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 : 3689096 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 : 3908>100 please execute split_portfolio.py -i 24113525 -l 100 size over we load limit photo not treated list_input_json: {} Current got : datou_id : 533, datou_cur_ids : ['3150707'] with mtr_portfolio_ids : ['24113525'] and first list_photo_ids : [] new path : /proc/3689096/ 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 ! BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 100 ; length of list_pids : 100 ; length of list_args : 100 time to download the photos : 15.396026611328125 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 Tue Aug 19 19:31:44 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 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 2025-08-19 19:31:47.135708: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-08-19 19:31:47.166259: 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 2025-08-19 19:31:47.166792: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-08-19 19:31:47.170428: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-08-19 19:31:47.173409: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-08-19 19:31:47.174768: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-08-19 19:31:47.178952: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-08-19 19:31:47.180785: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-08-19 19:31:47.188710: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-08-19 19:31:47.190260: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-08-19 19:31:47.190729: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-08-19 19:31:47.216665: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3492910000 Hz 2025-08-19 19:31:47.218897: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f2e80000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-08-19 19:31:47.218945: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-08-19 19:31:47.340202: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x17e34a80 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-08-19 19:31:47.340269: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-08-19 19:31:47.341612: 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 2025-08-19 19:31:47.341723: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-08-19 19:31:47.341760: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-08-19 19:31:47.341793: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-08-19 19:31:47.341825: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-08-19 19:31:47.341856: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-08-19 19:31:47.341888: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-08-19 19:31:47.341922: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-08-19 19:31:47.343613: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-08-19 19:31:47.343685: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-08-19 19:31:47.344780: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-08-19 19:31:47.344813: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-08-19 19:31:47.344827: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-08-19 19:31:47.346652: 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 : 5104 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 : 8.010353803634644 time used to load_weights : 0.20080161094665527 0it [00:00, ?it/s] 100it [00:00, 1175.03it/s]2025-08-19 19:31:57.948851: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-08-19 19:31:58.393587: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-08-19 19:32:04.759438: W tensorflow/core/framework/op_kernel.cc:1741] Unknown: OSError: image file is truncated (48 bytes not processed) Traceback (most recent call last): File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/script_ops.py", line 243, in __call__ ret = func(*args) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/impl/api.py", line 309, in wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 785, in generator_py_func values = next(generator_state.get_iterator(iterator_id)) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 801, in wrapped_generator for data in generator_fn(): File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 932, in generator_fn yield x[i] File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/iterator.py", line 65, in __getitem__ return self._get_batches_of_transformed_samples(index_array) File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/iterator.py", line 227, in _get_batches_of_transformed_samples img = load_img(filepaths[j], File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/utils.py", line 138, in load_img img = img.resize(width_height_tuple, resample) File "/home/admin/.local/lib/python3.8/site-packages/PIL/Image.py", line 2157, in resize self.load() File "/home/admin/.local/lib/python3.8/site-packages/PIL/ImageFile.py", line 266, in load raise OSError(msg) OSError: image file is truncated (48 bytes not processed) temp/1755624688_3689096_1377038279_cc1e5811b8f0f6d7a8d583af3d9f51bb.jpg temp/1755624688_3689096_1377038275_0753f53b2835d8738d6a5cf7c0eb22f0.jpg temp/1755624688_3689096_1377038273_fbe19b5273704098e598831b0ae4018d.jpg temp/1755624688_3689096_1377038269_376587cb645b804ddf9994ada7d1d9aa.jpg temp/1755624688_3689096_1377038268_8c858584347756e00547fc6a5e31e35c.jpg temp/1755624688_3689096_1377038267_5ab734d5b479cdef6203a325ef702635.jpg temp/1755624688_3689096_1372556472_b42e4fc92ed4b6948d73808f8584124a.jpg temp/1755624688_3689096_1372556467_ba53261ed6688e77bc8594c387bcb8b1.jpg temp/1755624688_3689096_1372556464_e5bb58052dedcc3f0d5e93ce4b923926.jpg temp/1755624688_3689096_1372556460_8e8c7660a8a9b8b99441855f74a92449.jpg temp/1755624688_3689096_1372556377_225a92e57638e4bb44bb9d4514981287.jpg temp/1755624688_3689096_1372556352_5aee1c242635aa4ceff865af0141d5b6.jpg