[I 2022-10-17 10:04:00] ...ytorch/bootstrap/run.py.73: Saving environment info [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: options: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: dataset: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: aux_kw_path: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_titles_kw.json [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_titles_kw.json [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_titles_kw.json [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: batch_sampler: random [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: batch_size: 96 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: database: lmdb [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: dir: /gpfsdswork/dataset/Recipe1M+/images_recipe1M+ [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: eval_split: val [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: freq_mismatch: 0.0 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: image_from: database [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: import: recipe1m.datasets.factory [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: kw_path: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_ingr_kw.json [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_ingr_kw.json [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_ingr_kw.json [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: name: recipe1m_13m [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: nb_classes: 1048 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: nb_threads: 4 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: orig_ids_eval: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: path_ids: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/original_ids.json [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: engine: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: resume: None [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: overrite: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a101', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-17 10:04:07] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-17 10:04:07] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-17 10:04:07] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-17 10:06:06] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-17 10:06:09] ...tasets/recipe1m_13m.py.293: randkw_p... 0.3 [I 2022-10-17 10:07:50] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-17 10:07:51] ...tasets/recipe1m_13m.py.293: randkw_p... None [I 2022-10-17 10:07:51] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-17 10:07:51] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-17 10:07:51] ...strap/models/factory.py.21: Creating model... [I 2022-10-17 10:07:55] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-17 10:07:59] ...e_networks/networks.py.145: cuda [I 2022-10-17 10:08:00] ...networks/tfood_vicha.py.49: Load VCs encoder... [I 2022-10-17 10:08:02] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-17 10:08:02] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-17 10:08:02] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-17 10:08:02] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-17 10:08:04] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-17 10:08:04] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-17 10:08:04] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-17 10:08:09] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-17 10:08:09] ...trap/engines/engine.py.163: Training model on trainset for epoch 0 [I 2022-10-17 10:08:09] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [I 2022-10-17 10:08:21] ...trap/engines/engine.py.224: train: epoch 0 | batch 0/7425 [I 2022-10-17 10:08:21] ...trap/engines/engine.py.228: elapsed: 0:00:12 | left: 1 day, 0:35:26 [I 2022-10-17 10:08:21] ...trap/engines/engine.py.229: process: 11.92280 | load: 7.68006 [I 2022-10-17 10:08:21] ...trap/engines/engine.py.230: loss: 1.42278 [I 2022-10-17 10:08:21] ...optimizers/trijoint.py.151: total_norm: 10.954002 [I 2022-10-17 10:08:31] ...trap/engines/engine.py.224: train: epoch 0 | batch 10/7425 [I 2022-10-17 10:08:31] ...trap/engines/engine.py.228: elapsed: 0:00:22 | left: 4:44:47 [I 2022-10-17 10:08:31] ...trap/engines/engine.py.229: process: 0.72294 | load: 0.00013 [I 2022-10-17 10:08:31] ...trap/engines/engine.py.230: loss: 1.39623 [I 2022-10-17 10:08:31] ...optimizers/trijoint.py.151: total_norm: 7.387934 [I 2022-10-17 10:08:49] ...trap/engines/engine.py.224: train: epoch 0 | batch 20/7425 [I 2022-10-17 10:08:49] ...trap/engines/engine.py.228: elapsed: 0:00:39 | left: 4:00:22 [I 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...trap/engines/engine.py.228: elapsed: 3:25:15 | left: 0:01:11 [I 2022-10-17 13:33:24] ...trap/engines/engine.py.229: process: 0.73721 | load: 0.00015 [I 2022-10-17 13:33:24] ...trap/engines/engine.py.230: loss: 0.62770 [I 2022-10-17 13:33:24] ...optimizers/trijoint.py.151: total_norm: 4.206250 [I 2022-10-17 13:33:43] ...trap/engines/engine.py.224: train: epoch 0 | batch 7390/7425 [I 2022-10-17 13:33:43] ...trap/engines/engine.py.228: elapsed: 3:25:33 | left: 0:01:14 [I 2022-10-17 13:33:43] ...trap/engines/engine.py.229: process: 4.74029 | load: 3.99030 [I 2022-10-17 13:33:43] ...trap/engines/engine.py.230: loss: 0.57870 [I 2022-10-17 13:33:43] ...optimizers/trijoint.py.151: total_norm: 4.506269 [I 2022-10-17 13:33:59] ...trap/engines/engine.py.224: train: epoch 0 | batch 7400/7425 [I 2022-10-17 13:33:59] ...trap/engines/engine.py.228: elapsed: 3:25:50 | left: 0:00:40 [I 2022-10-17 13:33:59] ...trap/engines/engine.py.229: process: 0.73707 | load: 0.00016 [I 2022-10-17 13:33:59] ...trap/engines/engine.py.230: loss: 0.70787 [I 2022-10-17 13:33:59] ...optimizers/trijoint.py.151: total_norm: 4.745574 [I 2022-10-17 13:34:19] ...trap/engines/engine.py.224: train: epoch 0 | batch 7410/7425 [I 2022-10-17 13:34:19] ...trap/engines/engine.py.228: elapsed: 3:26:10 | left: 0:00:31 [I 2022-10-17 13:34:19] ...trap/engines/engine.py.229: process: 4.52771 | load: 3.76753 [I 2022-10-17 13:34:19] ...trap/engines/engine.py.230: loss: 0.52311 [I 2022-10-17 13:34:19] ...optimizers/trijoint.py.151: total_norm: 4.181600 [I 2022-10-17 13:34:34] ...trap/engines/engine.py.224: train: epoch 0 | batch 7420/7425 [I 2022-10-17 13:34:34] ...trap/engines/engine.py.228: elapsed: 3:26:25 | left: 0:00:07 [I 2022-10-17 13:34:34] ...trap/engines/engine.py.229: process: 0.73511 | load: 0.00009 [I 2022-10-17 13:34:34] ...trap/engines/engine.py.230: loss: 0.46093 [I 2022-10-17 13:34:34] ...optimizers/trijoint.py.151: total_norm: 3.468158 [I 2022-10-17 13:34:42] ...trap/engines/engine.py.224: train: epoch 0 | batch 7425/7425 [I 2022-10-17 13:34:42] ...trap/engines/engine.py.228: elapsed: 3:26:33 | left: 0:00:00 [I 2022-10-17 13:34:42] ...trap/engines/engine.py.229: process: 2.45243 | load: 1.72018 [I 2022-10-17 13:34:42] ...trap/engines/engine.py.230: loss: 0.66639 [I 2022-10-17 13:34:42] ...optimizers/trijoint.py.151: total_norm: 4.995146 [S 2022-10-17 13:34:44] ...trap/engines/engine.py.129: train_epoch.epoch: 0 [S 2022-10-17 13:34:44] ...trap/engines/engine.py.129: