python /home/admin/mtr/script_for_cron.py -j datou_current3 -m 8 -a ' --fifo -a 533 -l 100 ' -s datou_current_533 -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 : 549294 load datou : 533 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! Unexpected type 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_0, score_0), (photo_id, hashtag_id_1, score_1), ...] was removed should we ? [ (photo_id, hashtag_id_0, score_0), (photo_id, hashtag_id_1, score_1), ...] was removed should we ? (photo_id, hashtag_id, score_max) was removed should we ? chemin de la photo was removed should we ? load thcls load pdts Running datou job : batch_current TODO datou_current to load to do maybe to take outside batchDatouExec no input labels no input values updating current state to 1 we have a portfolio with more photos than limit : 10462>100 please execute split_portfolio.py -i 24628097 -l 100 size over we load limit photo not treated list_input_json: {} Current got : datou_id : 533, datou_cur_ids : ['3239078'] with mtr_portfolio_ids : ['24628097'] and first list_photo_ids : [] new path : /proc/549294/ 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 ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! Number of inputs / outputs for each step checked ! Here we check the consistency of outputs/inputs types during steps connections eke 1-6-18 : checkConsistencyTypeOutputInput should be processed after checkConsistencyNbInputNbOutput ! DataTypes for each output/input checked ! List Step Type Loaded in datou : tfhub_classification2, argmax list_input_json : {} origin We have 1 , WARNING: data may be incomplete, need to offset and complete ! BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 24 ; length of list_pids : 24 ; length of list_args : 24 time to download the photos : 3.4726080894470215 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 : 2 step1:tfhub_classification2 Thu Jul 10 03:16:33 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou_step TFHub with tf2 ! nombre de thcls : 3 we are using the classfication for multi_thcl [3513, 3379, 3847] begin to check gpu status inside check gpu memory 2025-07-10 03:16:36.137655: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-07-10 03:16:36.168439: 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 2025-07-10 03:16:36.168721: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-10 03:16:36.172293: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-10 03:16:36.174803: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-10 03:16:36.175318: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-10 03:16:36.179122: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-10 03:16:36.180793: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-10 03:16:36.187872: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-10 03:16:36.189352: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-10 03:16:36.189883: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-07-10 03:16:36.215402: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493035000 Hz 2025-07-10 03:16:36.217611: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f70c4000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-07-10 03:16:36.217640: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-07-10 03:16:36.333426: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x423c6c00 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-07-10 03:16:36.333465: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-07-10 03:16:36.334749: 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 2025-07-10 03:16:36.334882: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-10 03:16:36.334919: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-10 03:16:36.334952: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-10 03:16:36.334984: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-10 03:16:36.335016: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-10 03:16:36.335048: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-10 03:16:36.335082: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-10 03:16:36.336749: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-10 03:16:36.336828: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-10 03:16:36.337845: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-07-10 03:16:36.337870: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-07-10 03:16:36.337885: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-07-10 03:16:36.339634: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 3096 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) l 3637 free memory gpu now : 5665 max_wait_temp : 1 max_wait : 5 1 Physical GPUs, 1 Logical GPUs tagging for thcl : 3513 To do loadFromThcl(), then load ParamDescType : thcl3513 thcls : [{'id': 3513, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2_tf', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 4557, 'photo_desc_type': 5767, 'type_classification': 'tf_classification2', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'}] thcl {'id': 3513, 'mtr_user_id': 31, 'name': 'Rungis_amount_dechets_fall_2018_v2_tf', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': '05102018_Papier_non_papier_dense,05102018_Papier_non_papier_peu_dense,05102018_Papier_non_papier_presque_vide,05102018_Papier_non_papier_tres_dense,05102018_Papier_non_papier_tres_peu_dense', 'svm_portfolios_learning': '1108385,1108386,1108388,1108384,1108387', 'photo_hashtag_type': 4557, 'photo_desc_type': 5767, 'type_classification': 'tf_classification2', 'hashtag_id_list': '2107751013,2107751014,2107751015,2107751016,2107751017'} Update svm_hashtag_type_desc : 5767 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5767, 'Rungis_amount_dechets_fall_2018_v2_tf', 2048, 2048, 'Rungis_amount_dechets_fall_2018_v2_tf', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2023, 3, 16, 15, 52, 10), datetime.datetime(2023, 3, 16, 15, 52, 10)) model_name : Rungis_amount_dechets_fall_2018_v2_tf model_param file didn't exist model_name : Rungis_amount_dechets_fall_2018_v2_tf model_type : tf_classification2 list file need : ['Confusion_Matrix.png', 'Precision_Recall_05102018_Papier_non_papier_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_peu_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_presque_vide.jpg', 'Precision_Recall_05102018_Papier_non_papier_tres_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_tres_peu_dense.