temp/1755624688_3689096_1372556327_8b68f6663a9f3c1e4580aceb674f8c7b.jpg temp/1755624688_3689096_1372556301_0a5e9c337f26864bd3cde2d37d2a2a87.jpg temp/1755624688_3689096_1372556268_954245df4fbbfe790f14a7f36b685e30.jpg temp/1755624688_3689096_1372556237_4596c23da6f61e617c50b452f70da344.jpg temp/1755624688_3689096_1372553752_cf69d1604636dc29ae930b343e1667db.jpg temp/1755624688_3689096_1372553732_57ef73378cb9ccb50ed07791dfd35df0.jpg temp/1755624688_3689096_1372553701_a60d911cac43590f2d9fe0fe665e80a3.jpg temp/1755624688_3689096_1372553670_32948aeb7c0adc14c4b783a2c04d7375.jpg temp/1755624688_3689096_1372553640_de7f8fb10bf4d79a95d2b265c3687f7b.jpg temp/1755624688_3689096_1372553604_d2f28e3ac14b6b592537d174dc8a3f1e.jpg temp/1755624688_3689096_1372553364_55234b89f376c781d1e5d202435532db.jpg 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temp/1755624688_3689096_1369538669_93b8d1fedfdd8a6811ff773e4bb55ffe_41008481.jpg temp/1755624688_3689096_1369538668_11c21a3ce4ed07d5aeb407c23db2112c_33564334.jpg temp/1755624688_3689096_1369538666_10fecb8ba056998422decfcbc4fd83ba_63352158.jpg temp/1755624688_3689096_1369538665_29b956acedce5dee643fed99527cd57c_19345974.jpg temp/1755624688_3689096_1369538663_96538e2ed30c1cde0565aa4be0ce70a5_63631434.jpg temp/1755624688_3689096_1369538661_f18f2f421a0eb3a2f9cd241c257d5949_8881104.jpg temp/1755624688_3689096_1369538660_578e3b8adde666ef99f186b5e6930412_20682816.jpg temp/1755624688_3689096_1369538659_39d5a8f1d73738f4ea9d4e4a91fd109f_35132666.jpg temp/1755624688_3689096_1369538642_8c5acc3552dad2214e2dd0d6c5c1e2ef_74986080.jpg temp/1755624688_3689096_1369538638_b7b3ad62c426af35500b1a20cdff5653_73245971.jpg temp/1755624688_3689096_1369538634_16a678c440ec83dc3acee98093cd1499_78238033.jpg temp/1755624688_3689096_1369538631_125c35ed0a95ad3730dfc81ce627b335_82430258.jpg temp/1755624688_3689096_1369538628_d16824642f6296a74c2ae26ab64d179a_67750380.jpg temp/1755624688_3689096_1369538625_d84ccbd4cce7c830d7da0a0f454068f4_39240596.jpg temp/1755624688_3689096_1369538525_1eaa42d044a8788d33cbe812ea87fa69_9469493.jpg Found 100 images belonging to 1 classes. begin to do the prediction : ERROR in datou_step_exec, will save and exit ! 2 root error(s) found. (0) Unknown: OSError: image file is truncated (48 bytes not processed) Traceback (most recent call last): File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/script_ops.py", line 243, in __call__ ret = func(*args) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/impl/api.py", line 309, in wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 785, in generator_py_func values = next(generator_state.get_iterator(iterator_id)) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 801, in wrapped_generator for data in generator_fn(): File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 932, in generator_fn yield x[i] File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/iterator.py", line 65, in __getitem__ return self._get_batches_of_transformed_samples(index_array) File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/iterator.py", line 227, in _get_batches_of_transformed_samples img = load_img(filepaths[j], File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/utils.py", line 138, in load_img img = img.resize(width_height_tuple, resample) File "/home/admin/.local/lib/python3.8/site-packages/PIL/Image.py", line 2157, in resize self.load() File "/home/admin/.local/lib/python3.8/site-packages/PIL/ImageFile.py", line 266, in load raise OSError(msg) OSError: image file is truncated (48 bytes not processed) [[{{node PyFunc}}]] [[IteratorGetNext]] (1) Unknown: OSError: image file is truncated (48 bytes not processed) Traceback (most recent call last): File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/script_ops.py", line 243, in __call__ ret = func(*args) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/impl/api.py", line 309, in wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 785, in generator_py_func values = next(generator_state.get_iterator(iterator_id)) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 801, in wrapped_generator for data in generator_fn(): File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 932, in generator_fn yield x[i] File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/iterator.py", line 65, in __getitem__ return self._get_batches_of_transformed_samples(index_array) File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/iterator.py", line 227, in _get_batches_of_transformed_samples img = load_img(filepaths[j], File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/utils.py", line 138, in load_img img = img.resize(width_height_tuple, resample) File "/home/admin/.local/lib/python3.8/site-packages/PIL/Image.py", line 2157, in resize self.load() File "/home/admin/.local/lib/python3.8/site-packages/PIL/ImageFile.py", line 266, in load raise OSError(msg) OSError: image file is truncated (48 bytes not processed) [[{{node PyFunc}}]] [[IteratorGetNext]] [[IteratorGetNext/_2]] 0 successful operations. 