train_epoch.loss: 0.7302685495723844 [I 2022-10-17 13:34:44] ...iterions/vlp_triplet.py.80: margin = 0.055 [I 2022-10-17 13:34:44] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 0 [I 2022-10-17 13:34:44] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [W 2022-10-17 13:34:51] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-17 13:34:51] ...otstrap/views/plotly.py.87: View 'eval_epoch.metric.med_im2recipe_mean' not in 'logs.json' [W 2022-10-17 13:34:51] ...otstrap/views/plotly.py.87: View 'eval_epoch.metric.recall_at_1_im2recipe_mean' not in 'logs.json' [W 2022-10-17 13:34:51] ...otstrap/views/plotly.py.87: View 'eval_epoch.metric.recall_at_5_im2recipe_mean' not in 'logs.json' [W 2022-10-17 13:34:51] ...otstrap/views/plotly.py.87: View 'eval_epoch.metric.recall_at_10_im2recipe_mean' not in 'logs.json' [W 2022-10-17 13:34:51] ...otstrap/views/plotly.py.87: View 'eval_epoch.metric.med_recipe2im_mean' not in 'logs.json' [W 2022-10-17 13:34:51] ...otstrap/views/plotly.py.87: View 'eval_epoch.metric.recall_at_1_recipe2im_mean' not in 'logs.json' [W 2022-10-17 13:34:51] ...otstrap/views/plotly.py.87: View 'eval_epoch.metric.recall_at_5_recipe2im_mean' not in 'logs.json' [W 2022-10-17 13:34:51] ...otstrap/views/plotly.py.87: View 'eval_epoch.metric.recall_at_10_recipe2im_mean' not in 'logs.json' [W 2022-10-17 13:34:51] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-17 13:34:51] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-17 13:34:55] ...trap/engines/engine.py.321: eval: epoch 0 | batch 0/1578 [I 2022-10-17 13:34:55] ...trap/engines/engine.py.325: elapsed: 0:00:10 | left: 4:47:51 [I 2022-10-17 13:34:55] ...trap/engines/engine.py.326: process: 10.94490 | load: 10.04830 [I 2022-10-17 13:34:57] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-17 13:35:09] ...trap/engines/engine.py.321: eval: epoch 0 | batch 10/1578 [I 2022-10-17 13:35:09] ...trap/engines/engine.py.325: elapsed: 0:00:24 | left: 1:03:22 [I 2022-10-17 13:35:09] ...trap/engines/engine.py.326: process: 0.37832 | load: 0.00017 [I 2022-10-17 13:35:30] ...trap/engines/engine.py.321: eval: epoch 0 | batch 20/1578 [I 2022-10-17 13:35:30] ...trap/engines/engine.py.325: elapsed: 0:00:45 | left: 1:02:23 [I 2022-10-17 13:35:30] ...trap/engines/engine.py.326: process: 6.12329 | load: 5.63430 [I 2022-10-17 13:35:43] ...trap/engines/engine.py.321: eval: epoch 0 | batch 30/1578 [I 2022-10-17 13:35:43] ...trap/engines/engine.py.325: elapsed: 0:00:58 | left: 0:38:34 [I 2022-10-17 13:35:43] ...trap/engines/engine.py.326: process: 0.44652 | load: 0.00015 [I 2022-10-17 13:36:02] ...trap/engines/engine.py.321: eval: epoch 0 | batch 40/1578 [I 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0.233000 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.510700 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.635000 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.223600 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.496800 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.617800 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.300000 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.489898 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_std: 0.010658 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.006798 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.015697 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.012548 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.008964 [S 2022-10-17 14:17:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.012914 [I 2022-10-17 14:18:08] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-17 14:18:08] ...trap/engines/engine.py.470: Saving model... [W 2022-10-17 14:18:08] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-17 14:18:08] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-17 14:18:08] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-17 14:18:08] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-17 14:18:11] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-17 14:18:15] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-17 14:18:15] ...trap/engines/engine.py.163: Training model on trainset for epoch 1 [I 2022-10-17 14:18:15] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.573000 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.685200 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.257700 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.561000 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.680300 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.000000 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.300000 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_std: 0.010024 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.012377 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.012648 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.010277 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.012625 [S 2022-10-17 18:23:13] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.010070 [I 2022-10-17 18:23:28] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.med_im2recipe_mean [I 2022-10-17 18:23:28] ...trap/engines/engine.py.470: Saving model... [W 2022-10-17 18:23:29] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-17 18:23:29] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-17 18:23:29] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-17 18:23:29] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-17 18:23:32] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-17 18:23:37] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-17 18:23:37] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-17 18:23:37] ...trap/engines/engine.py.470: Saving model... [I 2022-10-17 18:23:40] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-17 18:23:48] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-17 18:23:48] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-17 18:23:48] ...trap/engines/engine.py.470: Saving model... [I 2022-10-17 18:23:51] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-17 18:23:56] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-17 18:23:56] ...trap/engines/engine.py.163: Training model on trainset for epoch 2 [I 2022-10-17 18:23:56] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-17 21:49:04] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-17 21:49:04] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-17 21:49:04] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-17 21:49:04] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-17 21:49:12] ...trap/engines/engine.py.321: eval: epoch 2 | batch 0/1578 [I 2022-10-17 21:49:12] ...trap/engines/engine.py.325: elapsed: 0:00:10 | left: 4:38:26 [I 2022-10-17 21:49:12] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.607200 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.718100 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.291500 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.590700 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.709000 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.400000 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.403113 