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00001', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file exist in s3 : ['Confusion_Matrix.png', 'Precision_Recall_05102018_Papier_non_papier_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_peu_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_presque_vide.jpg', 'Precision_Recall_05102018_Papier_non_papier_tres_dense.jpg', 'Precision_Recall_05102018_Papier_non_papier_tres_peu_dense.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00001', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file manque in s3 : [] local folder : /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Confusion_Matrix.png size_local : 67810 size in s3 : 67810 create time local : 2023-10-30 16:21:37 create time in s3 : 2023-10-30 14:09:29 Confusion_Matrix.png already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Precision_Recall_05102018_Papier_non_papier_dense.jpg size_local : 73949 size in s3 : 73949 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:30 Precision_Recall_05102018_Papier_non_papier_dense.jpg already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Precision_Recall_05102018_Papier_non_papier_peu_dense.jpg size_local : 85572 size in s3 : 85572 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:39 Precision_Recall_05102018_Papier_non_papier_peu_dense.jpg already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Precision_Recall_05102018_Papier_non_papier_presque_vide.jpg size_local : 72361 size in s3 : 72361 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:37 Precision_Recall_05102018_Papier_non_papier_presque_vide.jpg already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Precision_Recall_05102018_Papier_non_papier_tres_dense.jpg size_local : 83567 size in s3 : 83567 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:48 Precision_Recall_05102018_Papier_non_papier_tres_dense.jpg already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Precision_Recall_05102018_Papier_non_papier_tres_peu_dense.jpg size_local : 71611 size in s3 : 71611 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:29 Precision_Recall_05102018_Papier_non_papier_tres_peu_dense.jpg already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/Result_Summary.txt size_local : 1058 size in s3 : 1058 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:30 Result_Summary.txt already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/checkpoint size_local : 99 size in s3 : 99 create time local : 2023-10-30 16:21:38 create time in s3 : 2023-10-30 14:09:36 checkpoint already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/model_checkpoint.ckpt.data-00000-of-00001 size_local : 188538519 size in s3 : 188538519 create time local : 2023-10-30 16:21:41 create time in s3 : 2023-10-30 14:09:40 model_checkpoint.ckpt.data-00000-of-00001 already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/model_checkpoint.ckpt.data-00000-of-00002 size_local : 216572 size in s3 : 216572 create time local : 2023-10-30 16:21:41 create time in s3 : 2023-03-16 14:52:09 model_checkpoint.ckpt.data-00000-of-00002 already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/model_checkpoint.ckpt.data-00001-of-00002 size_local : 32279708 size in s3 : 32279708 create time local : 2023-10-30 16:21:42 create time in s3 : 2023-03-16 14:52:07 model_checkpoint.ckpt.data-00001-of-00002 already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/model_checkpoint.ckpt.index size_local : 28001 size in s3 : 28001 create time local : 2023-10-30 16:21:42 create time in s3 : 2023-10-30 14:09:30 model_checkpoint.ckpt.index already exist and didn't need to update /data/models_weight/Rungis_amount_dechets_fall_2018_v2_tf/model_weights.h5 size_local : 94501976 size in s3 : 94501976 create time local : 2023-10-30 16:21:44 create time in s3 : 2023-10-30 14:09:37 model_weights.h5 already exist and didn't need to update desc size : 2048 Model: "sequential" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= module (KerasLayer) (None, 2048) 23561152 _________________________________________________________________ Rungis_amount_dechets_fall_2 (None, 5) 10245 ================================================================= Total params: 23,571,397 Trainable params: 10,245 Non-trainable params: 23,561,152 _________________________________________________________________ Loading Weights... time used to create the model : 7.419212341308594 time used to load_weights : 0.16552400588989258 0it [00:00, ?it/s] 24it [00:00, 1899.63it/s]2025-07-10 03:16:45.694042: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-10 03:16:45.880242: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 temp/1752110189_549294_1371470513_21397e931b2f20ee0fd7a00d09a56861.jpg temp/1752110189_549294_1371470509_fc800a5415b48fd32f6f59e5708de262.jpg temp/1752110189_549294_1371470505_a97b45a10a39fa73c3dfb14127a614f9.jpg