python /home/admin/mtr/script_for_cron.py -j datou_current3 -m 10 -a ' -a 4892  ' -s datou_current_4892 -M 0 -S 0 -U 95,95,80
 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 : 3683586
load datou : 4892
# 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 : 1869>1000
please execute split_portfolio.py -i 20322867 -l 1000
size over we load limit photo not treated
list_input_json: {}
Current got : datou_id : 4892, datou_cur_ids : ['2561624'] with mtr_portfolio_ids : ['20322867'] and first list_photo_ids : []
new path :  /proc/3683586/
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
over limit max, limiting to limit_max 300
list_input_json : {}
origin
We have 1 , 
WARNING: data may be incomplete, need to offset and complete !
BFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFBFwe have missing 0 photos in the step downloads : 
photo missing : []
try to delete the photos missing in DB
length of list_filenames : 300 ; length of list_pids : 300 ; length of list_args : 300
time to download the photos : 50.144641399383545
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
Fri Feb  7 12:57:19 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 : 2
we are using the classfication for multi_thcl 
[3513, 3890]


begin to check gpu status 
inside check gpu memory
2025-02-07 12:57:24.641297: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1
2025-02-07 12:57:24.772907: 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
2025-02-07 12:57:24.775072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-02-07 12:57:24.809141: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-02-07 12:57:24.831172: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-02-07 12:57:24.836374: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-02-07 12:57:24.878885: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-02-07 12:57:24.885083: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-02-07 12:57:24.954457: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-02-07 12:57:24.955994: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-02-07 12:57:24.959983: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2025-02-07 12:57:24.999148: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493065000 Hz
2025-02-07 12:57:25.001172: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f1910000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2025-02-07 12:57:25.001222: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version
2025-02-07 12:57:25.368771: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x402aa430 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices:
2025-02-07 12:57:25.368825: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5
2025-02-07 12:57:25.370290: 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
2025-02-07 12:57:25.370393: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-02-07 12:57:25.370426: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-02-07 12:57:25.370450: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10
2025-02-07 12:57:25.370478: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10
2025-02-07 12:57:25.370503: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10
2025-02-07 12:57:25.370536: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10
2025-02-07 12:57:25.370574: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-02-07 12:57:25.371714: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0
2025-02-07 12:57:25.372138: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
2025-02-07 12:57:25.372840: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix:
2025-02-07 12:57:25.372859: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108]      0 
2025-02-07 12:57:25.372869: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0:   N 