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_std: 0.010385 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.017058 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.017038 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.010920 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.017550 [S 2022-10-17 22:29:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.017210 [I 2022-10-17 22:29:54] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.med_im2recipe_mean [I 2022-10-17 22:29:54] ...trap/engines/engine.py.470: Saving model... [W 2022-10-17 22:29:54] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-17 22:29:54] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-17 22:29:54] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-17 22:29:55] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-17 22:29:57] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-17 22:30:02] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-17 22:30:02] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-17 22:30:02] ...trap/engines/engine.py.470: Saving model... [I 2022-10-17 22:30:05] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-17 22:30:10] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-17 22:30:10] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-17 22:30:10] ...trap/engines/engine.py.470: Saving model... [I 2022-10-17 22:30:13] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-17 22:30:18] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-17 22:30:18] ...trap/engines/engine.py.163: Training model on trainset for epoch 3 [I 2022-10-17 22:30:18] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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epoch 3 | batch 7425/7425 [I 2022-10-18 02:00:38] ...trap/engines/engine.py.228: elapsed: 3:30:19 | left: 0:00:00 [I 2022-10-18 02:00:38] ...trap/engines/engine.py.229: process: 4.50821 | load: 3.75436 [I 2022-10-18 02:00:38] ...trap/engines/engine.py.230: loss: 0.31967 [I 2022-10-18 02:00:38] ...optimizers/trijoint.py.151: total_norm: 3.181765 [S 2022-10-18 02:00:40] ...trap/engines/engine.py.129: train_epoch.epoch: 3 [S 2022-10-18 02:00:40] ...trap/engines/engine.py.129: train_epoch.loss: 0.4668170115495351 [I 2022-10-18 02:00:40] ...iterions/vlp_triplet.py.80: margin = 0.07 [I 2022-10-18 02:00:40] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 3 [I 2022-10-18 02:00:40] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.626600 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.738500 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.306100 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.614800 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.728800 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.300000 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.400000 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_std: 0.018378 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.016390 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.013589 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.010616 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.017383 [S 2022-10-18 02:41:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.009867 [I 2022-10-18 02:41:34] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.med_im2recipe_mean [I 2022-10-18 02:41:34] ...trap/engines/engine.py.470: Saving model... [W 2022-10-18 02:41:34] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-18 02:41:34] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-18 02:41:34] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-18 02:41:35] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-18 02:41:37] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-18 02:41:42] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-18 02:41:42] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-18 02:41:42] ...trap/engines/engine.py.470: Saving model... [I 2022-10-18 02:41:45] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-18 02:41:50] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-18 02:41:50] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-18 02:41:50] ...trap/engines/engine.py.470: Saving model... [I 2022-10-18 02:41:53] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-18 02:41:57] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-18 02:41:57] ...trap/engines/engine.py.163: Training model on trainset for epoch 4 [I 2022-10-18 02:41:57] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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...trap/engines/engine.py.230: loss: 0.41039 [I 2022-10-18 06:00:34] ...optimizers/trijoint.py.151: total_norm: 3.368485 [I 2022-10-18 06:00:50] ...trap/engines/engine.py.224: train: epoch 4 | batch 7410/7425 [I 2022-10-18 06:00:50] ...trap/engines/engine.py.228: elapsed: 3:18:52 | left: 0:00:21 [I 2022-10-18 06:00:50] ...trap/engines/engine.py.229: process: 0.72631 | load: 0.00015 [I 2022-10-18 06:00:50] ...trap/engines/engine.py.230: loss: 0.42038 [I 2022-10-18 06:00:50] ...optimizers/trijoint.py.151: total_norm: 3.408053 [I 2022-10-18 06:01:10] ...trap/engines/engine.py.224: train: epoch 4 | batch 7420/7425 [I 2022-10-18 06:01:10] ...trap/engines/engine.py.228: elapsed: 3:19:12 | left: 0:00:09 [I 2022-10-18 06:01:10] ...trap/engines/engine.py.229: process: 0.72739 | load: 0.00002 [I 2022-10-18 06:01:10] ...trap/engines/engine.py.230: loss: 0.36335 [I 2022-10-18 06:01:10] ...optimizers/trijoint.py.151: total_norm: 3.633444 [I 2022-10-18 06:01:17] ...trap/engines/engine.py.224: train: epoch 4 | batch 7425/7425 [I 2022-10-18 06:01:17] ...trap/engines/engine.py.228: elapsed: 3:19:19 | left: 0:00:00 [I 2022-10-18 06:01:17] ...trap/engines/engine.py.229: process: 0.72484 | load: 0.00007 [I 2022-10-18 06:01:17] ...trap/engines/engine.py.230: loss: 0.42548 [I 2022-10-18 06:01:17] ...optimizers/trijoint.py.151: total_norm: 3.508900 [S 2022-10-18 06:01:18] ...trap/engines/engine.py.129: train_epoch.epoch: 4 [S 2022-10-18 06:01:18] ...trap/engines/engine.py.129: train_epoch.loss: 0.45478923737986726 [I 2022-10-18 06:01:18] ...iterions/vlp_triplet.py.80: margin = 0.07500000000000001 [I 2022-10-18 06:01:19] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 4 [I 2022-10-18 06:01:19] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [W 2022-10-18 06:01:21] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-18 06:01:21] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-18 06:01:21] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-18 06:01:22] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-18 06:01:29] ...trap/engines/engine.py.321: eval: epoch 4 | batch 0/1578 [I 2022-10-18 06:01:29] ...trap/engines/engine.py.325: elapsed: 0:00:10 | left: 4:34:51 [I 2022-10-18 06:01:29] ...trap/engines/engine.py.326: process: 10.45109 | load: 9.99183 [I 2022-10-18 06:01:44] ...trap/engines/engine.py.321: eval: epoch 4 | batch 10/1578 [I 2022-10-18 06:01:44] ...trap/engines/engine.py.325: elapsed: 0:00:25 | left: 1:04:17 [I 2022-10-18 06:01:44] ...trap/engines/engine.py.326: process: 0.37891 | load: 0.00014 [I 2022-10-18 06:02:02] ...trap/engines/engine.py.321: eval: epoch 4 | batch 20/1578 [I 2022-10-18 06:02:02] ...trap/engines/engine.py.325: elapsed: 0:00:43 | left: 0:54:29 [I 2022-10-18 06:02:02] ...trap/engines/engine.py.326: process: 4.74174 | load: 4.30699 [I 2022-10-18 06:02:15] ...trap/engines/engine.py.321: eval: epoch 4 | batch 30/1578 [I 2022-10-18 06:02:15] ...trap/engines/engine.py.325: elapsed: 0:00:56 | left: 0:35:36 [I 2022-10-18 06:02:15] ...trap/engines/engine.py.326: process: 0.38308 | load: 0.00017 [I 2022-10-18 06:02:35] ...trap/engines/engine.py.321: eval: epoch 4 | batch 40/1578 [I 2022-10-18 06:02:35] ...trap/engines/engine.py.325: elapsed: 0:01:16 | left: 0:53:36 [I 2022-10-18 06:02:35] ...trap/engines/engine.py.326: process: 4.84881 | load: 4.42667 [I 2022-10-18 06:02:48] ...trap/engines/engine.py.321: eval: epoch 4 | batch 50/1578 [I 2022-10-18 06:02:48] ...trap/engines/engine.py.325: elapsed: 0:01:29 | left: 0:35:48 [I 2022-10-18 06:02:48] ...trap/engines/engine.py.326: process: 0.37522 | load: 0.00017 [I 2022-10-18 06:03:07] ...trap/engines/engine.py.321: eval: epoch 4 | batch 60/1578 [I 2022-10-18 06:03:07] ...trap/engines/engine.py.325: elapsed: 0:01:48 | left: 0:50:35 [I 2022-10-18 06:03:07] ...trap/engines/engine.py.326: process: 5.13874 | load: 4.69654 [I 2022-10-18 06:03:20] ...trap/engines/engine.py.321: eval: epoch 4 | batch 70/1578 [I 2022-10-18 06:03:20] ...trap/engines/engine.py.325: elapsed: 0:02:01 | left: 0:35:48 [I 2022-10-18 06:03:20] ...trap/engines/engine.py.326: process: 0.36968 | load: 0.00014 [I 2022-10-18 06:03:38] ...trap/engines/engine.py.321: eval: epoch 4 | batch 80/1578 [I 2022-10-18 06:03:38] ...trap/engines/engine.py.325: elapsed: 0:02:19 | left: 0:46:35 [I 2022-10-18 06:03:38] ...trap/engines/engine.py.326: process: 4.41476 | load: 3.98329 [I 2022-10-18 06:03:51] ...trap/engines/engine.py.321: eval: epoch 4 | batch 90/1578 [I 2022-10-18 06:03:51] ...trap/engines/engine.py.325: elapsed: 0:02:32 | left: 0:33:44 [I 2022-10-18 06:03:51] ...trap/engines/engine.py.326: process: 0.36896 | load: 0.00014 [I 2022-10-18 11:48:17] ...ytorch/bootstrap/run.py.73: Saving environment info [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: options: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: dataset: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: aux_kw_path: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_titles_kw.json [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_titles_kw.json [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_titles_kw.json [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: batch_sampler: random [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: batch_size: 96 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: database: lmdb [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: dir: /gpfsdswork/dataset/Recipe1M+/images_recipe1M+ [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: eval_split: val [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: freq_mismatch: 0.0 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: image_from: database [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: import: recipe1m.datasets.factory [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: kw_path: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_ingr_kw.json [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_ingr_kw.json [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_ingr_kw.json [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: name: recipe1m_13m [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: nb_classes: 1048 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: nb_threads: 4 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: orig_ids_eval: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: path_ids: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/original_ids.json [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: engine: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-18 11:48:23] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-18 11:48:24] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a103', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-18 11:48:24] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-18 11:48:24] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-18 11:48:24] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-18 11:50:16] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-18 11:50:28] ...tasets/recipe1m_13m.py.293: randkw_p... 0.3 [I 2022-10-18 11:52:10] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-18 11:52:10] ...tasets/recipe1m_13m.py.293: randkw_p... None [I 2022-10-18 11:52:10] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-18 11:52:10] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-18 11:52:10] ...strap/models/factory.py.21: Creating model... [I 2022-10-18 11:52:13] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-18 11:52:17] ...e_networks/networks.py.145: cuda [I 2022-10-18 11:52:18] ...networks/tfood_vicha.py.49: Load VCs encoder... [I 2022-10-18 11:52:20] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-18 11:52:20] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-18 11:52:20] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-18 11:52:20] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-18 11:52:22] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-18 11:52:22] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-18 11:52:22] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-18 11:52:23] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-18 11:52:23] ...trap/engines/engine.py.440: Loading model... [I 2022-10-18 11:52:29] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-18 11:52:34] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-18 11:52:34] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-18 11:52:34] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-18 11:52:34] ...trap/engines/engine.py.163: Training model on trainset for epoch 4 [I 2022-10-18 11:52:34] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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...optimizers/trijoint.py.151: total_norm: 3.126476 [I 2022-10-18 11:54:15] ...trap/engines/engine.py.224: train: epoch 4 | batch 50/7425 [I 2022-10-18 11:54:15] ...trap/engines/engine.py.228: elapsed: 0:01:40 | left: 3:12:19 [I 2022-10-18 11:54:15] ...trap/engines/engine.py.229: process: 0.73455 | load: 0.00014 [I 2022-10-18 11:54:15] ...trap/engines/engine.py.230: loss: 0.45716 [I 2022-10-18 11:54:15] ...optimizers/trijoint.py.151: total_norm: 3.657475 [I 2022-10-18 11:54:36] ...trap/engines/engine.py.224: train: epoch 4 | batch 60/7425 [I 2022-10-18 11:54:36] ...trap/engines/engine.py.228: elapsed: 0:02:01 | left: 4:49:43 [I 2022-10-18 11:54:36] ...trap/engines/engine.py.229: process: 5.97851 | load: 5.25065 [I 2022-10-18 11:54:36] ...trap/engines/engine.py.230: loss: 0.37751 [I 2022-10-18 11:54:36] ...optimizers/trijoint.py.151: total_norm: 3.699319 [I 2022-10-18 11:54:51] ...trap/engines/engine.py.224: train: epoch 4 | batch 70/7425 [I 2022-10-18 11:54:51] ...trap/engines/engine.py.228: elapsed: 0:02:16 | left: 3:18:34 [I 2022-10-18 11:54:51] ...trap/engines/engine.py.229: process: 0.72778 | load: 0.00013 [I 2022-10-18 