temp/1752110189_549294_1371470501_e0a4a49e72d0ed6f5fcf3377ebf09716.jpg temp/1752110189_549294_1371470493_c50dd37d209f28a7ab889e30fc85dd8e.jpg temp/1752110189_549294_1371470482_da8da65bf11540b5c799787724dde1ef.jpg temp/1752110189_549294_1371470450_7c9192636225c595f742620a26c0ed12.jpg temp/1752110189_549294_1371470448_642933bc9d28a783114b4c61c32b29ca.jpg temp/1752110189_549294_1371470444_231d43d93996baa57120cc3b429c0401.jpg temp/1752110189_549294_1371470441_e9e858e26ee34a0db2515730e2867188.jpg temp/1752110189_549294_1371470432_d50c90a5f43bb5ed44629f84f5cf8742.jpg temp/1752110189_549294_1371470428_023eedbaeb2cc829ea5baa598184c17a.jpg temp/1752110189_549294_1371469824_d33f1d75b99a55320cf6d282502a1a6c.jpg temp/1752110189_549294_1371469822_a68d82094927b24da9c6a2dd8c23acae.jpg temp/1752110189_549294_1371469819_8d7584e9d823dd27aed13e453f2d035d.jpg temp/1752110189_549294_1371469807_a81b632bb541c1673fb03d1900dfede3.jpg temp/1752110189_549294_1371469801_334ed5dcd05f462ac1d917e88f0599ac.jpg temp/1752110189_549294_1371469794_575b385b3df7dd8a49bf624a8edd4723.jpg temp/1752110189_549294_1371469387_e5db5bf1f65f79d2fa72628436190561.jpg temp/1752110189_549294_1371469384_f4e71e445817c86bcfa5ab2608f43632.jpg temp/1752110189_549294_1371469377_160c60c5a248a6d1660a87b2398d9791.jpg temp/1752110189_549294_1371469358_008dedeac3130b0205c2b18b27fa8db7.jpg temp/1752110189_549294_1371469352_41f20e6ade7f218e43e4915d55e6a730.jpg temp/1752110189_549294_1371469349_bcfb001eed35e30e75f3c168096d26a7.jpg Found 24 images belonging to 1 classes. begin to do the prediction : time used to do the prediction : 2.713937997817993 (24,) (24, 5) (24, 2048) shape of features : (24, 2048) shape of new features : (1, 24, 2048) save descriptor for thcl : 3513 time to traite the descriptors : 0.12770605087280273 storage_type for insertDescriptorsMulti : 3 To insert : 1371470513 To insert : 1371470509 To insert : 1371470505 To insert : 1371470501 To insert : 1371470493 To insert : 1371470482 To insert : 1371470450 To insert : 1371470448 To insert : 1371470444 To insert : 1371470441 To insert : 1371470432 To insert : 1371470428 To insert : 1371469824 To insert : 1371469822 To insert : 1371469819 To insert : 1371469807 To insert : 1371469801 To insert : 1371469794 To insert : 1371469387 To insert : 1371469384 To insert : 1371469377 To insert : 1371469358 To insert : 1371469352 To insert : 1371469349 time to insert the descriptors : 5.260162115097046 tagging for thcl : 3379 To do loadFromThcl(), then load ParamDescType : thcl3379 thcls : [{'id': 3379, 'mtr_user_id': 31, 'name': 'learn_classif_flux_maj_generique_effnet_v2_s_02062022', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'aluminium,ela,film_pedb,flux_dev,jrm,pcm,pcnc,pehd_pp,pet_clair,refus,tapis_vide', 'svm_portfolios_learning': '5515864,5515840,5515844,5515850,6244400,6237996,6237998,5515847,5515841,5515868,5515866', 'photo_hashtag_type': 4374, 'photo_desc_type': 5680, 'type_classification': 'tf_classification2', 'hashtag_id_list': '493546845,492741797,2107760237,2107760238,495916461,560181804,1284539308,2107760239,2107755846,538914404,2107748999'}] thcl {'id': 3379, 'mtr_user_id': 31, 'name': 'learn_classif_flux_maj_generique_effnet_v2_s_02062022', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'aluminium,ela,film_pedb,flux_dev,jrm,pcm,pcnc,pehd_pp,pet_clair,refus,tapis_vide', 'svm_portfolios_learning': '5515864,5515840,5515844,5515850,6244400,6237996,6237998,5515847,5515841,5515868,5515866', 'photo_hashtag_type': 4374, 'photo_desc_type': 5680, 'type_classification': 'tf_classification2', 'hashtag_id_list': '493546845,492741797,2107760237,2107760238,495916461,560181804,1284539308,2107760239,2107755846,538914404,2107748999'} Update svm_hashtag_type_desc : 5680 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (5680, 'learn_classif_flux_maj_generique_effnet_v2_s_02062022', 1280, 1280, 'learn_classif_flux_maj_generique_effnet_v2_s_02062022', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2022, 6, 4, 1, 31, 10), datetime.datetime(2022, 6, 4, 1, 31, 10)) model_name : learn_classif_flux_maj_generique_effnet_v2_s_02062022 model_param file didn't exist model_name : learn_classif_flux_maj_generique_effnet_v2_s_02062022 model_type : tf_classification2 list file need : ['Confusion_Matrix.png', 'Precision_Recall_aluminium.jpg', 'Precision_Recall_ela.jpg', 'Precision_Recall_film_pedb.jpg', 'Precision_Recall_flux_dev.jpg', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd_pp.jpg', 'Precision_Recall_pet_clair.jpg', 'Precision_Recall_refus.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file exist in s3 : ['Confusion_Matrix.png', 'Precision_Recall_aluminium.jpg', 'Precision_Recall_ela.jpg', 'Precision_Recall_film_pedb.jpg', 'Precision_Recall_flux_dev.jpg', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd_pp.jpg', 'Precision_Recall_pet_clair.jpg', 'Precision_Recall_refus.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00002', 'model_checkpoint.ckpt.data-00001-of-00002', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file manque in s3 : [] local folder : /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022 /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Confusion_Matrix.png size_local : 82527 size in s3 : 82527 create time local : 2022-06-06 13:01:24 create time in s3 : 2022-06-03 23:31:09 Confusion_Matrix.png already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_aluminium.jpg size_local : 67602 size in s3 : 67602 create time local : 2022-06-06 13:01:24 create time in s3 : 2022-06-03 23:23:41 Precision_Recall_aluminium.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_ela.jpg size_local : 67189 size in s3 : 67189 create time local : 2022-06-06 13:01:25 create time in s3 : 2022-06-03 23:26:13 Precision_Recall_ela.