python /home/admin/mtr/script_for_cron.py -j datou_current3 -m 20 -a ' -a 3318 ' -s datou_3318 -M 0 -S 0 -U 95,95,120 import MySQLdb succeeded Import error (python version) ['/Users/moilerat/Documents/Fotonower/install/caffe/distribute/python', '/home/admin/workarea/git/Velours/python/prod', '/home/admin/workarea/install/caffe_cuda8_python3/python', '/home/admin/workarea/install/darknet', '/home/admin/workarea/git/Velours/python', '/home/admin/workarea/install/caffe_frcnn_python3/py-faster-rcnn/caffe-fast-rcnn/python', '/home/admin/mtr/.credentials', '/home/admin/workarea/install/caffe/python', '/home/admin/workarea/install/caffe_frcnn/py-faster-rcnn/tools', '/home/admin/workarea/git/fotonowerpip', '/home/admin/workarea/install/segment-anything', '/home/admin/workarea/git/pyfvs', '/usr/lib/python38.zip', '/usr/lib/python3.8', '/usr/lib/python3.8/lib-dynload', '/home/admin/.local/lib/python3.8/site-packages', '/usr/local/lib/python3.8/dist-packages', '/usr/lib/python3/dist-packages'] process id : 3425237 load datou : 3318 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! Unexpected type for variable list_input_json ERROR or WARNING : can't parse json string Expecting value: line 1 column 1 (char 0) Tried to parse : chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? [(photo_id, hashtag_id, hashtag_type, x0, x1, y0, y1, score, seg_temp, polygons), ...] was removed should we ? chemin de la photo was removed should we ? [ (photo_id_loc, hashtag_id, hashtag_type, x0, x1, y0, y1, score, None), ...] was removed should we ? chemin de la photo was removed should we ? id de la photo (peut être local ou global) was removed should we ? chemin de la photo was removed should we ? (x0, y0, x1, y1) was removed should we ? chemin de la photo was removed should we ? donnée sous forme de texte was removed should we ? [ (photo_id, photo_id_loc, hashtag_type, x0, x1, y0, y1, score), ...] was removed should we ? None was removed should we ? donnée sous forme de texte was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? id de la photo (peut être local ou global) was removed should we ? donnée sous forme de texte was removed should we ? donnée sous forme de texte was removed should we ? donnée sous forme de texte was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? chemin de la photo was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? None was removed should we ? donnée sous forme de nombre was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? donnée sous forme de texte was removed should we ? None was removed should we ? donnée sous forme de texte was removed should we ? [ptf_id0,ptf_id1...] was removed should we ? FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) load thcls load THCL from format json or kwargs add thcl : 2847 in CacheModelConfig load pdts add pdt : 5275 in CacheModelConfig Running datou job : batch_current TODO datou_current to load to do maybe to take outside batchDatouExec updating current state to 1 list_input_json: [] Current got : datou_id : 3318, datou_cur_ids : ['3370219'] with mtr_portfolio_ids : ['25399044'] and first list_photo_ids : [] new path : /proc/3425237/ Inside batchDatouExec : verbose : 0 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 7928 mask_detect is not consistent : 3 used against 2 in the step definition ! Step 8092 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 8092 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7933 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 7935 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 7934 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 7934 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! WARNING : number of outputs for step 13649 velours_tree is not consistent : 2 used against 1 in the step definition ! Step 9283 split_time_score have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 1 of step 7935 doesn't seem to be define in the database( WARNING : type of input 3 of step 7934 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of input 1 of step 7935 doesn't seem to be define in the database( WARNING : output 1 of step 7933 have datatype=7 whereas input 1 of step 7935 have datatype=None WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 2 of step 8092 doesn't seem to be define in the database( WARNING : type of output 3 of step 8092 doesn't seem to be define in the database( WARNING : type of input 1 of step 7933 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10917 doesn't seem to be define in the database( WARNING : type of output 2 of step 7928 doesn't seem to be define in the database( WARNING : type of input 1 of step 10918 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 7935 have datatype=10 whereas input 3 of step 10916 have datatype=6 WARNING : output 0 of step 7935 have datatype=10 whereas input 0 of step 13649 have datatype=18 WARNING : type of output 1 of step 13649 doesn't seem to be define in the database( WARNING : type of input 5 of step 10916 doesn't seem to be define in the database( DataTypes for each output/input checked ! List Step Type Loaded in datou : mask_detect, crop_condition, rle_unique_nms_with_priority, ventilate_hashtags_in_portfolio, final, blur_detection, brightness, velours_tree, send_mail_cod, split_time_score over limit max, limiting to limit_max 40 list_input_json : [] origin We have 1 , BFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 13 ; length of list_pids : 13 ; length of list_args : 13 time to download the photos : 2.158418893814087 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 : 0 number of steps : 10 step1:mask_detect Mon Jul 28 12:20:31 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 : 376 wait 20 seconds l 3637 free memory gpu now : 376 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-07-28 12:20:53.900146: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-07-28 12:20:53.927310: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493035000 Hz 2025-07-28 