 18:36:28.655304: 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
2025-05-09 18:36:28.655436: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-09 18:36:28.655465: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-09 18:36:28.655492: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-09 18:36:28.655517: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-09 18:36:28.655543: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-09 18:36:28.655567: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-09 18:36:28.655596: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-09 18:36:28.656490: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-09 18:36:28.657629: 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
2025-05-09 18:36:28.657669: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-05-09 18:36:28.657691: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-05-09 18:36:28.657712: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-05-09 18:36:28.657733: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-05-09 18:36:28.657753: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-05-09 18:36:28.657774: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-05-09 18:36:28.657794: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-05-09 18:36:28.658669: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-05-09 18:36:28.658712: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2025-05-09 18:36:28.658724: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2025-05-09 18:36:28.658735: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 
2025-05-09 18:36:28.659689: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 204 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5)
2025-05-09 18:36:29.648841: 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
2025-05-09 18:36:29.649472: 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
2025-05-09 18:36:29.650439: 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
2025-05-09 18:36:29.651484: 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
2025-05-09 18:36:29.652439: 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
2025-05-09 18:36:29.653255: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 18.90M (19814144 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
2025-05-09 18:36:29.801922: 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
2025-05-09 18:36:29.802439: 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
2025-05-09 18:36:39.803517: 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
2025-05-09 18:36:39.804375: 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
2025-05-09 18:36:39.804407: 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.
2025-05-09 18:36:39.804430: I tensorflow/core/common_runtime/bfc_allocator.cc:934] BFCAllocator dump for GPU_0_bfc
2025-05-09 18:36:39.804449: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (256): 	Total Chunks: 60, Chunks in use: 60. 15.0KiB allocated for chunks. 15.0KiB in use in bin. 8.8KiB client-requested in use in bin.
2025-05-09 18:36:39.804465: 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.
2025-05-09 18:36:39.804482: 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.
2025-05-09 18:36:39.804500: 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.
2025-05-09 18:36:39.804518: 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.
2025-05-09 18:36:39.804533: 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.
2025-05-09 18:36:39.804549: 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.
2025-05-09 18:36:39.804565: 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.
2025-05-09 18:36:39.804580: 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.
2025-05-09 18:36:39.804596: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (131072): 	Total Chunks: 5, Chunks in use: 4. 768.8KiB allocated for chunks. 560.0KiB in use in bin. 560.0KiB client-requested in use in bin.
2025-05-09 18:36:39.804611: 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.
2025-05-09 18:36:39.804626: 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.
2025-05-09 18:36:39.804657: 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.
2025-05-09 18:36:39.804673: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2097152): 	Total Chunks: 9, Chunks in use: 9. 21.76MiB allocated for chunks. 21.76MiB in use in bin. 20.00MiB client-requested in use in bin.
2025-05-09 18:36:39.804687: 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.
2025-05-09 18:36:39.804701: 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.
2025-05-09 18:36:39.804717: 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.
2025-05-09 18:36:39.804731: 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.
2025-05-09 18:36:39.804745: 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.
2025-05-09 18:36:39.804758: 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.
2025-05-09 18:36:39.804772: 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.
2025-05-09 18:36:39.804786: I tensorflow/core/common_runtime/bfc_allocator.cc:957] Bin for 2.25MiB was 2.00MiB, Chunk State: 
2025-05-09 18:36:39.804798: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 17832960
2025-05-09 18:36:39.804814: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52c000000 of size 2359296 next 245
2025-05-09 18:36:39.804827: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52c240000 of size 1048576 next 269
2025-05-09 18:36:39.804839: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free  at 7fc52c340000 of size 1310720 next 263
2025-05-09 18:36:39.804851: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc52c480000 of size 2359296 next 262
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2025-05-09 18:36:39.808692: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce60d00 of size 1024 next 284
2025-05-09 18:36:39.808704: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce61100 of size 1024 next 285
2025-05-09 18:36:39.808716: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce61500 of size 1024 next 286
2025-05-09 18:36:39.808728: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce61900 of size 4096 next 288
2025-05-09 18:36:39.808741: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce62900 of size 6144 next 27
2025-05-09 18:36:39.808753: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce64100 of size 147456 next 26
2025-05-09 18:36:39.808765: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce88100 of size 65536 next 47
2025-05-09 18:36:39.808777: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ce98100 of size 65536 next 59
2025-05-09 18:36:39.808789: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66cea8100 of size 65536 next 65
2025-05-09 18:36:39.808802: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7fc66ceb8100 of size 294656 next 18446744073709551615
2025-05-09 18:36:39.808813: I tensorflow/core/common_runtime/bfc_allocator.cc:995]      Summary of in-use Chunks by size: 
2025-05-09 18:36:39.808828: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 60 Chunks of size 256 totalling 15.0KiB
2025-05-09 18:36:39.808842: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 40 Chunks of size 512 totalling 20.0KiB
2025-05-09 18:36:39.808856: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 95 Chunks of size 1024 totalling 95.0KiB
2025-05-09 18:36:39.808869: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1280 totalling 1.2KiB
2025-05-09 18:36:39.808882: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 25 Chunks of size 2048 totalling 50.0KiB
2025-05-09 18:36:39.808896: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 38 Chunks of size 4096 totalling 152.0KiB
2025-05-09 18:36:39.808909: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 6144 totalling 6.0KiB
2025-05-09 18:36:39.808922: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 7680 totalling 7.5KiB
2025-05-09 18:36:39.808935: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 16384 totalling 16.0KiB
2025-05-09 18:36:39.808949: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 37632 totalling 36.8KiB
2025-05-09 18:36:39.808962: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 6 Chunks of size 65536 totalling 384.0KiB
2025-05-09 18:36:39.808975: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 131072 totalling 128.0KiB
2025-05-09 18:36:39.808988: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 3 Chunks of size 147456 totalling 432.0KiB
2025-05-09 18:36:39.809002: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 4 Chunks of size 262144 totalling 1.00MiB
2025-05-09 18:36:39.809015: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 294656 totalling 287.8KiB
2025-05-09 18:36:39.809028: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 327680 totalling 640.0KiB
2025-05-09 18:36:39.809041: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 2 Chunks of size 524288 totalling 1.00MiB
2025-05-09 18:36:39.809054: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 3 Chunks of size 589824 totalling 1.69MiB
2025-05-09 18:36:39.809076: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 786432 totalling 768.0KiB
2025-05-09 18:36:39.809089: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 9 Chunks of size 1048576 totalling 9.00MiB
2025-05-09 18:36:39.809103: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 4 Chunks of size 1310720 totalling 5.00MiB
2025-05-09 18:36:39.809116: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1441792 totalling 1.38MiB
2025-05-09 18:36:39.809129: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 2097152 totalling 2.00MiB
2025-05-09 18:36:39.809142: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 6 Chunks of size 2359296 totalling 13.50MiB
2025-05-09 18:36:39.809155: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 2883584 totalling 2.75MiB
2025-05-09 18:36:39.809168: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 3677184 totalling 3.51MiB
2025-05-09 18:36:39.809181: I tensorflow/core/common_runtime/bfc_allocator.cc:1002] Sum Total of in-use chunks: 43.79MiB
2025-05-09 18:36:39.809194: I tensorflow/core/common_runtime/bfc_allocator.cc:1004] total_region_allocated_bytes_: 50338816 memory_limit_: 214827008 available bytes: 164488192 curr_region_allocation_bytes_: 67108864
2025-05-09 18:36:39.809210: I tensorflow/core/common_runtime/bfc_allocator.cc:1010] Stats: 
Limit:                   214827008
InUse:                    45914368
MaxInUse:                 45914368
NumAllocs:                    1014
MaxAllocSize:              4325376