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_film_pedb.jpg size_local : 71280 size in s3 : 71280 create time local : 2022-06-06 13:01:25 create time in s3 : 2022-06-03 23:26:14 Precision_Recall_film_pedb.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_flux_dev.jpg size_local : 59936 size in s3 : 59936 create time local : 2022-06-06 13:01:25 create time in s3 : 2022-06-03 23:23:41 Precision_Recall_flux_dev.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_jrm.jpg size_local : 67657 size in s3 : 67657 create time local : 2022-06-06 13:01:25 create time in s3 : 2022-06-03 23:31:06 Precision_Recall_jrm.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_pcm.jpg size_local : 83042 size in s3 : 83042 create time local : 2022-06-06 13:01:25 create time in s3 : 2022-06-03 23:23:40 Precision_Recall_pcm.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_pcnc.jpg size_local : 69972 size in s3 : 69972 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:31:05 Precision_Recall_pcnc.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_pehd_pp.jpg size_local : 67313 size in s3 : 67313 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:23:45 Precision_Recall_pehd_pp.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_pet_clair.jpg size_local : 67320 size in s3 : 67320 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:31:04 Precision_Recall_pet_clair.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_refus.jpg size_local : 59936 size in s3 : 59936 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:31:08 Precision_Recall_refus.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Precision_Recall_tapis_vide.jpg size_local : 80244 size in s3 : 80244 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:23:45 Precision_Recall_tapis_vide.jpg already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/Result_Summary.txt size_local : 1018 size in s3 : 1018 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:31:08 Result_Summary.txt already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/checkpoint size_local : 99 size in s3 : 99 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:31:06 checkpoint already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/model_checkpoint.ckpt.data-00000-of-00002 size_local : 216640 size in s3 : 216640 create time local : 2022-06-06 13:01:27 create time in s3 : 2022-06-03 23:23:43 model_checkpoint.ckpt.data-00000-of-00002 already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/model_checkpoint.ckpt.data-00001-of-00002 size_local : 32341196 size in s3 : 32341196 create time local : 2022-06-06 13:01:28 create time in s3 : 2022-06-03 23:26:15 model_checkpoint.ckpt.data-00001-of-00002 already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/model_checkpoint.ckpt.index size_local : 43546 size in s3 : 43546 create time local : 2022-06-06 13:01:28 create time in s3 : 2022-06-03 23:26:13 model_checkpoint.ckpt.index already exist and didn't need to update /data/models_weight/learn_classif_flux_maj_generique_effnet_v2_s_02062022/model_weights.h5 size_local : 16531224 size in s3 : 16531224 create time local : 2022-06-06 13:01:29 create time in s3 : 2022-06-03 23:23:46 model_weights.h5 already exist and didn't need to update desc size : 1280 Model: "sequential" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= module (KerasLayer) (None, 1280) 4049564 _________________________________________________________________ learn_classif_flux_maj_gener (None, 11) 14091 ================================================================= Total params: 4,063,655 Trainable params: 14,091 Non-trainable params: 4,049,564 _________________________________________________________________ Loading Weights... time used to create the model : 6.827563047409058 time used to load_weights : 0.14095354080200195 0it [00:00, ?it/s] 24it [00:00, 1846.66it/s]temp/1752110189_549294_1371470513_21397e931b2f20ee0fd7a00d09a56861.jpg temp/1752110189_549294_1371470509_fc800a5415b48fd32f6f59e5708de262.jpg temp/1752110189_549294_1371470505_a97b45a10a39fa73c3dfb14127a614f9.jpg temp/1752110189_549294_1371470501_e0a4a49e72d0ed6f5fcf3377ebf09716.jpg temp/1752110189_549294_1371470493_c50dd37d209f28a7ab889e30fc85dd8e.jpg temp/1752110189_549294_1371470482_da8da65bf11540b5c799787724dde1ef.jpg temp/1752110189_549294_1371470450_7c9192636225c595f742620a26c0ed12.jpg temp/1752110189_549294_1371470448_642933bc9d28a783114b4c61c32b29ca.jpg temp/1752110189_549294_1371470444_231d43d93996baa57120cc3b429c0401.jpg temp/1752110189_549294_1371470441_e9e858e26ee34a0db2515730e2867188.jpg temp/1752110189_549294_1371470432_d50c90a5f43bb5ed44629f84f5cf8742.jpg temp/1752110189_549294_1371470428_023eedbaeb2cc829ea5baa598184c17a.jpg temp/1752110189_549294_1371469824_d33f1d75b99a55320cf6d282502a1a6c.jpg temp/1752110189_549294_1371469822_a68d82094927b24da9c6a2dd8c23acae.jpg temp/1752110189_549294_1371469819_8d7584e9d823dd27aed13e453f2d035d.jpg temp/1752110189_549294_1371469807_a81b632bb541c1673fb03d1900dfede3.jpg temp/1752110189_549294_1371469801_334ed5dcd05f462ac1d917e88f0599ac.jpg temp/1752110189_549294_1371469794_575b385b3df7dd8a49bf624a8edd4723.jpg temp/1752110189_549294_1371469387_e5db5bf1f65f79d2fa72628436190561.jpg temp/1752110189_549294_1371469384_f4e71e445817c86bcfa5ab2608f43632.jpg temp/1752110189_549294_1371469377_160c60c5a248a6d1660a87b2398d9791.jpg temp/1752110189_549294_1371469358_008dedeac3130b0205c2b18b27fa8db7.jpg temp/1752110189_549294_1371469352_41f20e6ade7f218e43e4915d55e6a730.jpg temp/1752110189_549294_1371469349_bcfb001eed35e30e75f3c168096d26a7.jpg