python /home/admin/mtr/script_for_cron.py -j datou_current3 -m 20 -a ' -a 4189' -s datou_current_4189 -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 : 3439351 load datou : 4189 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! 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 : None was removed should we ? donnée sous forme de texte was removed should we ? [ptf_id0,ptf_id1...] 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 list_input_json: {} Current got : datou_id : 4189, datou_cur_ids : ['2744195'] with mtr_portfolio_ids : ['22264378'] and first list_photo_ids : [] new path : /proc/3439351/ 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) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : split_time_score over limit max, limiting to limit_max 100 list_input_json : {} origin We have 1 , we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB time to download the photos : 0.03810000419616699 About to test input to load Calling datou_exec Inside datou_exec : verbose : 0 number of steps : 1 step1:split_time_score Fri Apr 11 12:00:31 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec begin split time score 2022-04-13 10:29:59 0 TODO : Insert select and so on Begin split_port_in_batch_balle 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'}] 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'}] (('10', 93),) ERROR counted https://github.com/fotonower/Velours/issues/663#issuecomment-421136223 {1: 93} 11042025 22264378 Nombre de photos uploadées : 93 / 23040 (0%) 11042025 22264378 Nombre de photos taguées (types de déchets): 93 / 93 (100%) 11042025 22264378 Nombre de photos taguées (volume) : 93 / 93 (100%) elapsed_time : load_data_split_time_score 3.5762786865234375e-06 elapsed_time : order_list_meta_photo_and_scores 5.340576171875e-05 LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL elapsed_time : fill_and_build_computed_from_old_data 0.006128549575805664 elapsed_time : insert_dashboard_record_day_entry 0.03593134880065918 LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLL Creating list_photo_by_hashtags elapsed_time : list_photo_by_hashtags 0.026539325714111328 Creating list_photo_total elapsed_time : select_descriptors 2.4832005500793457 11042025 22264378 Nombre de photos avec descriptors (type 5680) : 47 / 47 (100%) ERROR : Hum hum, what can we do for different size of descriptors (ignore the difference ) : 0 vs 1280 photo_id : 1351555419 photo_id_prec : 0 0:00:00|ON:LLMissing descriptors for photos 1351574067 and 1351574333 LMissing descriptors for photos 1351574333 and 1351574280 LMissing descriptors for photos 1351574280 and 1351574138 LMissing descriptors for photos 1351574138 and 1351573995 LMissing descriptors for photos 1351573995 and 1351574245 LMissing descriptors for photos 1351574245 and 1351577738 LMissing descriptors for photos 1351577738 and 1351577762 LMissing descriptors for photos 1351577762 and 1351577829 LMissing descriptors for photos 1351577829 and 1351577872 LMissing descriptors for photos 1351577872 and 1351577886 LMissing descriptors for photos 1351577886 and 1351577903 LMissing descriptors for photos 1351577903 and 1351581432 LMissing descriptors for photos 1351581432 and 1351581644 LMissing descriptors for photos 1351581644 and 1351581608 LMissing descriptors for photos 1351581608 and 1351581555 LMissing descriptors for photos 1351581555 and 1351581473 LMissing descriptors for photos 1351581473 and 1351581360 LMissing descriptors for photos 1351581360 and 1351586472 LMissing descriptors for photos 1351586472 and 1351586426 LMissing descriptors for photos 1351586426 and 1351586382 LMissing descriptors for photos 1351586382 and 1351586336 LMissing descriptors for photos 1351586336 and 1351586233 LMissing descriptors for photos 1351586233 and 1351583609 LMissing descriptors for photos 1351583609 and 1351586166 LMissing descriptors for photos 1351586166 and 1351583555 LMissing descriptors for photos 1351583555 and 1351583588 LMissing descriptors for photos 1351583588 and 1351590200 LMissing descriptors for photos 1351590200 and 1351590243 LMissing descriptors for photos 1351590243 and 1351590289 LLMissing descriptors for photos 1351590362 and 1351590365 LMissing descriptors for photos 1351590365 and 1351594897 LMissing descriptors for photos 1351594897 and 1351595333 LMissing descriptors for photos 1351595333 and 1351595066 LLMissing descriptors for photos 1351594386 and 1351594116 LMissing descriptors for photos 1351594116 and 1351599037 LMissing descriptors for photos 1351599037 and 1351599099 LMissing descriptors for photos 1351599099 and 1351599158 LMissing descriptors for photos 1351599158 and 1351599249 LMissing descriptors for photos 1351599249 and 1351599308 LMissing descriptors for photos 1351599308 and 1351599557 LLLLMissing descriptors for photos 1351604660 and 1351604735 LLLLLLLLLLLLLLLLLLLLL 11042025 Removing 0 photos because of the 'same image' condition Total on : 0 Total off : 0.0 list_time_off Warning in study_and_display_distrib_list : min=max : 0.0 0.0 dist_desc begin to insert list_values into photo_hahstag_ids : length of list_valuse in save_photo_hashtag_id_type : 93 time used for this insertion : 0.02621912956237793 photos_removed : len 0 elapsed_time : remove_photo_duplicate 0.057796478271484375 To do, maybe not at the correct place ! ....................L.....L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L..L.L.L.L.L..L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.L.Lforce hashtag to JRM elapsed_time : CREATE_PORT_BATCH_BY_HOUR 0.008508920669555664 NUMBER BATCH : 1 list_ponderation