2025-02-07 12:57:25.374461: 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 : 3137  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 : 
[]
2025-02-07 12:57:32.734809: I tensorflow/stream_executor/cuda/cuda_driver.cc:763] failed to allocate 3.02G (3246391296 bytes) from device: CUDA_ERROR_OUT_OF_MEMORY: out of memory
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 : 10.292444705963135
time used to load_weights : 0.4819791316986084

0it [00:00, ?it/s]
41it [00:00, 407.21it/s]
82it [00:00, 293.59it/s]temp/1738929388_3683586_1335510834_f8d13d186d22b1cd1dd663d1c3e4ec52.jpg
temp/1738929388_3683586_1335510833_17422592fea907ba739e72ac40a91b6a.jpg
temp/1738929388_3683586_1335510825_cdc7d46171d77418cb1c0f15b22c4379.jpg
temp/1738929388_3683586_1335510802_f521a0c6a4f2a99068a74a3504158959.jpg
temp/1738929388_3683586_1335510797_f4254d87e5d84f0c68d51c65837e60ac.jpg
temp/1738929388_3683586_1335510792_8fe94a1b83eee37a97aeef2f98d001c6.jpg
temp/1738929388_3683586_1335510739_a33a265a3d8b271158231c6148bf0040.jpg
temp/1738929388_3683586_1335510735_c380b761fd7fb6c94f6d224471f0a124.jpg
temp/1738929388_3683586_1335510713_c86315270962c8c699a0115e5a33fb29.jpg
temp/1738929388_3683586_1335510698_8ff698dec7ce3e1ab738b28c85701717.jpg
temp/1738929388_3683586_1335510694_6d17a51aba72ff4ac3b4d28a6a12629b.jpg
temp/1738929388_3683586_1335510689_d81d4eb1dca63ee75c95e6c77db1d79f.jpg
temp/1738929388_3683586_1335510667_6b2d6d650083bd577e26c60a1900bd3b.jpg
temp/1738929388_3683586_1335510666_d43ba020f03f2d5150873be0d4f167e5.jpg
temp/1738929388_3683586_1335510663_1c4667da42cc763631351e0fd7955958.jpg
temp/1738929388_3683586_1335510658_2668a68644b622d71bb10f9fbd93cf23.jpg
temp/1738929388_3683586_1335510652_bbd70146a9d7e50df6bf8c52d4a36c1e.jpg
temp/1738929388_3683586_1335510646_07ec8d41f02ccb1f38923f99f200f601.jpg
temp/1738929388_3683586_1335510598_66a2a42c8a1ebf9a1eda78d51c2871a9.jpg
temp/1738929388_3683586_1335510590_8a7e86af4c2e0b0b6d46b59a89635990.jpg
temp/1738929388_3683586_1335510585_92b677561cc5aa7b64b81c25c41901e8.jpg
temp/1738929388_3683586_1335510580_9f8c6f2a7d86b57855bf5b08aa1dccfc.jpg
temp/1738929388_3683586_1335510575_8a989a6f73ebe9c4513a0a48ae1c45de.jpg
temp/1738929388_3683586_1335510569_c7c4bc757154ba3d9ca3804c84c94b29.jpg
temp/1738929388_3683586_1335510392_38bd01f7ec641a11baf67a25a6f098d1.jpg
temp/1738929388_3683586_1335510335_f622beceda6fb73b202b8ff14bad92cb.jpg
temp/1738929388_3683586_1335510192_966e648f5f67db09465f535469b69dd9.jpg
temp/1738929388_3683586_1335510033_84d5bf1794a4fb58fc3dec0e498f1b46.jpg
temp/1738929388_3683586_1335509967_0d9d8676e32c11ecee6a5fd0df55f1e7.jpg
temp/1738929388_3683586_1335509962_5bfa6f248ca6feafe78b21e76d6ab433.jpg
temp/1738929388_3683586_1335509928_095c1bffe45250aa9711546cb3ce69de.jpg
temp/1738929388_3683586_1335509870_60aadb8762806d800e50ad31f776dd0b.jpg
temp/1738929388_3683586_1335509869_2da568858182f49d12b4e477d56514bd.jpg
temp/1738929388_3683586_1335509867_adf3718ffad9ad858ce63c9d4afef924.jpg
temp/1738929388_3683586_1335509864_88c26526114e283423b8b46c5a322afe.jpg
temp/1738929388_3683586_1335509863_4892593063c811d9bf95289f101ec464.jpg
temp/1738929388_3683586_1335509813_1ca9f5a92aef5ffc8a673a67e4cf5966.jpg
temp/1738929388_3683586_1335509792_64ebe5f8e797bcd5cb691a2643bb704b.jpg
temp/1738929388_3683586_1335509782_e56f88ff23cab125b7d48d231e6bbaaa.jpg
temp/1738929388_3683586_1335509780_915f45ec40ad76ae3f7bf47909e492c2.jpg
temp/1738929388_3683586_1335509777_2769b6c2e783ba658b86318aa3142322.jpg
temp/1738929388_3683586_1335509771_e8c57ca79a1e7253776240ea2ab8e619.jpg
temp/1738929388_3683586_1335508511_a1c5399f1900775cfa05a4f93f679a91.jpg
temp/1738929388_3683586_1335508426_75c65296b6da13faf4ef106a6bb0910b.jpg
temp/1738929388_3683586_1335508344_cddf4b56ad9104dc49adcbb7f5460030.jpg
temp/1738929388_3683586_1335508247_931f0819e9c5b30dd78e6f9c5a786641.jpg