Found 24 images belonging to 1 classes. begin to do the prediction : time used to do the prediction : 1.459892988204956 (24,) (24, 11) (24, 1280) shape of features : (24, 1280) shape of new features : (1, 24, 1280) save descriptor for thcl : 3379 time to traite the descriptors : 0.12851309776306152 storage_type for insertDescriptorsMulti : 3 To insert : 1371470513 To insert : 1371470509 To insert : 1371470505 To insert : 1371470501 To insert : 1371470493 To insert : 1371470482 To insert : 1371470450 To insert : 1371470448 To insert : 1371470444 To insert : 1371470441 To insert : 1371470432 To insert : 1371470428 To insert : 1371469824 To insert : 1371469822 To insert : 1371469819 To insert : 1371469807 To insert : 1371469801 To insert : 1371469794 To insert : 1371469387 To insert : 1371469384 To insert : 1371469377 To insert : 1371469358 To insert : 1371469352 To insert : 1371469349 time to insert the descriptors : 4.705341577529907 tagging for thcl : 3847 To do loadFromThcl(), then load ParamDescType : thcl3847 thcls : [{'id': 3847, 'mtr_user_id': 31, 'name': 'learn_MM_generique_050224', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'aluminium,ela,emr,film_pedb,flux_dev,jrm,pcm,pcnc,pehd_pp,pet_clair,refus,tapis_vide', 'svm_portfolios_learning': '13096157,13096155,13096163,13096159,13301956,13095886,13096162,13096160,13358264,13096158,5515868,13276803', 'photo_hashtag_type': 4932, 'photo_desc_type': 6032, 'type_classification': 'tf_classification2', 'hashtag_id_list': '493546845,492741797,616987804,2107760237,2107760238,495916461,560181804,1284539308,2107760239,2107755846,538914404,2107748999'}] thcl {'id': 3847, 'mtr_user_id': 31, 'name': 'learn_MM_generique_050224', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'aluminium,ela,emr,film_pedb,flux_dev,jrm,pcm,pcnc,pehd_pp,pet_clair,refus,tapis_vide', 'svm_portfolios_learning': '13096157,13096155,13096163,13096159,13301956,13095886,13096162,13096160,13358264,13096158,5515868,13276803', 'photo_hashtag_type': 4932, 'photo_desc_type': 6032, 'type_classification': 'tf_classification2', 'hashtag_id_list': '493546845,492741797,616987804,2107760237,2107760238,495916461,560181804,1284539308,2107760239,2107755846,538914404,2107748999'} Update svm_hashtag_type_desc : 6032 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (6032, 'learn_MM_generique_050224', 1280, 1280, 'learn_MM_generique_050224', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 3, datetime.datetime(2024, 2, 5, 21, 42, 4), datetime.datetime(2024, 2, 5, 21, 42, 4)) model_name : learn_MM_generique_050224 model_param file didn't exist model_name : learn_MM_generique_050224 model_type : tf_classification2 list file need : ['Confusion_Matrix.png', 'Precision_Recall_aluminium.jpg', 'Precision_Recall_ela.jpg', 'Precision_Recall_emr.jpg', 'Precision_Recall_film_pedb.jpg', 'Precision_Recall_flux_dev.jpg', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd_pp.jpg', 'Precision_Recall_pet_clair.jpg', 'Precision_Recall_refus.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00001', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file exist in s3 : ['Confusion_Matrix.png', 'Precision_Recall_aluminium.jpg', 'Precision_Recall_ela.jpg', 'Precision_Recall_emr.jpg', 'Precision_Recall_film_pedb.jpg', 'Precision_Recall_flux_dev.jpg', 'Precision_Recall_jrm.jpg', 'Precision_Recall_pcm.jpg', 'Precision_Recall_pcnc.jpg', 'Precision_Recall_pehd_pp.jpg', 'Precision_Recall_pet_clair.jpg', 'Precision_Recall_refus.jpg', 'Precision_Recall_tapis_vide.jpg', 'Result_Summary.txt', 'checkpoint', 'model_checkpoint.ckpt.data-00000-of-00001', 'model_checkpoint.ckpt.index', 'model_weights.h5'] file manque in s3 : [] local folder : /data/models_weight/learn_MM_generique_050224 /data/models_weight/learn_MM_generique_050224/Confusion_Matrix.png size_local : 88145 size in s3 : 88145 create time local : 2024-04-08 09:17:48 create time in s3 : 2024-02-05 20:41:54 Confusion_Matrix.png already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_aluminium.jpg size_local : 67983 size in s3 : 67983 create time local : 2024-04-08 09:17:48 create time in s3 : 2024-02-05 20:42:02 Precision_Recall_aluminium.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_ela.jpg size_local : 68484 size in s3 : 68484 create time local : 2024-04-08 09:17:48 create time in s3 : 2024-02-05 20:42:04 Precision_Recall_ela.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_emr.jpg size_local : 77930 size in s3 : 77930 create time local : 2024-04-08 09:17:48 create time in s3 : 2024-02-05 20:41:55 Precision_Recall_emr.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_film_pedb.jpg size_local : 66701 size in s3 : 66701 create time local : 2024-04-08 09:17:48 create time in s3 : 2024-02-05 20:41:55 Precision_Recall_film_pedb.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_flux_dev.jpg size_local : 59936 size in s3 : 59936 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:04 Precision_Recall_flux_dev.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_jrm.jpg size_local : 72890 size in s3 : 72890 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:04 Precision_Recall_jrm.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_pcm.jpg size_local : 93916 size in s3 : 93916 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:02 Precision_Recall_pcm.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_pcnc.jpg size_local : 74701 size in s3 : 74701 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:04 Precision_Recall_pcnc.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_pehd_pp.jpg size_local : 68765 size in s3 : 68765 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:03 Precision_Recall_pehd_pp.