12:20:53.928866: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f11d8000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-07-28 12:20:53.928886: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-07-28 12:20:53.931415: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-07-28 12:20:54.050513: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3a571c40 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-07-28 12:20:54.050549: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-07-28 12:20:54.051130: 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 2025-07-28 12:20:54.051402: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-28 12:20:54.053309: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-28 12:20:54.055291: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-28 12:20:54.055583: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-28 12:20:54.057618: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-28 12:20:54.058582: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-28 12:20:54.062683: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-28 12:20:54.063526: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-28 12:20:54.063597: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-28 12:20:54.064045: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-07-28 12:20:54.064061: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-07-28 12:20:54.064085: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-07-28 12:20:54.064762: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. 2025-07-28 12:20:54.305042: 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 2025-07-28 12:20:54.305152: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-28 12:20:54.305169: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-28 12:20:54.305183: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-28 12:20:54.305196: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-28 12:20:54.305209: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-28 12:20:54.305222: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-28 12:20:54.305235: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-28 12:20:54.305819: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-28 12:20:54.306655: 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 2025-07-28 12:20:54.306685: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-28 12:20:54.306701: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-28 12:20:54.306716: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-28 12:20:54.306730: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-28 12:20:54.306744: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-28 12:20:54.306758: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-28 12:20:54.306772: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-28 12:20:54.307357: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-28 12:20:54.307390: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-07-28 12:20:54.307398: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-07-28 12:20:54.307405: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-07-28 12:20:54.308026: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) 2025-07-28 12:21:04.757640: W tensorflow/core/common_runtime/bfc_allocator.cc:434] Allocator (GPU_0_bfc) ran out of memory trying to allocate 144.0KiB (rounded to 147456) Current allocation summary follows. 2025-07-28 12:21:04.757691: I tensorflow/core/common_runtime/bfc_allocator.cc:934] BFCAllocator dump for GPU_0_bfc 2025-07-28 12:21:04.757702: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (256): Total Chunks: 16, Chunks in use: 16. 4.0KiB allocated for chunks. 4.0KiB in use in bin. 2.5KiB client-requested in use in bin. 2025-07-28 12:21:04.757710: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (512): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-28 12:21:04.757718: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1024): Total Chunks: 1, Chunks in use: 1. 1.2KiB allocated for chunks. 1.2KiB in use in bin. 1.0KiB client-requested in use in bin. 2025-07-28 12:21:04.757725: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2048): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-28 12:21:04.757733: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (4096): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-28 12:21:04.757740: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (8192): Total Chunks: 1, Chunks in use: 0. 14.8KiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-28 12:21:04.757751: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (16384): Total Chunks: 3, Chunks in use: 1. 55.5KiB allocated for chunks. 16.0KiB in use in bin. 16.0KiB client-requested in use in bin. 2025-07-28 12:21:04.757760: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (32768): Total Chunks: 1, Chunks in use: 1. 52.5KiB allocated for chunks. 52.5KiB in use in bin. 36.8KiB client-requested in use in bin. 2025-07-28 12:21:04.757767: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (65536): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-28 12:21:04.757774: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (131072): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-28 12:21:04.757782: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (262144): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-28 12:21:04.757788: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (524288): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-28 12:21:04.757795: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1048576): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-28 12:21:04.757802: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2097152): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-28 12:21:04.757810: 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. 2025-07-28 12:21:04.757817: 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. 2025-07-28 12:21:04.757824: 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. 2025-07-28 12:21:04.757831: 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. 