11:54:51] ...trap/engines/engine.py.230: loss: 0.35790 [I 2022-10-18 11:54:51] ...optimizers/trijoint.py.151: total_norm: 3.169583 [I 2022-10-18 11:55:11] ...trap/engines/engine.py.224: train: epoch 4 | batch 80/7425 [I 2022-10-18 11:55:11] ...trap/engines/engine.py.228: elapsed: 0:02:36 | left: 4:13:07 [I 2022-10-18 11:55:11] ...trap/engines/engine.py.229: process: 4.78730 | load: 4.04791 [I 2022-10-18 11:55:11] ...trap/engines/engine.py.230: loss: 0.47860 [I 2022-10-18 11:55:11] ...optimizers/trijoint.py.151: total_norm: 4.389018 [I 2022-10-18 11:55:26] ...trap/engines/engine.py.224: train: epoch 4 | batch 90/7425 [I 2022-10-18 11:55:26] ...trap/engines/engine.py.228: elapsed: 0:02:51 | left: 3:17:32 [I 2022-10-18 11:55:26] ...trap/engines/engine.py.229: process: 0.75527 | load: 0.00014 [I 2022-10-18 11:55:26] ...trap/engines/engine.py.230: loss: 0.49225 [I 2022-10-18 11:55:26] ...optimizers/trijoint.py.151: total_norm: 4.033569 [I 2022-10-18 11:55:45] ...trap/engines/engine.py.224: train: epoch 4 | batch 100/7425 [I 2022-10-18 11:55:45] ...trap/engines/engine.py.228: elapsed: 0:03:10 | left: 4:08:44 [I 2022-10-18 11:55:45] ...trap/engines/engine.py.229: process: 4.61110 | load: 3.86668 [I 2022-10-18 11:55:45] ...trap/engines/engine.py.230: loss: 0.41730 [I 2022-10-18 11:55:45] ...optimizers/trijoint.py.151: total_norm: 4.787673 [I 2022-10-18 11:56:01] ...trap/engines/engine.py.224: train: epoch 4 | batch 110/7425 [I 2022-10-18 11:56:01] ...trap/engines/engine.py.228: elapsed: 0:03:26 | left: 3:17:49 [I 2022-10-18 11:56:01] ...trap/engines/engine.py.229: process: 0.72788 | load: 0.00008 [I 2022-10-18 11:56:01] ...trap/engines/engine.py.230: loss: 0.48684 [I 2022-10-18 11:56:01] ...optimizers/trijoint.py.151: total_norm: 3.626703 [I 2022-10-18 11:56:22] ...trap/engines/engine.py.224: train: 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| load: 3.79774 [I 2022-10-18 11:56:57] ...trap/engines/engine.py.230: loss: 0.42282 [I 2022-10-18 11:56:57] ...optimizers/trijoint.py.151: total_norm: 3.206102 [I 2022-10-18 11:57:10] ...trap/engines/engine.py.224: train: epoch 4 | batch 150/7425 [I 2022-10-18 11:57:10] ...trap/engines/engine.py.228: elapsed: 0:04:35 | left: 3:00:28 [I 2022-10-18 11:57:10] ...trap/engines/engine.py.229: process: 0.72433 | load: 0.00014 [I 2022-10-18 11:57:10] ...trap/engines/engine.py.230: loss: 0.34972 [I 2022-10-18 11:57:10] ...optimizers/trijoint.py.151: total_norm: 2.913903 [I 2022-10-18 11:57:36] ...trap/engines/engine.py.224: train: epoch 4 | batch 160/7425 [I 2022-10-18 11:57:36] ...trap/engines/engine.py.228: elapsed: 0:05:01 | left: 6:19:11 [I 2022-10-18 11:57:36] ...trap/engines/engine.py.229: process: 9.18728 | load: 8.42984 [I 2022-10-18 11:57:36] ...trap/engines/engine.py.230: loss: 0.56720 [I 2022-10-18 11:57:36] ...optimizers/trijoint.py.151: total_norm: 4.075524 [I 2022-10-18 11:57:51] ...trap/engines/engine.py.224: train: epoch 4 | batch 170/7425 [I 2022-10-18 11:57:51] ...trap/engines/engine.py.228: elapsed: 0:05:16 | left: 3:17:22 [I 2022-10-18 11:57:51] ...trap/engines/engine.py.229: process: 0.75067 | load: 0.00014 [I 2022-10-18 11:57:51] ...trap/engines/engine.py.230: loss: 0.43459 [I 2022-10-18 11:57:51] ...optimizers/trijoint.py.151: total_norm: 3.817239 [I 2022-10-18 11:58:08] ...trap/engines/engine.py.224: train: epoch 4 | batch 180/7425 [I 2022-10-18 11:58:08] ...trap/engines/engine.py.228: elapsed: 0:05:33 | left: 3:33:46 [I 2022-10-18 11:58:08] ...trap/engines/engine.py.229: process: 3.48971 | load: 2.73159 [I 2022-10-18 11:58:08] ...trap/engines/engine.py.230: loss: 0.50546 [I 2022-10-18 11:58:08] ...optimizers/trijoint.py.151: total_norm: 4.676411 [I 2022-10-18 11:58:22] ...trap/engines/engine.py.224: train: epoch 4 | batch 190/7425 [I 2022-10-18 11:58:22] ...trap/engines/engine.py.228: elapsed: 0:05:47 | left: 2:56:38 [I 2022-10-18 11:58:22] ...trap/engines/engine.py.229: process: 0.72359 | load: 0.00013 [I 2022-10-18 11:58:22] ...trap/engines/engine.py.230: loss: 0.41262 [I 2022-10-18 11:58:22] ...optimizers/trijoint.py.151: total_norm: 3.317519 [I 2022-10-18 11:58:41] ...trap/engines/engine.py.224: train: epoch 4 | batch 200/7425 [I 2022-10-18 11:58:41] ...trap/engines/engine.py.228: elapsed: 0:06:06 | left: 3:57:52 [I 2022-10-18 11:58:41] ...trap/engines/engine.py.229: process: 4.28455 | load: 3.55274 [I 2022-10-18 11:58:41] ...trap/engines/engine.py.230: loss: 0.44571 [I 2022-10-18 11:58:41] ...optimizers/trijoint.py.151: total_norm: 3.732444 [I 2022-10-18 11:58:54] ...trap/engines/engine.py.224: train: epoch 4 | batch 210/7425 [I 2022-10-18 11:58:54] ...trap/engines/engine.py.228: elapsed: 0:06:19 | left: 2:41:23 [I 2022-10-18 11:58:54] ...trap/engines/engine.py.229: process: 0.75184 | load: 0.00014 [I 2022-10-18 11:58:54] ...trap/engines/engine.py.230: loss: 0.45771 [I 2022-10-18 11:58:54] 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epoch 4 | batch 7425/7425 [I 2022-10-18 15:05:54] ...trap/engines/engine.py.228: elapsed: 3:13:19 | left: 0:00:00 [I 2022-10-18 15:05:54] ...trap/engines/engine.py.229: process: 0.74159 | load: 0.00009 [I 2022-10-18 15:05:54] ...trap/engines/engine.py.230: loss: 0.42244 [I 2022-10-18 15:05:54] ...optimizers/trijoint.py.151: total_norm: 3.502806 [S 2022-10-18 15:05:56] ...trap/engines/engine.py.129: train_epoch.epoch: 4 [S 2022-10-18 15:05:56] ...trap/engines/engine.py.129: train_epoch.loss: 0.44853603859940466 [I 2022-10-18 15:05:56] ...iterions/vlp_triplet.py.80: margin = 0.07 [I 2022-10-18 15:05:57] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 4 [I 2022-10-18 15:05:57] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [W 2022-10-18 15:06:01] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-18 15:06:01] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-18 15:06:01] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-18 15:06:08] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-18 15:06:08] ...trap/engines/engine.py.321: eval: epoch 4 | batch 0/1578 [I 2022-10-18 15:06:08] ...trap/engines/engine.py.325: elapsed: 0:00:11 | left: 4:56:06 [I 2022-10-18 15:06:08] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.643000 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.753400 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.322800 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.629000 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.743500 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.000000 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.000000 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_std: 0.013746 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.013498 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.012917 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.016744 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.017686 [S 2022-10-18 15:55:18] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.017380 [I 2022-10-18 15:55:35] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.med_im2recipe_mean [I 2022-10-18 15:55:35] ...trap/engines/engine.py.470: Saving model... [W 2022-10-18 15:55:35] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-18 15:55:35] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-18 