0 derived errors ignored. [Op:__inference_predict_function_34490] Function call stack: predict_function -> predict_function 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 2523, in datou_step_exec return lib_process.datou_step_tfhub2(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 3147, in datou_step_tfhub2 classes, outputs, features = this_model.predict_image_paths(list_paths, keep_aspect_ratio=keep_aspect_ratio, File "/home/admin/workarea/git/Velours/python/mtr/tfhub2/evaluate.py", line 288, in predict_image_paths Y_pred, F_pred = self.model.predict(valid_generator, validation_steps) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/training.py", line 88, in _method_wrapper return method(self, *args, **kwargs) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/training.py", line 1268, in predict tmp_batch_outputs = predict_function(iterator) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/def_function.py", line 580, in __call__ result = self._call(*args, **kwds) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/def_function.py", line 618, in _call results = self._stateful_fn(*args, **kwds) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/function.py", line 2420, in __call__ return graph_function._filtered_call(args, kwargs) # pylint: disable=protected-access File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/function.py", line 1661, in _filtered_call return self._call_flat( File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/function.py", line 1745, in _call_flat return self._build_call_outputs(self._inference_function.call( File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/function.py", line 593, in call outputs = execute.execute( File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/eager/execute.py", line 59, in quick_execute tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name, [1377038279, 1377038275, 1377038273, 1377038269, 1377038268, 1377038267, 1372556472, 1372556467, 1372556464, 1372556460, 1372556377, 1372556352, 1372556327, 1372556301, 1372556268, 1372556237, 1372553752, 1372553732, 1372553701, 1372553670, 1372553640, 1372553604, 1372553364, 1372553301, 1372553236, 1372553191, 1372553179, 1372553177, 1372553152, 1372553149, 1372553147, 1372553145, 1372553143, 1372553140, 1372553053, 1372553047, 1372553039, 1372553037, 1372553035, 1372553033, 1372300109, 1372300106, 1372300102, 1372300099, 1372299302, 1372299293, 1372299285, 1372299281, 1372299277, 1369539061, 1369539056, 1369539031, 1369539028, 1369539021, 1369539016, 1369539009, 1369539002, 1369538946, 1369538941, 1369538932, 1369538927, 1369538919, 1369538912, 1369538887, 1369538883, 1369538879, 1369538866, 1369538865, 1369538864, 1369538848, 1369538845, 1369538841, 1369538809, 1369538804, 1369538793, 1369538787, 1369538782, 1369538728, 1369538721, 1369538714, 1369538709, 1369538677, 1369538674, 1369538671, 1369538670, 1369538669, 1369538668, 1369538666, 1369538665, 1369538663, 1369538661, 1369538660, 1369538659, 1369538642, 1369538638, 1369538634, 1369538631, 1369538628, 1369538625, 1369538525] begin to insert list_values into mtr_datou_result : length of list_values in save_final : 100 time used for this insertion : 0.1708850860595703 save_final ERROR in last step tfhub_classification2, 2 root error(s) found. (0) Unknown: OSError: image file is truncated (48 bytes not processed) Traceback (most recent call last): File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/script_ops.py", line 243, in __call__ ret = func(*args) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/impl/api.py", line 309, in wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 785, in generator_py_func values = next(generator_state.get_iterator(iterator_id)) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 801, in wrapped_generator for data in generator_fn(): File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 932, in generator_fn yield x[i] File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/iterator.py", line 65, in __getitem__ return self._get_batches_of_transformed_samples(index_array) File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/iterator.py", line 227, in _get_batches_of_transformed_samples img = load_img(filepaths[j], File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/utils.py", line 138, in load_img img = img.resize(width_height_tuple, resample) File "/home/admin/.local/lib/python3.8/site-packages/PIL/Image.py", line 2157, in resize self.load() File "/home/admin/.local/lib/python3.8/site-packages/PIL/ImageFile.py", line 266, in load raise OSError(msg) OSError: image file is truncated (48 bytes not processed) [[{{node PyFunc}}]] [[IteratorGetNext]] (1) Unknown: OSError: image file is truncated (48 bytes not processed) Traceback (most recent call last): File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/ops/script_ops.py", line 243, in __call__ ret = func(*args) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/autograph/impl/api.py", line 309, in wrapper return func(*args, **kwargs) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/data/ops/dataset_ops.py", line 785, in generator_py_func values = next(generator_state.get_iterator(iterator_id)) File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 801, in wrapped_generator for data in generator_fn(): File "/usr/local/lib/python3.8/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 932, in generator_fn yield x[i] File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/iterator.py", line 65, in __getitem__ return self._get_batches_of_transformed_samples(index_array) File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/iterator.py", line 227, in _get_batches_of_transformed_samples img = load_img(filepaths[j], File "/usr/local/lib/python3.8/dist-packages/keras_preprocessing/image/utils.py", line 138, in load_img img = img.resize(width_height_tuple, resample) File "/home/admin/.local/lib/python3.8/site-packages/PIL/Image.py", line 2157, in resize self.load() File "/home/admin/.local/lib/python3.8/site-packages/PIL/ImageFile.py", line 266, in load raise OSError(msg) OSError: image file is truncated (48 bytes not processed) [[{{node PyFunc}}]] [[IteratorGetNext]] [[IteratorGetNext/_2]] 0 successful operations. 0 derived errors ignored. [Op:__inference_predict_function_34490] Function call stack: predict_function -> predict_function time spend for datou_step_exec : 20.73274803161621 time spend to save output : 0.18102145195007324 total time spend for step 0 : 20.913769483566284 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 ! 19.76user 5.68system 0:41.75elapsed 60%CPU (0avgtext+0avgdata 2911620maxresident)k 70264inputs+254840outputs (284major+1396190minor)pagefaults 0swaps