2025-07-28 12:21:04.757845: 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. 2025-07-28 12:21:04.757853: 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. 2025-07-28 12:21:04.757860: 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. 2025-07-28 12:21:04.757868: I tensorflow/core/common_runtime/bfc_allocator.cc:957] Bin for 144.0KiB was 128.0KiB, Chunk State: 2025-07-28 12:21:04.757875: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 131072 2025-07-28 12:21:04.757888: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00000 of size 1280 next 1 2025-07-28 12:21:04.757895: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00500 of size 256 next 5 2025-07-28 12:21:04.757901: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00600 of size 256 next 7 2025-07-28 12:21:04.757908: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00700 of size 256 next 8 2025-07-28 12:21:04.757914: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00800 of size 256 next 9 2025-07-28 12:21:04.757920: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00900 of size 256 next 10 2025-07-28 12:21:04.757926: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00a00 of size 256 next 11 2025-07-28 12:21:04.757932: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00b00 of size 256 next 12 2025-07-28 12:21:04.757939: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00c00 of size 256 next 16 2025-07-28 12:21:04.757945: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00d00 of size 256 next 18 2025-07-28 12:21:04.757951: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00e00 of size 256 next 19 2025-07-28 12:21:04.757957: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e00f00 of size 256 next 20 2025-07-28 12:21:04.757963: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e01000 of size 256 next 21 2025-07-28 12:21:04.757970: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f1134e01100 of size 15104 next 13 2025-07-28 12:21:04.757976: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e04c00 of size 256 next 14 2025-07-28 12:21:04.757983: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e04d00 of size 256 next 15 2025-07-28 12:21:04.757991: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f1134e04e00 of size 18944 next 2 2025-07-28 12:21:04.757997: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e09800 of size 256 next 3 2025-07-28 12:21:04.758004: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e09900 of size 256 next 4 2025-07-28 12:21:04.758011: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e09a00 of size 16384 next 17 2025-07-28 12:21:04.758019: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f1134e0da00 of size 21504 next 6 2025-07-28 12:21:04.758026: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f1134e12e00 of size 53760 next 18446744073709551615 2025-07-28 12:21:04.758033: I tensorflow/core/common_runtime/bfc_allocator.cc:995] Summary of in-use Chunks by size: 2025-07-28 12:21:04.758042: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 16 Chunks of size 256 totalling 4.0KiB 2025-07-28 12:21:04.758050: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1280 totalling 1.2KiB 2025-07-28 12:21:04.758057: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 16384 totalling 16.0KiB 2025-07-28 12:21:04.758071: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 53760 totalling 52.5KiB 2025-07-28 12:21:04.758079: I tensorflow/core/common_runtime/bfc_allocator.cc:1002] Sum Total of in-use chunks: 73.8KiB 2025-07-28 12:21:04.758086: I tensorflow/core/common_runtime/bfc_allocator.cc:1004] total_region_allocated_bytes_: 131072 memory_limit_: 131072 available bytes: 0 curr_region_allocation_bytes_: 262144 2025-07-28 12:21:04.758098: I tensorflow/core/common_runtime/bfc_allocator.cc:1010] Stats: Limit: 131072 InUse: 75520 MaxInUse: 130816 NumAllocs: 49 MaxAllocSize: 53760 2025-07-28 12:21:04.758108: W tensorflow/core/common_runtime/bfc_allocator.cc:439] ****__________**_____________**************_______________******************************xxxxxxxxxxxx 2025-07-28 12:21:04.758151: W tensorflow/core/framework/op_kernel.cc:1753] OP_REQUIRES failed at random_op.cc:77 : Resource exhausted: OOM when allocating tensor with shape[3,3,64,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl2847 thcls : [{'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}] thcl {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 5275 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5275, 'learn_RUBBIA_REFUS_AMIENS_23', 16384, 25088, 'learn_RUBBIA_REFUS_AMIENS_23', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2021, 4, 23, 14, 19, 39), datetime.datetime(2021, 4, 23, 14, 19, 39)) {'thcl': {'id': 2847, 'mtr_user_id': 31, 'name': 'learn_RUBBIA_REFUS_AMIENS_23', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'photo_desc_type': 5275, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'], 'list_hashtags_csv': 'background,papier,carton,metal,pet_clair,autre,pehd,pet_fonce,environnement', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 3594, 'svm_hashtag_type_desc': 5275, 'photo_desc_type': 5275, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['background', 'papier', 'carton', 'metal', 'pet_clair', 'autre', 'pehd', 'pet_fonce', 'environnement'] 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 learn_RUBBIA_REFUS_AMIENS_23 NUM_CLASSES 9 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 Exception in mask_detect : OOM when allocating tensor with shape[3,3,64,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:RandomUniform] we want to redo the detection Using TensorFlow backend. max_time_sub_proc : 3600 erreur pendant la detection Catched exception ! (2013, 'Lost connection to MySQL server during query') Connect or reconnect ! in case -12 caffe_path_current : About to save ! 2 After save, about to update current ! 3.22user 2.81system 0:40.09elapsed 15%CPU (0avgtext+0avgdata 1071264maxresident)k 0inputs+37120outputs (0major+223335minor)pagefaults 0swaps