15:55:35] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-18 15:55:37] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-18 15:55:38] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-18 15:55:43] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-18 15:55:43] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-18 15:55:43] ...trap/engines/engine.py.470: Saving model... [I 2022-10-18 15:55:46] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-18 15:55:51] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-18 15:55:51] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-18 15:55:51] ...trap/engines/engine.py.470: Saving model... [I 2022-10-18 15:55:54] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-18 15:55:59] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-18 15:55:59] ...trap/engines/engine.py.163: Training model on trainset for epoch 5 [I 2022-10-18 15:55:59] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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...trap/engines/engine.py.230: loss: 0.36114 [I 2022-10-18 19:26:38] ...optimizers/trijoint.py.151: total_norm: 14.460070 [I 2022-10-18 19:26:45] ...trap/engines/engine.py.224: train: epoch 5 | batch 7425/7425 [I 2022-10-18 19:26:45] ...trap/engines/engine.py.228: elapsed: 3:30:46 | left: 0:00:00 [I 2022-10-18 19:26:45] ...trap/engines/engine.py.229: process: 1.04049 | load: 0.24382 [I 2022-10-18 19:26:45] ...trap/engines/engine.py.230: loss: 0.44731 [I 2022-10-18 19:26:45] ...optimizers/trijoint.py.151: total_norm: 19.355635 [S 2022-10-18 19:26:47] ...trap/engines/engine.py.129: train_epoch.epoch: 5 [S 2022-10-18 19:26:47] ...trap/engines/engine.py.129: train_epoch.loss: 0.4380903008762409 [I 2022-10-18 19:26:47] ...iterions/vlp_triplet.py.80: margin = 0.07500000000000001 [I 2022-10-18 19:26:47] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 5 [I 2022-10-18 19:26:48] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [W 2022-10-18 19:26:49] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-18 19:26:49] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-18 19:26:49] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-18 19:26:50] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-18 19:26:57] ...trap/engines/engine.py.321: eval: epoch 5 | batch 0/1578 [I 2022-10-18 19:26:57] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:05:11 [I 2022-10-18 19:26:57] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.669900 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.771500 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.334900 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.648000 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.763200 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.489898 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.000000 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_std: 0.013063 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.009894 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.006622 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.008252 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.008222 [S 2022-10-18 20:10:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.010438 [I 2022-10-18 20:10:53] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.med_im2recipe_mean [I 2022-10-18 20:10:53] ...trap/engines/engine.py.470: Saving model... [W 2022-10-18 20:10:53] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-18 20:10:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-18 20:10:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-18 20:10:55] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-18 20:10:57] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-18 20:11:03] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-18 20:11:03] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-18 20:11:03] ...trap/engines/engine.py.470: Saving model... [I 2022-10-18 20:11:06] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-18 20:11:14] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-18 20:11:14] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-18 20:11:14] ...trap/engines/engine.py.470: Saving model... [I 2022-10-18 20:11:17] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-18 20:11:23] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-18 20:11:23] ...trap/engines/engine.py.163: Training model on trainset for epoch 6 [I 2022-10-18 20:11:23] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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train: epoch 6 | batch 7425/7425 [I 2022-10-18 23:44:50] ...trap/engines/engine.py.228: elapsed: 3:33:27 | left: 0:00:00 [I 2022-10-18 23:44:50] ...trap/engines/engine.py.229: process: 0.82019 | load: 0.00012 [I 2022-10-18 23:44:50] ...trap/engines/engine.py.230: loss: 0.35265 [I 2022-10-18 23:44:50] ...optimizers/trijoint.py.151: total_norm: 16.536486 [S 2022-10-18 23:44:52] ...trap/engines/engine.py.129: train_epoch.epoch: 6 [S 2022-10-18 23:44:52] ...trap/engines/engine.py.129: train_epoch.loss: 0.4344747278998876 [I 2022-10-18 23:44:52] ...iterions/vlp_triplet.py.80: margin = 0.08000000000000002 [I 2022-10-18 23:44:52] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 6 [I 2022-10-18 23:44:52] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.674600 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.778200 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.351300 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.659400 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.768700 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.403113 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.300000 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_std: 0.012706 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.009145 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011763 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.014000 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.013336 [S 2022-10-19 00:29:08] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.010687 [I 2022-10-19 00:29:25] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.med_im2recipe_mean [I 2022-10-19 00:29:25] ...trap/engines/engine.py.470: Saving model... [W 2022-10-19 00:29:25] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-19 00:29:25] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-19 00:29:25] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-19 00:29:28] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-19 00:29:29] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 00:29:35] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 00:29:35] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-19 00:29:35] ...trap/engines/engine.py.470: Saving model... [I 2022-10-19 00:29:38] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 00:29:44] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 00:29:44] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-19 00:29:44] ...trap/engines/engine.py.470: Saving model... [I 2022-10-19 00:29:48] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 00:29:54] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 