temp/1738929388_3683586_1335508161_d5eaa2cf783a65182a3869aff864f0f1.jpg
temp/1738929388_3683586_1335508103_6b8a12c4d172561ad475f3ad99f54d5f.jpg
temp/1738929388_3683586_1335508085_3507ba98286cd77ccd5c6537b2e8108b.jpg
temp/1738929388_3683586_1335508007_d2bddd1a4d7e4392cfb1945e53c1ad92.jpg
temp/1738929388_3683586_1335508001_d8ec6752c06f80f7f485655184b2ff16.jpg
temp/1738929388_3683586_1335507997_2dfe561258fe7551f825954a27f1cf2a.jpg
temp/1738929388_3683586_1335507968_7c47f1246595042a023038808649fd75.jpg
temp/1738929388_3683586_1335507958_3296ffd1a606df07cfbbd4fe3197cad7.jpg
temp/1738929388_3683586_1335507631_d6aa72163bccb35f468b0cbf1a9933e5.jpg
temp/1738929388_3683586_1335507621_902108a58fa26167a719bd96cf7c72f2.jpg
temp/1738929388_3683586_1335507620_fd53a8177e571978ff6b9ded6231b2fa.jpg
temp/1738929388_3683586_1335507617_810be99b6e1d9cdd425d3c78c5951801.jpg
temp/1738929388_3683586_1335507614_ebcff8e570c52517dc5b669669097cc2.jpg
temp/1738929388_3683586_1335507608_14621dc404c3a9a92c47f9ead6ec5ea3.jpg
temp/1738929388_3683586_1335507475_0d7672046a5edd66a1a9b17d959eb437.jpg
temp/1738929388_3683586_1335507473_33e907b82f728f70f4dbc523f6a9575f.jpg
temp/1738929388_3683586_1335507470_c2a482e8d4722cad2a616a5a4514d646.jpg
temp/1738929388_3683586_1335507467_987a3b335406452a554f941e5090eaf5.jpg
temp/1738929388_3683586_1335507418_b7849cd34fa43e8c5598012e7adab38d.jpg
temp/1738929388_3683586_1335507403_9159c657e27a26637d7fb9b884652ed7.jpg
temp/1738929388_3683586_1335507153_f3a6596acb462f945541d48a5f5e1ad3.jpg
temp/1738929388_3683586_1335507150_b2352963e0fce8e55af1145ce0344e5c.jpg
temp/1738929388_3683586_1335507145_e07213ce82ebbca18042137c8d852271.jpg
temp/1738929388_3683586_1335507141_d0191f631575298807e6446c6994e0cb.jpg
temp/1738929388_3683586_1335507137_68302ffcbb33fe72152995ee41e98ec2.jpg
temp/1738929388_3683586_1335507066_a7d7738cd377baba356ab6a77ff05625.jpg
temp/1738929388_3683586_1335506666_f12e6df859d1ebd76184147e7e2bd259.jpg
temp/1738929388_3683586_1335506651_e35f630b91acf915371de5705a2bd1af.jpg
temp/1738929388_3683586_1335506537_b9e7ccfc5a0e715d02f6ae09b0f95501.jpg
temp/1738929388_3683586_1335506507_07852422c76756e2274ee4ac1931212d.jpg
temp/1738929388_3683586_1335506506_1f4a1755bd5a862f28b92a90109d6007.jpg
temp/1738929388_3683586_1335506504_1352ebe01d2ee07fb8bbdd0176ae53e5.jpg
temp/1738929388_3683586_1335506232_42c0873c32e2e077c35d97640d0e5d20.jpg
temp/1738929388_3683586_1335506151_ddd25720c8bfaf0d8f01f8370bf46f84.jpg
temp/1738929388_3683586_1335506075_d4c05741a9f1b8b1d5b06bc808bc698d.jpg
temp/1738929388_3683586_1335506058_445038826c066a0e1fb59fd8a5383c92.jpg
temp/1738929388_3683586_1335506056_2b1e8c9927fca497f5ed0e40a9e07886.jpg
temp/1738929388_3683586_1335506052_6d9494621687c577038af9167479079f.jpg
temp/1738929388_3683586_1335505866_5a0e75740fd6a2ec030a9f81d7339f14.jpg
temp/1738929388_3683586_1335505778_673444072ce7a0f58bb4bde9de486e84.jpg
temp/1738929388_3683586_1335505688_33b450112fb084cccc5567c6380dbb35.jpg
temp/1738929388_3683586_1335505609_1f38b731e5ea9fa1de995f59723a6cd0.jpg
temp/1738929388_3683586_1335505531_e000feedce65f70c95ea4c3ede0bf518.jpg
temp/1738929388_3683586_1335505438_ab412131e4266704f7dec9f7ea89854c.jpg
temp/1738929388_3683586_1335505117_7b0f41041489573626bfbbc863debd41.jpg
temp/1738929388_3683586_1335505115_1f4c56e213f752cfdb013c8695c442e0.jpg
temp/1738929388_3683586_1335505111_3c06316eed84b6d8a2b099304d4159ff.jpg
temp/1738929388_3683586_1335505107_1b43986bab337fa58a8ecba017b200ad.jpg
temp/1738929388_3683586_1335505103_361ba5e3da0f35617cd868b5ed7b72a9.jpg
temp/1738929388_3683586_1335505099_b93a2aee68edd7bf3b5826033b215062.jpg
temp/1738929388_3683586_1335505091_7d05b89d0800c747cd55629b80aa7561.jpg
temp/1738929388_3683586_1335505087_3f700aee3accf65224d98a2a5ae81b19.jpg
temp/1738929388_3683586_1335505083_c9740059b1c905f8c036a157bebd6e72.jpg