used : [1e-05, 1e-05, 1e-05, 1e-05, 1e-05] , list_hashtag_class_create_as_list : ['jrm'] LLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLLresult_one_balle_Type_JRM:{'day': '11042025', 'map_nb_amount': {0: 6, 1: 40, 2: 1, 3: 0, 4: 0}, 'map_time_amount': {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}, 'duration': 840.155769109726, 'nb_balles_papier': 0.0004700000000000006, 'begin_time_port': 'image_11042025_10_00_02_313268m0.jpg 1e-05 for time 1, id_amount 2 this amount prod time diff : 1e-05'} Production hashtag (incorrect ponderation at 20-10-18) : 0.0004700000000000006 We have rejected 0 photos because of the batch_size condition ! NUMBER BATCH list_of_portfolios_to_create : 1 list_same_port_ids : [] https://marlene.fotonower.com/api/v1/secured/portfolio/new?name=JRM_diff_batch__11042025_10_00_02_313268&access_token=b05576c56a0e42ad0cb9b46155f68f82 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! All sons are already in current list ! DONE and to test : checkNoCycle ! Here we check the consistency of inputs/outputs number between the given ones and the db ! eke 1-6-18 : checkConsistencyNbInputNbOutput should be processed after step reordering ! WARNING : number of outputs for step 12489 mask_detect is not consistent : 3 used against 2 in the step definition ! WARNING : number of outputs for step 12499 brightness is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 12500 blur_detection is not consistent : 2 used against 1 in the step definition ! WARNING : number of inputs for step 12492 crop_condition is not consistent : 3 used against 2 in the step definition ! Step 12492 crop_condition have less outputs used (2) than in the step definition (3) : some outputs may be not used ! WARNING : number of outputs for step 12493 merge_mask_thcl_custom is not consistent : 4 used against 2 in the step definition ! WARNING : number of inputs for step 12494 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 12494 rle_unique_nms_with_priority is not consistent : 2 used against 1 in the step definition ! Step 12502 crop_condition have less inputs used (1) than in the step definition (2) : maybe we manage optionnal inputs ! WARNING : number of outputs for step 12502 crop_condition is not consistent : 4 used against 3 in the step definition ! WARNING : number of inputs for step 12496 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! WARNING : number of outputs for step 12496 ventilate_hashtags_in_portfolio is not consistent : 2 used against 1 in the step definition ! Step 12495 final have less inputs used (2) than in the step definition (3) : maybe we manage optionnal inputs ! Step 12495 final have less outputs used (1) than in the step definition (2) : some outputs may be not used ! 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 ! WARNING : type of output 2 of step 12489 doesn't seem to be define in the database( WARNING : type of input 2 of step 12492 doesn't seem to be define in the database( WARNING : output 1 of step 12489 have datatype=2 whereas input 1 of step 12493 have datatype=7 WARNING : type of output 2 of step 12493 doesn't seem to be define in the database( WARNING : type of input 1 of step 12494 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 3 of step 12493 doesn't seem to be define in the database( WARNING : type of input 1 of step 12496 doesn't seem to be define in the database( WARNING : type of output 1 of step 12496 doesn't seem to be define in the database( WARNING : type of input 3 of step 12495 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : type of output 2 of step 12489 doesn't seem to be define in the database( WARNING : type of input 1 of step 12500 doesn't seem to be define in the database( WARNING : type of output 2 of step 12489 doesn't seem to be define in the database( WARNING : type of input 1 of step 12499 doesn't seem to be define in the database( We ignore checkConsistencyTypeOutputInput for datou_step final ! WARNING : output 0 of step 12496 have datatype=10 whereas input 3 of step 12498 have datatype=6 WARNING : type of input 5 of step 12498 doesn't seem to be define in the database( WARNING : output 0 of step 12501 have datatype=11 whereas input 5 of step 12498 have datatype=None WARNING : output 0 of step 12496 have datatype=10 whereas input 0 of step 12501 have datatype=18 WARNING : type of input 2 of step 12502 doesn't seem to be define in the database( WARNING : output 1 of step 12494 have datatype=7 whereas input 2 of step 12502 have datatype=None WARNING : type of output 3 of step 12502 doesn't seem to be define in the database( WARNING : type of input 2 of step 12496 doesn't seem to be define in the database( WARNING : type of output 1 of step 12499 doesn't seem to be define in the database( WARNING : type of input 3 of step 12492 doesn't seem to be define in the database( WARNING : type of output 1 of step 12500 doesn't seem to be define in the database( WARNING : type of input 3 of step 12492 doesn't seem to be define in the database( WARNING : output 0 of step 12493 have datatype=1 whereas input 0 of step 12494 have datatype=2 DataTypes for each output/input checked ! TODO Duplicate data, are they consistent 3 ? Duplicate data, are they consistent 4 ? SELECT mptpi.id, mptpi.mtr_portfolio_id_1, mptpi.mtr_portfolio_id_2, mptpi.type, mptpi.hashtag_id, mptpi.min_score, mptpi.mtr_user_id, mptpi.created_at, mptpi.updated_at, mptpi.last_updated_at_desc, mptpi.last_updated_at_asc, h.hashtag FROM MTRPhoto.mtr_port_to_port_ids mptpi, MTRBack.hashtags h WHERE h.hashtag_id=mptpi.hashtag_id AND mptpi.`mtr_portfolio_id_1`=22272899 AND mptpi.