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_pet_clair.jpg size_local : 69649 size in s3 : 69649 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:03 Precision_Recall_pet_clair.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_refus.jpg size_local : 59936 size in s3 : 59936 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:41:59 Precision_Recall_refus.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Precision_Recall_tapis_vide.jpg size_local : 71529 size in s3 : 71529 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:41:54 Precision_Recall_tapis_vide.jpg already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/Result_Summary.txt size_local : 1076 size in s3 : 1076 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:41:55 Result_Summary.txt already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/checkpoint size_local : 99 size in s3 : 99 create time local : 2024-04-08 09:17:49 create time in s3 : 2024-02-05 20:42:00 checkpoint already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/model_checkpoint.ckpt.data-00000-of-00001 size_local : 32591049 size in s3 : 32591049 create time local : 2024-04-08 09:17:50 create time in s3 : 2024-02-05 20:42:02 model_checkpoint.ckpt.data-00000-of-00001 already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/model_checkpoint.ckpt.index size_local : 42495 size in s3 : 42495 create time local : 2024-04-08 09:17:50 create time in s3 : 2024-02-05 20:41:55 model_checkpoint.ckpt.index already exist and didn't need to update /data/models_weight/learn_MM_generique_050224/model_weights.h5 size_local : 16536200 size in s3 : 16536200 create time local : 2024-04-08 09:17:50 create time in s3 : 2024-02-05 20:42:00 model_weights.h5 already exist and didn't need to update desc size : 1280 Model: "sequential" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= module (KerasLayer) (None, 1280) 4049564 _________________________________________________________________ learn_MM_generique_050224den (None, 12) 15372 ================================================================= Total params: 4,064,936 Trainable params: 15,372 Non-trainable params: 4,049,564 _________________________________________________________________ Loading Weights... time used to create the model : 6.842910051345825 time used to load_weights : 0.12415742874145508 0it [00:00, ?it/s] 24it [00:00, 1727.38it/s]temp/1752110189_549294_1371470513_21397e931b2f20ee0fd7a00d09a56861.jpg temp/1752110189_549294_1371470509_fc800a5415b48fd32f6f59e5708de262.jpg temp/1752110189_549294_1371470505_a97b45a10a39fa73c3dfb14127a614f9.jpg temp/1752110189_549294_1371470501_e0a4a49e72d0ed6f5fcf3377ebf09716.jpg temp/1752110189_549294_1371470493_c50dd37d209f28a7ab889e30fc85dd8e.jpg temp/1752110189_549294_1371470482_da8da65bf11540b5c799787724dde1ef.jpg temp/1752110189_549294_1371470450_7c9192636225c595f742620a26c0ed12.jpg temp/1752110189_549294_1371470448_642933bc9d28a783114b4c61c32b29ca.jpg temp/1752110189_549294_1371470444_231d43d93996baa57120cc3b429c0401.jpg temp/1752110189_549294_1371470441_e9e858e26ee34a0db2515730e2867188.jpg temp/1752110189_549294_1371470432_d50c90a5f43bb5ed44629f84f5cf8742.jpg temp/1752110189_549294_1371470428_023eedbaeb2cc829ea5baa598184c17a.jpg temp/1752110189_549294_1371469824_d33f1d75b99a55320cf6d282502a1a6c.jpg temp/1752110189_549294_1371469822_a68d82094927b24da9c6a2dd8c23acae.jpg temp/1752110189_549294_1371469819_8d7584e9d823dd27aed13e453f2d035d.jpg temp/1752110189_549294_1371469807_a81b632bb541c1673fb03d1900dfede3.jpg temp/1752110189_549294_1371469801_334ed5dcd05f462ac1d917e88f0599ac.jpg temp/1752110189_549294_1371469794_575b385b3df7dd8a49bf624a8edd4723.jpg temp/1752110189_549294_1371469387_e5db5bf1f65f79d2fa72628436190561.jpg temp/1752110189_549294_1371469384_f4e71e445817c86bcfa5ab2608f43632.jpg temp/1752110189_549294_1371469377_160c60c5a248a6d1660a87b2398d9791.jpg temp/1752110189_549294_1371469358_008dedeac3130b0205c2b18b27fa8db7.jpg temp/1752110189_549294_1371469352_41f20e6ade7f218e43e4915d55e6a730.jpg temp/1752110189_549294_1371469349_bcfb001eed35e30e75f3c168096d26a7.jpg Found 24 images belonging to 1 classes. begin to do the prediction : time used to do the prediction : 1.252561330795288 (24,) (24, 12) (24, 1280) shape of features : (24, 1280) shape of new features : (1, 24, 1280) save descriptor for thcl : 3847 time to traite the descriptors : 0.12144327163696289 storage_type for insertDescriptorsMulti : 3 To insert : 1371470513 To insert : 1371470509 To insert : 1371470505 To insert : 1371470501 To insert : 1371470493 To insert : 1371470482 To insert : 1371470450 To insert : 1371470448 To insert : 1371470444 To insert : 1371470441 To insert : 1371470432 To insert : 1371470428 To insert : 1371469824 To insert : 1371469822 To insert : 1371469819 To insert : 1371469807 To insert : 1371469801 To insert : 1371469794 To insert : 1371469387 To insert : 1371469384 To insert : 1371469377 To insert : 1371469358 To insert : 1371469352 To insert : 1371469349 time to insert the descriptors : 4.551229000091553 Inside saveOutput : final : False verbose : 0 saveOutput not yet implemented for datou_step.type : tfhub_classification2 we use saveGeneral [1371470513, 1371470509, 1371470505, 1371470501, 1371470493, 1371470482, 1371470450, 1371470448, 1371470444, 1371470441, 1371470432, 1371470428, 1371469824, 1371469822, 1371469819, 1371469807, 1371469801, 1371469794, 1371469387, 1371469384, 1371469377, 1371469358, 1371469352, 1371469349] Looping around the photos to save general results len do output : 24 /1371470513Didn't retrieve data . /1371470509Didn't retrieve data . /1371470505Didn't retrieve data . /1371470501Didn't retrieve data . /1371470493Didn't retrieve data . /1371470482Didn't retrieve data . /1371470450Didn't retrieve data . /1371470448Didn't retrieve data . /1371470444Didn't retrieve data . /1371470441Didn't retrieve data . /1371470432Didn't retrieve data . /1371470428Didn't retrieve data . /1371469824Didn't retrieve data . /1371469822Didn't retrieve data . /1371469819Didn't retrieve data . /1371469807Didn't retrieve data . /1371469801Didn't retrieve data . /1371469794Didn't retrieve data . /1371469387Didn't retrieve data . /1371469384Didn't retrieve data . /1371469377Didn't retrieve data . /1371469358Didn't retrieve data . /1371469352Didn't retrieve data . /1371469349Didn't retrieve data . before output type Here is an output not treated by saveGeneral : Managing all output in save final without adding information in the mtr_datou_result ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470513', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470509', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470505', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470501', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470493', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470482', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470450', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470448', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470444', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470441', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470432', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371470428', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469824', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469822', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469819', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469807', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469801', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469794', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469387', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469384', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469377', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469358', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469352', None, None, None, None, None, '3239078') ('533', None, None, None, None, None, None, None, '3239078') ('533', '24628097', '1371469349', None, None, None, None, None, '3239078') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 48 time used for this insertion : 0.018862009048461914 save_final save missing photos in datou_result : time spend for datou_step_exec : 50.404531478881836 time spend to save output : 0.020197629928588867 total time spend for step 1 : 50.424729108810425 step2:argmax Thu Jul 10 03:17:23 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Currently we do not manage missing dependencies information, that could maybe be correctly interpreted with default behavior Some of the step done at execution of the step could be done before when the tree of execution is build and the dependencies of different step analysed complete output_args for input 0 VR 22-3-18 : For now we do not clean correctly the datou structure Beginning of datou_step Argmax ! Inside saveOutput : final : True verbose : 0 photo_id : 1371470513 output[photo_id] : [[(1371470513, '05102018_Papier_non_papier_presque_vide', 0.5175589, 4557, 3513), (1371470513, 'jrm', 0.67559123, 4374, 3379), (1371470513, 'tapis_vide', 0.21365425, 4932, 3847)], 'temp/1752110189_549294_1371470513_21397e931b2f20ee0fd7a00d09a56861.jpg'] photo_id : 1371470509 output[photo_id] : [[(1371470509, '05102018_Papier_non_papier_tres_dense', 0.54749423, 4557, 3513), (1371470509, 'jrm', 0.708231, 4374, 3379), (1371470509, 'jrm', 0.27716565, 4932, 3847)], 'temp/1752110189_549294_1371470509_fc800a5415b48fd32f6f59e5708de262.jpg'] photo_id : 1371470505 output[photo_id] : [[(1371470505, '05102018_Papier_non_papier_tres_dense', 0.50712144, 4557, 3513), (1371470505, 'jrm', 0.68100053, 4374, 3379), (1371470505, 'jrm', 0.21965091, 4932, 3847)], 'temp/1752110189_549294_1371470505_a97b45a10a39fa73c3dfb14127a614f9.jpg'] photo_id : 1371470501 output[photo_id] : [[(1371470501, '05102018_Papier_non_papier_tres_dense', 0.48121068, 4557, 3513), (1371470501, 'jrm', 0.68977594, 4374, 3379), (1371470501, 'jrm', 0.24363352, 4932, 3847)], 'temp/1752110189_549294_1371470501_e0a4a49e72d0ed6f5fcf3377ebf09716.jpg'] photo_id : 1371470493 output[photo_id] : [[(1371470493, '05102018_Papier_non_papier_tres_dense', 0.48283365, 4557, 3513), (1371470493, 'jrm', 0.76372397, 4374, 3379), (1371470493, 'jrm', 0.2616922, 4932, 3847)], 'temp/1752110189_549294_1371470493_c50dd37d209f28a7ab889e30fc85dd8e.jpg'] photo_id : 1371470482 output[photo_id] : [[(1371470482, '05102018_Papier_non_papier_tres_dense', 0.6563527, 4557, 3513), (1371470482, 'jrm', 0.6048027, 4374, 3379), (1371470482, 'aluminium', 0.1828034, 4932, 3847)], 'temp/1752110189_549294_1371470482_da8da65bf11540b5c799787724dde1ef.jpg'] photo_id : 1371470450 output[photo_id] : [[(1371470450, '05102018_Papier_non_papier_presque_vide', 0.5542058, 4557, 3513), (1371470450, 'jrm', 0.8145563, 4374, 3379), (1371470450, 'tapis_vide', 0.36357072, 4932, 3847)], 'temp/1752110189_549294_1371470450_7c9192636225c595f742620a26c0ed12.jpg'] photo_id : 1371470448 output[photo_id] : [[(1371470448, '05102018_Papier_non_papier_tres_dense', 0.446227, 4557, 3513), (1371470448, 'jrm', 0.8562365, 4374, 3379), (1371470448, 'tapis_vide', 0.3686629, 4932, 3847)], 'temp/1752110189_549294_1371470448_642933bc9d28a783114b4c61c32b29ca.jpg'] photo_id : 1371470444 