temp/1738929388_3683586_1335505079_bb9bde9d1e5d5b4f007722b87e2ce124.jpg
temp/1738929388_3683586_1335505074_e2fc70e3c06f706ba326fd32ba785df4.jpg
temp/1738929388_3683586_1335505070_5a0ec5335b4ebd22ed905ef2e9b874b7.jpg
temp/1738929388_3683586_1335505063_ba9f90e0a0e0273aee0298d59f3ecd24.jpg
temp/1738929388_3683586_1335505058_c59d714a79a1b4472d570f6980ee9cf7.jpg
temp/1738929388_3683586_1335505054_514779bae162d83d0cbe7428b3a015cf.jpg
temp/1738929388_3683586_1335505049_310ae8bfc46036491c2fc44c7621514a.jpg
temp/1738929388_3683586_1335505045_810954ce64ae1af8b3d1851e8190117a.jpg
temp/1738929388_3683586_1335505041_fca9036941afd1f2e87ddf7852e83940.jpg
temp/1738929388_3683586_1335505024_b7582df73b243e54ee480a2ccb6eb0e8.jpg
temp/1738929388_3683586_1335505020_339acdfe7157342031a02e06856d1e48.jpg
temp/1738929388_3683586_1335505011_47c96a37cf05f134327b3789e401a45c.jpg
temp/1738929388_3683586_1335504998_8017b0f12488d66c90658b14be4dc1b0.jpg
temp/1738929388_3683586_1335504997_ed9411058d18bd23b24f7db5df2e8e8b.jpg

114it [00:00, 297.45it/s]
145it [00:00, 261.49it/s]
173it [00:00, 245.08it/s]
199it [00:00, 240.61it/s]
224it [00:00, 240.19it/s]temp/1738929388_3683586_1335504995_37d9b85e34c1999cb4895910482689a9.jpg
temp/1738929388_3683586_1335504972_187a24128196e24e0f3ec6077f8a77bd.jpg
temp/1738929388_3683586_1335504969_bbbc1d98106d18014c4673c35e4fd5f7.jpg
temp/1738929388_3683586_1335504966_30d0d845d7c2f201d3aa0f5f7227ef9d.jpg
temp/1738929388_3683586_1335504965_7e74abfd515e1bb4598e68c429699e63.jpg
temp/1738929388_3683586_1335504964_fd7fb72568d5dcd8035a6027805d281e.jpg
temp/1738929388_3683586_1335504963_83247d780a7d739b5f20217cd01db6dd.jpg
temp/1738929388_3683586_1335504815_843f420cb3f59715e0bc31478ca039f1.jpg
temp/1738929388_3683586_1335504795_01b573e25b3334eb5156dccf9e71f1e4.jpg
temp/1738929388_3683586_1335504781_d54555d3b77685a336c8c1779112dc29.jpg
temp/1738929388_3683586_1335504743_d3664874af347e238c976cf9a9dc6eb9.jpg
temp/1738929388_3683586_1335504709_36dcd5e83600df362c8feb8f489201b5.jpg
temp/1738929388_3683586_1335504606_14fc36322b1ae3a427d8752df599657a.jpg
temp/1738929388_3683586_1335504329_9687d6bbe1a30160c540e0984bb459c2.jpg
temp/1738929388_3683586_1335504328_31ccfdf37676e29cef77f80adf8c8ada.jpg
temp/1738929388_3683586_1335504325_5be6adf1a7c2dd53a6c5b11fea4478d5.jpg
temp/1738929388_3683586_1335504292_abea8241e57fa78ee379cd92c5388d53.jpg
temp/1738929388_3683586_1335504287_2a4955d2a1b60553a3ad60ec10e89a4b.jpg
temp/1738929388_3683586_1335504283_1afcb87e694762166fada4169d1def61.jpg
temp/1738929388_3683586_1335503539_d3dcfbdde45ccfa1fabcea3fb2d50710.jpg
temp/1738929388_3683586_1335503533_5ff4b5947a736648f71e15472dae605b.jpg
temp/1738929388_3683586_1335503531_275e532e46946589a6e770146831e094.jpg
temp/1738929388_3683586_1335503529_bec9ca1e78f4216205648c5fb87f0fda.jpg
temp/1738929388_3683586_1335503521_ae81c360eb330022b293572b9dbafce0.jpg
temp/1738929388_3683586_1335503519_60babf52be43bbd772a80cad1de0d449.jpg
temp/1738929388_3683586_1335503494_9feba87ae0447b8c0fc673974c984c9d.jpg
temp/1738929388_3683586_1335503492_6181acf1e12d67b567ceaa367f6950f9.jpg
temp/1738929388_3683586_1335503488_4c6db67cfcb9a3a1ee4e7f6fa004eb63.jpg
temp/1738929388_3683586_1335503486_1058ef5973590ef5d13c0949ee50cc72.jpg
temp/1738929388_3683586_1335503471_f44c9eeae7ef4bd23e5f857c281f123c.jpg
temp/1738929388_3683586_1335503380_91bf1b33c16e0bfdbf708694b984fd2d.jpg
temp/1738929388_3683586_1335503157_9cc04f3ae455a09e2245b66983b8b5de.jpg
temp/1738929388_3683586_1335503068_f676038f7d099ce9dd240adc796215bc.jpg
temp/1738929388_3683586_1335503007_89522b195c7da7b8713b8bb97de0b9fb.jpg
temp/1738929388_3683586_1335503001_7d05190a51feee64471b35ef7f9461bc.jpg
temp/1738929388_3683586_1335502996_1d13c773638b76377f477d680fbb0e30.jpg
temp/1738929388_3683586_1335502988_1b9dbf807fa1a431ecd3814a7f20d62b.jpg