`type`=3726 To do elapsed_time : count_nb_balles_and_create_portfolio 2.7572414875030518 # DISPLAY ALL COLLECTED DATA : {'11042025': {'nb_upload': 93, 'nb_taggue_class': 93, 'nb_taggue_densite': 93, 'nb_descriptors': 47}} Inside saveOutput : final : True verbose : 0 saveOutput not yet implemented for datou_step.type : split_time_score we use saveGeneral [1351616331, 1351616249, 1351616171, 1351616038, 1351615886, 1351615760, 1351611543, 1351611443, 1351611309, 1351611186, 1351611038, 1351610880, 1351607767, 1351607706, 1351607694, 1351607686, 1351607646, 1351607612, 1351604922, 1351604873, 1351604735, 1351604660, 1351604591, 1351604527, 1351599557, 1351599308, 1351599249, 1351599158, 1351599099, 1351599037, 1351595333, 1351595066, 1351594897, 1351594606, 1351594386, 1351594116, 1351590365, 1351590362, 1351590327, 1351590289, 1351590243, 1351590200, 1351586472, 1351586426, 1351586382, 1351586336, 1351586233, 1351586166, 1351583609, 1351583588, 1351583555, 1351581644, 1351581608, 1351581555, 1351581473, 1351581432, 1351581360, 1351577903, 1351577886, 1351577872, 1351577829, 1351577762, 1351577738, 1351574333, 1351574280, 1351574245, 1351574138, 1351574067, 1351573995, 1351569684, 1351569353, 1351569149, 1351569107, 1351569097, 1351569092, 1351564761, 1351564705, 1351564650, 1351564610, 1351564589, 1351564542, 1351560989, 1351560922, 1351560858, 1351560799, 1351560662, 1351560577, 1351555930, 1351555865, 1351555657, 1351555560, 1351555419, 1351555374] Looping around the photos to save general results len do output : 1 /22264378Didn'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 ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351616331', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351616249', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351616171', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351616038', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351615886', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351615760', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351611543', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351611443', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351611309', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351611186', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351611038', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351610880', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351607767', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351607706', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351607694', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351607686', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351607646', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351607612', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351604922', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351604873', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351604735', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351604660', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351604591', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351604527', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351599557', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351599308', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351599249', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351599158', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351599099', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351599037', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351595333', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351595066', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351594897', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351594606', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351594386', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351594116', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351590365', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351590362', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351590327', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351590289', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351590243', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351590200', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', 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'2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351560577', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351555930', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351555865', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351555657', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351555560', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351555419', None, None, None, None, None, '2744195') ('4189', None, None, None, None, None, None, None, '2744195') ('4189', '22264378', '1351555374', None, None, None, None, None, '2744195') begin to insert list_values into mtr_datou_result : length of list_values in save_final : 94 time used for this insertion : 0.31392836570739746 save_final save missing photos in datou_result : time spend for datou_step_exec : 16.68269419670105 time spend to save output : 0.3173511028289795 total time spend for step 1 : 17.00004529953003 caffe_path_current : About to save ! 2 After save, about to update current ! ret : 2 len(input) + len(total_photo_id_missing) : 1 set_done_treatment 1.87user 0.94system 0:23.11elapsed 12%CPU (0avgtext+0avgdata 101892maxresident)k 632inputs+456outputs (4major+49043minor)pagefaults 0swaps