2025-05-09 18:36:39.809233: W tensorflow/core/common_runtime/bfc_allocator.cc:439] *******__************************xx************************************_*********x***_**************
2025-05-09 18:36:39.809274: 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:Mul]
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/09052025/python_test3//data_2/data_log/job/2025/May/09052025/python_test3/log-python3----short_python3--v--marlene-18:35:02.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 : 0.18256664276123047
#### 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
Fri May  9 18:36:40 2025
VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next
VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case
VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec 
VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec
After prepare type args : <class 'list'>

Here we display some param of map_info ! 
map_filenames : {'temp/1746808600_1338151_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png': 1189321094}
map_photo_id_path_extension : {1189321094: {'path': 'temp/1746808600_1338151_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 : 0.016117095947265625
 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 : 3.6014606952667236
time spend to save output : 0.017712831497192383
total time spend for step 0 : 3.619173526763916
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 : 0.1297931671142578
#### 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
Fri May  9 18:36:44 2025
VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next
VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case
VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec 
VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec
After prepare type args : <class 'list'>

Here we display some param of map_info ! 
map_filenames : {'temp/1746808604_1338151_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg': 917754606}
map_photo_id_path_extension : {917754606: {'path': 'temp/1746808604_1338151_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
E0509 18:36:45.619792 1338151 common.cpp:114] Cannot create Cublas handle. Cublas won't be available.
E0509 18:36:45.632190 1338151 common.cpp:121] Cannot create Curand generator. Curand won't be available.
F0509 18:36:45.662596 1338151 syncedmem.hpp:22] Check failed: error == cudaSuccess (2 vs. 0)  out of memory
*** Check failure stack trace: ***
Command terminated by signal 6
6.74user 7.49system 1:19.73elapsed 17%CPU (0avgtext+0avgdata 1188520maxresident)k
1401248inputs+3432outputs (3359major+588698minor)pagefaults 0swaps