temp/1738929388_3683586_1335502533_a3fdb87c7ab7be8c39a04d24a84aa259.jpg
temp/1738929388_3683586_1335502398_098e71e07dd749317e5d365d31beabd1.jpg
temp/1738929388_3683586_1335502314_0dc98a1368e2ca95c21df84c4a88b97f.jpg
temp/1738929388_3683586_1335502264_01dc669e205c5b4fef8626c8ab485e38.jpg
temp/1738929388_3683586_1335502263_7c215b88f1f9bb6242c867f2ab634668.jpg
temp/1738929388_3683586_1335502262_b4df99bedbf288eebafad38b1def948e.jpg
temp/1738929388_3683586_1335502237_d91690c9372468732595808e91d23b27.jpg
temp/1738929388_3683586_1335502236_76173fe85fc99da8821c2b679fd98a95.jpg
temp/1738929388_3683586_1335502235_8e320840d97492c82ed7676f9cfcc837.jpg
temp/1738929388_3683586_1335502234_72125c4733ab0b1f3b994b26f5b2c432.jpg
temp/1738929388_3683586_1335502232_e15f534bc0b8521947e286538e71ce21.jpg
temp/1738929388_3683586_1335502227_da652d2b274191f0138fd3f511da5bc8.jpg
temp/1738929388_3683586_1335502074_511c78da7962064b92930bdc29a6b43a.jpg
temp/1738929388_3683586_1335502072_50a13f419e8f67102be22077fb3b2dfc.jpg
temp/1738929388_3683586_1335502068_2fe528be5bc40866390ff76644f4eaff.jpg
temp/1738929388_3683586_1335502063_93d77b2d792d0dc42823b6e58e5a769d.jpg
temp/1738929388_3683586_1335502058_8e04005948a7a659c7bd913e078cb035.jpg
temp/1738929388_3683586_1335502053_c3ca2bb0bc9649b4d6245a1a1ad09b50.jpg
temp/1738929388_3683586_1335502023_f8ac83a07fabfab2d5c433e82c97545f.jpg
temp/1738929388_3683586_1335502012_ad80e9098f336039af9be958b967d92b.jpg
temp/1738929388_3683586_1335502007_33b800a1389b6bcae311348ea85f3efc.jpg
temp/1738929388_3683586_1335502003_b6a214aade8abc7f0ad6b003ea55cdc2.jpg
temp/1738929388_3683586_1335502000_80a62e1dab2362de4baad4e3fdece623.jpg
temp/1738929388_3683586_1335501995_e958237e4ff52e894fc23b404e3efeed.jpg
temp/1738929388_3683586_1335501949_cf385978954fa531c3c432e680c85495.jpg
temp/1738929388_3683586_1335501944_fd06a79a826b6a1a3f53cfc408c41413.jpg
temp/1738929388_3683586_1335501910_6dc9a1a01a4e919517dd37b65cafbff3.jpg
temp/1738929388_3683586_1335501902_f1ef2b23c54f3803f2a9779c37042592.jpg
temp/1738929388_3683586_1335501834_158321f909738cd09b3dc0752c694dcd.jpg
temp/1738929388_3683586_1335501812_f85d20940e794a502d490bf4c0f0051e.jpg
temp/1738929388_3683586_1335501495_97ab6531a9452a3e0cbbdc7dc3392627.jpg
temp/1738929388_3683586_1335501427_50eeab811553e9d9b08a161322360430.jpg
temp/1738929388_3683586_1335501132_2373c96066fc0ff815f96fcd62fb5638.jpg
temp/1738929388_3683586_1335500907_e93509ed8b6aa5598ba40ba4680dcb2d.jpg
temp/1738929388_3683586_1335500902_55c5b41473d09f5e9835da4129b82d56.jpg
temp/1738929388_3683586_1335500890_75d1a389cdd489c2e41ddfbe1ade8644.jpg
temp/1738929388_3683586_1335500537_7d44e975f9964460bebc44492f360ebf.jpg
temp/1738929388_3683586_1335500504_e69e83128320a6c0b4580e3c78699f1a.jpg
temp/1738929388_3683586_1335500498_8c75d9ee2026b9f44045c089abf8678d.jpg
temp/1738929388_3683586_1335500481_6c829d6bfc0ce52ee1214c576676028c.jpg
temp/1738929388_3683586_1335500440_7e768a7b8df9201b9da1ae21039b7e7d.jpg
temp/1738929388_3683586_1335500351_5b1f9c01d65aee2c14064336aa7787b3.jpg
temp/1738929388_3683586_1335499989_3800cf3fa7a4e8fcf2ae2a2f84ea349f.jpg
temp/1738929388_3683586_1335499985_460d38108ca5d51cf7257f5356632be3.jpg
temp/1738929388_3683586_1335499982_871a805442b80f0c247cc2de4379aa7a.jpg
temp/1738929388_3683586_1335499978_d36608bfcdba0a242fed8e9097b0ea82.jpg
temp/1738929388_3683586_1335499975_dc6c224be2d88fdbe68f049cedcc6d1c.jpg
temp/1738929388_3683586_1335499972_5340a560d79e5cff5592efe8020028d6.jpg
temp/1738929388_3683586_1335499732_c6f37e8aa641ffb5fa9b8368c80d7736.jpg
temp/1738929388_3683586_1335499658_fe84202e66ca4ceab2483ca6485e836d.jpg
temp/1738929388_3683586_1335499577_8ca752ef89aecda8880a118fc13aa054.jpg
temp/1738929388_3683586_1335499559_25fec461114b3ccd09549c7de31a2ab2.jpg
temp/1738929388_3683586_1335499503_14f77feb22e90a0917ffb8eaa07e9254.jpg