output[photo_id] : [[(1371470444, '05102018_Papier_non_papier_tres_dense', 0.5016618, 4557, 3513), (1371470444, 'jrm', 0.7387306, 4374, 3379), (1371470444, 'film_pedb', 0.2317281, 4932, 3847)], 'temp/1752110189_549294_1371470444_231d43d93996baa57120cc3b429c0401.jpg'] photo_id : 1371470441 output[photo_id] : [[(1371470441, '05102018_Papier_non_papier_tres_dense', 0.5677152, 4557, 3513), (1371470441, 'jrm', 0.7248681, 4374, 3379), (1371470441, 'tapis_vide', 0.22112967, 4932, 3847)], 'temp/1752110189_549294_1371470441_e9e858e26ee34a0db2515730e2867188.jpg'] photo_id : 1371470432 output[photo_id] : [[(1371470432, '05102018_Papier_non_papier_presque_vide', 0.5897474, 4557, 3513), (1371470432, 'jrm', 0.7154712, 4374, 3379), (1371470432, 'tapis_vide', 0.28322235, 4932, 3847)], 'temp/1752110189_549294_1371470432_d50c90a5f43bb5ed44629f84f5cf8742.jpg'] photo_id : 1371470428 output[photo_id] : [[(1371470428, '05102018_Papier_non_papier_tres_dense', 0.55998504, 4557, 3513), (1371470428, 'jrm', 0.6399539, 4374, 3379), (1371470428, 'tapis_vide', 0.26475707, 4932, 3847)], 'temp/1752110189_549294_1371470428_023eedbaeb2cc829ea5baa598184c17a.jpg'] photo_id : 1371469824 output[photo_id] : [[(1371469824, '05102018_Papier_non_papier_tres_dense', 0.54909456, 4557, 3513), (1371469824, 'jrm', 0.67852294, 4374, 3379), (1371469824, 'tapis_vide', 0.22086105, 4932, 3847)], 'temp/1752110189_549294_1371469824_d33f1d75b99a55320cf6d282502a1a6c.jpg'] photo_id : 1371469822 output[photo_id] : [[(1371469822, '05102018_Papier_non_papier_tres_dense', 0.5496243, 4557, 3513), (1371469822, 'jrm', 0.46880856, 4374, 3379), (1371469822, 'pet_clair', 0.16614446, 4932, 3847)], 'temp/1752110189_549294_1371469822_a68d82094927b24da9c6a2dd8c23acae.jpg'] photo_id : 1371469819 output[photo_id] : [[(1371469819, '05102018_Papier_non_papier_tres_dense', 0.49951297, 4557, 3513), (1371469819, 'jrm', 0.4781955, 4374, 3379), (1371469819, 'pet_clair', 0.1983012, 4932, 3847)], 'temp/1752110189_549294_1371469819_8d7584e9d823dd27aed13e453f2d035d.jpg'] photo_id : 1371469807 output[photo_id] : [[(1371469807, '05102018_Papier_non_papier_presque_vide', 0.49356434, 4557, 3513), (1371469807, 'jrm', 0.6944006, 4374, 3379), (1371469807, 'jrm', 0.15716444, 4932, 3847)], 'temp/1752110189_549294_1371469807_a81b632bb541c1673fb03d1900dfede3.jpg'] photo_id : 1371469801 output[photo_id] : [[(1371469801, '05102018_Papier_non_papier_presque_vide', 0.47844088, 4557, 3513), (1371469801, 'jrm', 0.8273462, 4374, 3379), (1371469801, 'tapis_vide', 0.37174076, 4932, 3847)], 'temp/1752110189_549294_1371469801_334ed5dcd05f462ac1d917e88f0599ac.jpg'] photo_id : 1371469794 output[photo_id] : [[(1371469794, '05102018_Papier_non_papier_tres_dense', 0.43909255, 4557, 3513), (1371469794, 'jrm', 0.89029074, 4374, 3379), (1371469794, 'tapis_vide', 0.27830428, 4932, 3847)], 'temp/1752110189_549294_1371469794_575b385b3df7dd8a49bf624a8edd4723.jpg'] photo_id : 1371469387 output[photo_id] : [[(1371469387, '05102018_Papier_non_papier_tres_dense', 0.52842957, 4557, 3513), (1371469387, 'jrm', 0.87360114, 4374, 3379), (1371469387, 'tapis_vide', 0.3319727, 4932, 3847)], 'temp/1752110189_549294_1371469387_e5db5bf1f65f79d2fa72628436190561.jpg'] photo_id : 1371469384 output[photo_id] : [[(1371469384, '05102018_Papier_non_papier_presque_vide', 0.4520141, 4557, 3513), (1371469384, 'jrm', 0.8507965, 4374, 3379), (1371469384, 'jrm', 0.30147275, 4932, 3847)], 'temp/1752110189_549294_1371469384_f4e71e445817c86bcfa5ab2608f43632.jpg'] photo_id : 1371469377 output[photo_id] : [[(1371469377, '05102018_Papier_non_papier_tres_dense', 0.5036405, 4557, 3513), (1371469377, 'jrm', 0.79146296, 4374, 3379), (1371469377, 'tapis_vide', 0.29861867, 4932, 3847)], 'temp/1752110189_549294_1371469377_160c60c5a248a6d1660a87b2398d9791.jpg'] photo_id : 1371469358 output[photo_id] : [[(1371469358, '05102018_Papier_non_papier_tres_dense', 0.62582904, 4557, 3513), (1371469358, 'jrm', 0.58216625, 4374, 3379), (1371469358, 'film_pedb', 0.23277713, 4932, 3847)], 'temp/1752110189_549294_1371469358_008dedeac3130b0205c2b18b27fa8db7.jpg'] photo_id : 1371469352 output[photo_id] : [[(1371469352, '05102018_Papier_non_papier_tres_dense', 0.54188275, 4557, 3513), (1371469352, 'jrm', 0.8424756, 4374, 3379), (1371469352, 'jrm', 0.26024106, 4932, 3847)], 'temp/1752110189_549294_1371469352_41f20e6ade7f218e43e4915d55e6a730.jpg'] photo_id : 1371469349 output[photo_id] : [[(1371469349, '05102018_Papier_non_papier_tres_dense', 0.5469685, 4557, 3513), (1371469349, 'jrm', 0.84207624, 4374, 3379), (1371469349, 'jrm', 0.22395636, 4932, 3847)], 'temp/1752110189_549294_1371469349_bcfb001eed35e30e75f3c168096d26a7.jpg'] begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 72 time used for this insertion : 0.01760101318359375 begin to insert list_values into class_photo_scores : length of list_valuse in save_photo_hashtag_id_thcl_score : 72 time used for this insertion : 0.016904592514038086 len list_finale : 72, len picture : 24 begin to insert list_values into mtr_datou_result : length of list_values in save_final : 72 time used for this insertion : 0.015974760055541992 saving photo_ids in datou_result begin to insert list_values into mtr_datou_result : length of list_values in save_final : 24 time used for this insertion : 0.015923261642456055 save missing photos in datou_result : time spend for datou_step_exec : 0.020627975463867188 time spend to save output : 0.09544110298156738 total time spend for step 2 : 0.11606907844543457 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 24 set_done_treatment 32.92user 5.76system 0:58.89elapsed 65%CPU (0avgtext+0avgdata 2837964maxresident)k 99544inputs+82888outputs (309major+1347467minor)pagefaults 0swaps