temp/1738929388_3683586_1335499467_dda7d4f4469041c763f3753ef552c7cf.jpg
temp/1738929388_3683586_1335499425_51e3a11df5f7e58ed1a137a536ab0d41.jpg
temp/1738929388_3683586_1335499389_9fd5e316a7ee297361b8282de19bc293.jpg
temp/1738929388_3683586_1335499350_7673c3a60c572069360e5d6181947fa6.jpg
temp/1738929388_3683586_1335499312_05e662c16204330e6ba7419327f67142.jpg
temp/1738929388_3683586_1335499262_4d2421f8191817b981031e245c23b06e.jpg
temp/1738929388_3683586_1335499184_634d5d28807bc663f23c3152c5eabf9c.jpg
temp/1738929388_3683586_1335498813_ad86015c2a9acfa06f24a1c18b75370a.jpg
temp/1738929388_3683586_1335498810_bd858d70e5856a4ef21ff964bc770a7b.jpg
temp/1738929388_3683586_1335498805_7784163a17f4934f71e9c507b61393d1.jpg
temp/1738929388_3683586_1335498798_5f740b9ec5ebd6e095d163cce110fc93.jpg
temp/1738929388_3683586_1335498778_87059cb4852525cd4f4fe8c1f47db9cc.jpg
temp/1738929388_3683586_1335498757_d8c5e5f33fcd31cae8d11ca101a3a3f7.jpg
temp/1738929388_3683586_1335498484_673bb4ddbcc5184bc2b113b20c8e227b.jpg
temp/1738929388_3683586_1335498482_0fd1e53ebe3c1812559d45d1be2998fa.jpg
temp/1738929388_3683586_1335498480_203fa23da40d6c616bc1ee44fab9e83a.jpg
temp/1738929388_3683586_1335498465_758d7fb5273290c831ac3f883f87ffd1.jpg
temp/1738929388_3683586_1335498435_6d663055c6389bddaa59ca5ffe433c66.jpg
temp/1738929388_3683586_1335498362_8007657f138c05732fc443b89142caf5.jpg
temp/1738929388_3683586_1335497774_e1ff503b1d5439b9ee295b8b3884a850.jpg
temp/1738929388_3683586_1335497771_c598592dfc2f753a0e7b8a350a0fe2ae.jpg
temp/1738929388_3683586_1335497750_17e264d88a521409753ad3f56d3cbd9b.jpg
temp/1738929388_3683586_1335497746_03a676eb452fde9230e571222c874dbf.jpg

253it [00:00, 254.03it/s]
289it [00:01, 284.00it/s]
300it [00:01, 272.31it/s]2025-02-07 12:57:39.838854: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10
2025-02-07 12:57:40.460457: E tensorflow/stream_executor/cuda/cuda_blas.cc:238] failed to create cublas handle: CUBLAS_STATUS_NOT_INITIALIZED
2025-02-07 12:57:40.605802: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7
2025-02-07 12:57:40.634976: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2025-02-07 12:57:40.637165: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
temp/1738929388_3683586_1335497742_e5089234f1663dde83b928a2cf81814c.jpg
temp/1738929388_3683586_1335497738_7abb4de9e07bd86fd3b568f14df79674.jpg
temp/1738929388_3683586_1335497709_ba94cb1e77fb37d64db9f500304a6f1e.jpg
temp/1738929388_3683586_1335497702_40ab7551da62eab964c94b6235df5eaf.jpg
temp/1738929388_3683586_1335497698_fe181b054b3c98c9cc023f9e2b9b306a.jpg
temp/1738929388_3683586_1335497695_172369e3b580720dce9e45f53da4ead1.jpg
temp/1738929388_3683586_1335497685_a2fba8496fae769bb5b7ec1931dfb9ce.jpg
temp/1738929388_3683586_1335497681_d3f6fbf8be0e0f1ba00efc489055b4d3.jpg
temp/1738929388_3683586_1335496937_55312e2ba4bfd284d178d9c04a0191a1.jpg
temp/1738929388_3683586_1335496866_8658e551ae6693a2a4266d8e446405d3.jpg
temp/1738929388_3683586_1335496778_92ffc84b755c2f1f7879c889a52c81e7.jpg
temp/1738929388_3683586_1335496699_5a9d104b28baded303362e27fe4fb99c.jpg
temp/1738929388_3683586_1335496612_6d66ff401acccee6a80e7e2f7a8cd607.jpg
temp/1738929388_3683586_1335496524_50ac015263ea0237dbd6ce1ce8e0ea79.jpg
temp/1738929388_3683586_1335496351_fe13cdeac221d9067bcb6fc2c5c84957.jpg
temp/1738929388_3683586_1335496347_94cad5ce8fdc78fb5347f944171ebce7.jpg
temp/1738929388_3683586_1335496342_61fd6a7ea519ba84abb91a74ec929d10.jpg
temp/1738929388_3683586_1335496339_1d07976f14eb6e18cfb511ca584d343c.jpg
temp/1738929388_3683586_1335496336_a581bcaa890a36c2eee9958e7a131717.jpg
temp/1738929388_3683586_1335496334_0602fcf0b86513697001b54354a2cd5f.jpg
temp/1738929388_3683586_1335496314_37e36a9ccba0ce811458a4c59eac77cc.jpg
temp/1738929388_3683586_1335496309_2714b010c3b14c7904f62859f8b45e49.jpg
temp/1738929388_3683586_1335496305_cf1730ac5df7fd5903f7e02fe3dc34a7.jpg
temp/1738929388_3683586_1335496302_1d275521d798fafacbb712673d81d613.jpg
temp/1738929388_3683586_1335496298_56345a994e283379c9eb88e533792e2e.jpg
temp/1738929388_3683586_1335496295_2cf1ac87450816f351ff930cf6ee3eac.jpg
temp/1738929388_3683586_1335496277_41861b3e22b9aa69fafc9cd559507c63.jpg
temp/1738929388_3683586_1335496273_5057954cc82afa8d43adfbad7b58004f.jpg
temp/1738929388_3683586_1335496267_582d9079f614f56722ad3f1df99f502c.jpg
temp/1738929388_3683586_1335496262_0821329f4e36b91c4e5b696a18d7996f.jpg
temp/1738929388_3683586_1335496258_03cad85dc5ab2c166b47fb22af7a0cf8.jpg
temp/1738929388_3683586_1335496256_e704ef28b961018155587598ce990fae.jpg
temp/1738929388_3683586_1335496236_716f307748240d515598a031b27b9ab2.jpg
temp/1738929388_3683586_1335496231_3f7a7697cf296a404baf6afc95f64dde.jpg
temp/1738929388_3683586_1335496227_4cc27efd5eb0232b8ef4ae541260fe6f.jpg
temp/1738929388_3683586_1335496221_8d5fa6ef80996e63dfaa9e40fdbfb7ea.jpg
temp/1738929388_3683586_1335496218_1881d5613f04046e153026eb2d238560.jpg
temp/1738929388_3683586_1335496215_720923b0d208b07fa2f13bb05466f519.jpg
temp/1738929388_3683586_1335496188_0e0a97deb251c5d10550ce19eef05130.jpg
temp/1738929388_3683586_1335496182_e6be19fbf724ede068cfe88e23b9c89d.jpg
temp/1738929388_3683586_1335496177_d9e5f56242bcefcdfc00b7283c291149.jpg
temp/1738929388_3683586_1335496174_c0952a75ed044e5ac0d2947ae94b511b.jpg
temp/1738929388_3683586_1335496170_5148cb3825af5f2fe58a5b403323f464.jpg
temp/1738929388_3683586_1335496167_c89105b150242a055bd7a5b6b31a27ae.jpg
temp/1738929388_3683586_1335496114_64e18b6f89a4545723427172bf63dd18.jpg
temp/1738929388_3683586_1335496110_713b0eac8dbcbba06f04ed9516c1f6d9.jpg
temp/1738929388_3683586_1335496107_0685ca77ca559ad8b6d389d31a09fbae.jpg
temp/1738929388_3683586_1335496104_6c4303a7aeade91c928025ea7241ccc2.jpg
temp/1738929388_3683586_1335496100_a1c661f9f93e957020b40a370ec2b83b.jpg
temp/1738929388_3683586_1335496096_d06e1003fcb89e3cff03afe893cb11fc.jpg
temp/1738929388_3683586_1335496066_36a5110c4a888661fa97905bf1a7891a.jpg
temp/1738929388_3683586_1335496063_ed6c0c14306e66d5f9ce9c7571e56cb1.jpg
temp/1738929388_3683586_1335496061_0640cff650a6b8eccad9ca37a63974bf.jpg
temp/1738929388_3683586_1335496059_f4142cd0b0cce33a4afe8fe978236cf3.jpg
temp/1738929388_3683586_1335496055_efc0732e40555fb6e7159524cdbd7c6e.jpg
temp/1738929388_3683586_1335496052_7d32f7b1a1e67922606e6a7c706f5429.jpg
temp/1738929388_3683586_1335496013_e767de67d5f43b7941e0dc77ba3fd4c0.jpg
temp/1738929388_3683586_1335496006_9f8ef0c90f44d3fd2c57dbdab30f52d1.jpg
temp/1738929388_3683586_1335496005_d8d5f2e5b35ed4bf6462dfd104f1b66b.jpg
temp/1738929388_3683586_1335496001_d6ab7ff1a0d1e1539ae7398a1a057248.jpg
temp/1738929388_3683586_1335495999_a4f38494ea6767c25e4d03a43cf8cb95.jpg
temp/1738929388_3683586_1335495997_ad552bc0c9a4176804f7cdc6834fb604.jpg
temp/1738929388_3683586_1335495992_d7c3b2c5d1db23fff29cb056f372e455.jpg
temp/1738929388_3683586_1335495991_c32ac492bde2e619e29e420c00a7f9dc.jpg
temp/1738929388_3683586_1335495980_bc9a806e6900ca179953f553e35db229.jpg
temp/1738929388_3683586_1335495979_fbea0fd7129681ade94a2bf860ea78f6.jpg
temp/1738929388_3683586_1335495973_cc06c0a1b79d7dd230f4f80ced788f75.jpg
temp/1738929388_3683586_1335495972_0ebcb7b538c2e3b37f1ca2890b7b1e86.jpg
temp/1738929388_3683586_1335495863_e58deb0af058c85471661ec5a56456bc.jpg
temp/1738929388_3683586_1335495861_8fa2083dfed8ee142a621b85ccfe8e6e.jpg
temp/1738929388_3683586_1335495829_540086af37c24634e701edbd2fad312a.jpg
temp/1738929388_3683586_1335495825_ffc502efca99091d56f606b703517b26.jpg
temp/1738929388_3683586_1335495821_a61f1bc5147a0690d86291203aa2cfc0.jpg
temp/1738929388_3683586_1335495818_1a3b7d71c50254d3ea638fefd1530839.jpg
Found 300 images belonging to 1 classes.

 begin to do the prediction :
ERROR in datou_step_exec, will save and exit !
 Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[{{node model/module/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/conv1/StatefulPartitionedCall/Conv2D}}]] [Op:__inference_predict_function_34490]

Function call stack:
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 3146, 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 650, in _call
    return self._concrete_stateful_fn._filtered_call(canon_args, canon_kwds)  # 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,

[1335510834, 1335510833, 1335510825, 1335510802, 1335510797, 1335510792, 1335510739, 1335510735, 1335510713, 1335510698, 1335510694, 1335510689, 1335510667, 1335510666, 1335510663, 1335510658, 1335510652, 1335510646, 1335510598, 1335510590, 1335510585, 1335510580, 1335510575, 1335510569, 1335510392, 1335510335, 1335510192, 1335510033, 1335509967, 1335509962, 1335509928, 1335509870, 1335509869, 1335509867, 1335509864, 1335509863, 1335509813, 1335509792, 1335509782, 1335509780, 1335509777, 1335509771, 1335508511, 1335508426, 1335508344, 1335508247, 1335508161, 1335508103, 1335508085, 1335508007, 1335508001, 1335507997, 1335507968, 1335507958, 1335507631, 1335507621, 1335507620, 1335507617, 1335507614, 1335507608, 1335507475, 1335507473, 1335507470, 1335507467, 1335507418, 1335507403, 1335507153, 1335507150, 1335507145, 1335507141, 1335507137, 1335507066, 1335506666, 1335506651, 1335506537, 1335506507, 1335506506, 1335506504, 1335506232, 1335506151, 1335506075, 1335506058, 1335506056, 1335506052, 1335505866, 1335505778, 1335505688, 1335505609, 1335505531, 1335505438, 1335505117, 1335505115, 1335505111, 1335505107, 1335505103, 1335505099, 1335505091, 1335505087, 1335505083, 1335505079, 1335505074, 1335505070, 1335505063, 1335505058, 1335505054, 1335505049, 1335505045, 1335505041, 1335505024, 1335505020, 1335505011, 1335504998, 1335504997, 1335504995, 1335504972, 1335504969, 1335504966, 1335504965, 1335504964, 1335504963, 1335504815, 1335504795, 1335504781, 1335504743, 1335504709, 1335504606, 1335504329, 1335504328, 1335504325, 1335504292, 1335504287, 1335504283, 1335503539, 1335503533, 1335503531, 1335503529, 1335503521, 1335503519, 1335503494, 1335503492, 1335503488, 1335503486, 1335503471, 1335503380, 1335503157, 1335503068, 1335503007, 1335503001, 1335502996, 1335502988, 1335502533, 1335502398, 1335502314, 1335502264, 1335502263, 1335502262, 1335502237, 1335502236, 1335502235, 1335502234, 1335502232, 1335502227, 1335502074, 1335502072, 1335502068, 1335502063, 1335502058, 1335502053, 1335502023, 1335502012, 1335502007, 1335502003, 1335502000, 1335501995, 1335501949, 1335501944, 1335501910, 1335501902, 1335501834, 1335501812, 1335501495, 1335501427, 1335501132, 1335500907, 1335500902, 1335500890, 1335500537, 1335500504, 1335500498, 1335500481, 1335500440, 1335500351, 1335499989, 1335499985, 1335499982, 1335499978, 1335499975, 1335499972, 1335499732, 1335499658, 1335499577, 1335499559, 1335499503, 1335499467, 1335499425, 1335499389, 1335499350, 1335499312, 1335499262, 1335499184, 1335498813, 1335498810, 1335498805, 1335498798, 1335498778, 1335498757, 1335498484, 1335498482, 1335498480, 1335498465, 1335498435, 1335498362, 1335497774, 1335497771, 1335497750, 1335497746, 1335497742, 1335497738, 1335497709, 1335497702, 1335497698, 1335497695, 1335497685, 1335497681, 1335496937, 1335496866, 1335496778, 1335496699, 1335496612, 1335496524, 1335496351, 1335496347, 1335496342, 1335496339, 1335496336, 1335496334, 1335496314, 1335496309, 1335496305, 1335496302, 1335496298, 1335496295, 1335496277, 1335496273, 1335496267, 1335496262, 1335496258, 1335496256, 1335496236, 1335496231, 1335496227, 1335496221, 1335496218, 1335496215, 1335496188, 1335496182, 1335496177, 1335496174, 1335496170, 1335496167, 1335496114, 1335496110, 1335496107, 1335496104, 1335496100, 1335496096, 1335496066, 1335496063, 1335496061, 1335496059, 1335496055, 1335496052, 1335496013, 1335496006, 1335496005, 1335496001, 1335495999, 1335495997, 1335495992, 1335495991, 1335495980, 1335495979, 1335495973, 1335495972, 1335495863, 1335495861, 1335495829, 1335495825, 1335495821, 1335495818]


begin to insert list_values into mtr_datou_result : 
length of list_values in save_final : 300
time used for this insertion : 0.12926816940307617
 save_final 
ERROR in last step tfhub_classification2,  Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[{{node model/module/StatefulPartitionedCall/StatefulPartitionedCall/StatefulPartitionedCall/conv1/StatefulPartitionedCall/Conv2D}}]] [Op:__inference_predict_function_34490]

Function call stack:
predict_function


time spend for datou_step_exec : 21.548027992248535
time spend to save output : 0.17037105560302734
total time spend for step 0 : 21.718399047851562
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 !
15.07user 8.17system 1:17.66elapsed 29%CPU (0avgtext+0avgdata 1412516maxresident)k
2852488inputs+1206344outputs (12528major+660314minor)pagefaults 0swaps