00:29:54] ...trap/engines/engine.py.163: Training model on trainset for epoch 7 [I 2022-10-19 00:29:54] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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train: epoch 7 | batch 7425/7425 [I 2022-10-19 04:03:56] ...trap/engines/engine.py.228: elapsed: 3:34:02 | left: 0:00:00 [I 2022-10-19 04:03:56] ...trap/engines/engine.py.229: process: 0.78841 | load: 0.00010 [I 2022-10-19 04:03:56] ...trap/engines/engine.py.230: loss: 0.47541 [I 2022-10-19 04:03:56] ...optimizers/trijoint.py.151: total_norm: 23.189840 [S 2022-10-19 04:03:58] ...trap/engines/engine.py.129: train_epoch.epoch: 7 [S 2022-10-19 04:03:58] ...trap/engines/engine.py.129: train_epoch.loss: 0.4277698449989133 [I 2022-10-19 04:03:58] ...iterions/vlp_triplet.py.80: margin = 0.08500000000000002 [I 2022-10-19 04:03:59] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 7 [I 2022-10-19 04:03:59] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [W 2022-10-19 04:04:00] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-19 04:04:00] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-19 04:04:00] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-19 04:04:02] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-19 04:04:09] ...trap/engines/engine.py.321: eval: epoch 7 | batch 0/1578 [I 2022-10-19 04:04:09] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:16:20 [I 2022-10-19 04:04:09] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.685400 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.788700 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.359400 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.668600 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.782400 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.300000 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.489898 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_std: 0.013790 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.017007 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011420 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.020500 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.015692 [S 2022-10-19 04:46:11] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.010800 [I 2022-10-19 04:47:33] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.med_im2recipe_mean [I 2022-10-19 04:47:33] ...trap/engines/engine.py.470: Saving model... [W 2022-10-19 04:47:33] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-19 04:47:33] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-19 04:47:33] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-19 04:47:35] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-19 04:47:37] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 04:47:43] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 04:47:43] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-19 04:47:43] ...trap/engines/engine.py.470: Saving model... [I 2022-10-19 04:47:46] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 04:47:52] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 04:47:52] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-19 04:47:52] ...trap/engines/engine.py.470: Saving model... [I 2022-10-19 04:47:55] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 04:48:01] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 04:48:01] ...trap/engines/engine.py.163: Training model on trainset for epoch 8 [I 2022-10-19 04:48:01] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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...ytorch/bootstrap/run.py.75: misc: [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-19 08:22:44] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-19 08:22:45] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a101', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-19 08:22:45] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-19 08:22:45] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-19 08:22:45] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-19 08:24:42] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-19 08:24:54] ...tasets/recipe1m_13m.py.293: randkw_p... 0.3 [I 2022-10-19 08:26:42] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-19 08:26:42] ...tasets/recipe1m_13m.py.293: randkw_p... None [I 2022-10-19 08:26:42] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-19 08:26:42] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-19 08:26:42] ...strap/models/factory.py.21: Creating model... [I 2022-10-19 08:26:45] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-19 08:26:48] ...e_networks/networks.py.145: cuda [I 2022-10-19 08:26:50] ...networks/tfood_vicha.py.49: Load VCs encoder... [I 2022-10-19 08:26:51] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-19 08:26:51] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-19 08:26:51] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-19 08:26:51] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-19 08:26:54] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-19 08:26:54] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-19 08:26:54] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-19 08:26:55] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-19 08:26:55] ...trap/engines/engine.py.440: Loading model... [I 2022-10-19 08:27:01] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-19 08:27:09] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-19 08:27:09] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-19 08:27:09] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-19 08:27:09] ...trap/engines/engine.py.163: Training model on trainset for epoch 8 [I 2022-10-19 08:27:09] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [I 2022-10-19 08:27:25] ...trap/engines/engine.py.224: train: epoch 8 | batch 0/7425 [I 2022-10-19 08:27:25] ...trap/engines/engine.py.228: elapsed: 0:00:15 | left: 1 day, 8:37:02 [I 2022-10-19 08:27:25] ...trap/engines/engine.py.229: process: 15.81449 | load: 10.86721 [I 2022-10-19 08:27:25] ...trap/engines/engine.py.230: loss: 0.42225 [I 2022-10-19 08:27:25] ...optimizers/trijoint.py.151: total_norm: 14.380232 [I 2022-10-19 08:27:39] ...trap/engines/engine.py.224: train: epoch 8 | batch 10/7425 [I 2022-10-19 08:27:39] ...trap/engines/engine.py.228: elapsed: 0:00:29 | left: 6:22:57 [I 2022-10-19 08:27:39] ...trap/engines/engine.py.229: process: 0.78302 | load: 0.00014 [I 2022-10-19 08:27:39] ...trap/engines/engine.py.230: loss: 0.31597 [I 2022-10-19 08:27:39] ...optimizers/trijoint.py.151: total_norm: 14.650458 [I 2022-10-19 08:28:01] ...trap/engines/engine.py.224: train: epoch 8 | batch 20/7425 [I 2022-10-19 08:28:01] ...trap/engines/engine.py.228: elapsed: 0:00:51 | left: 5:00:32 [I 2022-10-19 08:28:01] ...trap/engines/engine.py.229: process: 4.85522 | load: 4.02862 [I 2022-10-19 08:28:01] ...trap/engines/engine.py.230: loss: 0.35840 [I 2022-10-19 08:28:01] ...optimizers/trijoint.py.151: total_norm: 19.692822 [I 2022-10-19 08:28:17] ...trap/engines/engine.py.224: train: epoch 8 | batch 30/7425 [I 2022-10-19 08:28:17] ...trap/engines/engine.py.228: elapsed: 0:01:07 | left: 3:34:29 [I 2022-10-19 08:28:17] ...trap/engines/engine.py.229: process: 0.81376 | load: 0.00018 [I 2022-10-19 08:28:17] ...trap/engines/engine.py.230: loss: 0.42204 [I 2022-10-19 08:28:17] ...optimizers/trijoint.py.151: total_norm: 16.174953 [I 2022-10-19 08:28:39] ...trap/engines/engine.py.224: train: epoch 8 | batch 40/7425 [I 2022-10-19 08:28:39] ...trap/engines/engine.py.228: elapsed: 0:01:30 | left: 5:04:38 [I 2022-10-19 08:28:39] ...trap/engines/engine.py.229: process: 6.04063 | load: 5.23930 [I 2022-10-19 08:28:39] ...trap/engines/engine.py.230: loss: 0.52392 [I 2022-10-19 08:28:39] ...optimizers/trijoint.py.151: total_norm: 20.804630 [I 2022-10-19 08:28:55] ...trap/engines/engine.py.224: train: epoch 8 | batch 50/7425 [I 2022-10-19 08:28:55] ...trap/engines/engine.py.228: elapsed: 0:01:45 | left: 3:28:41 [I 2022-10-19 08:28:55] ...trap/engines/engine.py.229: process: 0.78534 | load: 0.00015 [I 2022-10-19 08:28:55] ...trap/engines/engine.py.230: loss: 0.52205 [I 2022-10-19 08:28:55] ...optimizers/trijoint.py.151: total_norm: 28.822315 [I 2022-10-19 08:29:17] ...trap/engines/engine.py.224: train: epoch 8 | batch 60/7425 [I 2022-10-19 08:29:17] ...trap/engines/engine.py.228: elapsed: 0:02:07 | left: 4:42:17 [I 2022-10-19 08:29:17] ...trap/engines/engine.py.229: process: 5.28476 | load: 4.46919 [I 2022-10-19 08:29:17] ...trap/engines/engine.py.230: loss: 0.40626 [I 2022-10-19 08:29:17] ...optimizers/trijoint.py.151: total_norm: 19.192684 [I 2022-10-19 08:29:33] ...trap/engines/engine.py.224: train: epoch 8 | batch 70/7425 [I 2022-10-19 08:29:33] ...trap/engines/engine.py.228: elapsed: 0:02:23 | left: 3:37:08 [I 2022-10-19 08:29:33] ...trap/engines/engine.py.229: process: 0.80243 | load: 0.00017 [I 2022-10-19 08:29:33] ...trap/engines/engine.py.230: loss: 0.38021 [I 2022-10-19 08:29:33] ...optimizers/trijoint.py.151: total_norm: 18.077427 [I 2022-10-19 08:29:52] ...trap/engines/engine.py.224: train: epoch 8 | batch 80/7425 [I 2022-10-19 08:29:52] ...trap/engines/engine.py.228: elapsed: 0:02:42 | left: 4:24:11 [I 2022-10-19 08:29:52] ...trap/engines/engine.py.229: process: 5.34257 | load: 4.52678 [I 2022-10-19 08:29:52] ...trap/engines/engine.py.230: loss: 0.35741 [I 2022-10-19 08:29:52] ...optimizers/trijoint.py.151: total_norm: 13.840885 [I 2022-10-19 08:30:08] ...trap/engines/engine.py.224: train: epoch 8 | batch 90/7425 [I 2022-10-19 08:30:08] ...trap/engines/engine.py.228: elapsed: 0:02:58 | left: 3:22:31 [I 2022-10-19 08:30:08] ...trap/engines/engine.py.229: process: 0.78509 | load: 0.00016 [I 2022-10-19 08:30:08] 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...optimizers/trijoint.py.151: total_norm: 15.271647 [I 2022-10-19 11:53:52] ...trap/engines/engine.py.224: train: epoch 8 | batch 7360/7425 [I 2022-10-19 11:53:52] ...trap/engines/engine.py.228: elapsed: 3:26:42 | left: 0:01:30 [I 2022-10-19 11:53:52] ...trap/engines/engine.py.229: process: 0.77376 | load: 0.00015 [I 2022-10-19 11:53:52] ...trap/engines/engine.py.230: loss: 0.41389 [I 2022-10-19 11:53:52] ...optimizers/trijoint.py.151: total_norm: 18.836082 [I 2022-10-19 11:54:10] ...trap/engines/engine.py.224: train: epoch 8 | batch 7370/7425 [I 2022-10-19 11:54:10] ...trap/engines/engine.py.228: elapsed: 3:27:00 | left: 0:01:35 [I 2022-10-19 11:54:10] ...trap/engines/engine.py.229: process: 0.78834 | load: 0.00007 [I 2022-10-19 11:54:10] ...trap/engines/engine.py.230: loss: 0.40689 [I 2022-10-19 11:54:10] ...optimizers/trijoint.py.151: total_norm: 19.841135 [I 2022-10-19 11:54:26] ...trap/engines/engine.py.224: train: epoch 8 | batch 7380/7425 [I 2022-10-19 11:54:26] 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[W 2022-10-19 11:55:53] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-19 11:55:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-19 11:55:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-19 11:55:57] ...trap/engines/engine.py.321: eval: epoch 8 | batch 0/1578 [I 2022-10-19 11:55:57] ...trap/engines/engine.py.325: elapsed: 0:00:10 | left: 4:38:30 [I 2022-10-19 11:55:57] ...trap/engines/engine.py.326: process: 10.58967 | load: 9.50409 [I 2022-10-19 11:56:00] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-19 11:56:11] ...trap/engines/engine.py.321: eval: epoch 8 | batch 10/1578 [I 2022-10-19 11:56:11] ...trap/engines/engine.py.325: elapsed: 0:00:24 | left: 1:02:48 [I 2022-10-19 11:56:11] ...trap/engines/engine.py.326: process: 0.53053 | load: 0.00007 [I 2022-10-19 11:56:29] ...trap/engines/engine.py.321: eval: epoch 8 | batch 20/1578 [I 2022-10-19 11:56:29] ...trap/engines/engine.py.325: elapsed: 0:00:42 | left: 0:50:39 [I 2022-10-19 11:56:29] ...trap/engines/engine.py.326: process: 3.84407 | load: 3.36528 [I 2022-10-19 11:56:44] ...trap/engines/engine.py.321: eval: epoch 8 | batch 30/1578 [I 2022-10-19 11:56:44] ...trap/engines/engine.py.325: elapsed: 0:00:57 | left: 0:40:31 [I 2022-10-19 11:56:44] ...trap/engines/engine.py.326: process: 0.49210 | load: 0.00007 [I 2022-10-19 11:57:02] ...trap/engines/engine.py.321: eval: epoch 8 | batch 40/1578 [I 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12:39:58] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.010070 [S 2022-10-19 12:39:58] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.016138 [S 2022-10-19 12:39:58] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.009049 [S 2022-10-19 12:39:58] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.013869 [I 2022-10-19 12:40:18] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.med_im2recipe_mean [I 2022-10-19 12:40:18] ...trap/engines/engine.py.470: Saving model... [W 2022-10-19 12:40:18] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-19 12:40:18] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-19 12:40:18] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-19 12:40:21] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-19 12:40:21] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 12:40:27] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 12:40:27] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-19 12:40:27] ...trap/engines/engine.py.470: Saving model... [I 2022-10-19 12:40:30] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 12:40:36] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 12:40:36] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-19 12:40:36] ...trap/engines/engine.py.470: Saving model... [I 2022-10-19 12:40:39] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 12:40:45] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 12:40:45] ...trap/engines/engine.py.163: Training model on trainset for epoch 9 [I 2022-10-19 12:40:45] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-19 16:21:17] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-19 16:21:17] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-19 16:21:17] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-19 16:21:19] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-19 16:21:26] ...trap/engines/engine.py.321: eval: epoch 9 | batch 0/1578 [I 2022-10-19 16:21:26] ...trap/engines/engine.py.325: elapsed: 0:00:11 | left: 4:54:03 [I 2022-10-19 16:21:26] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.691100 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.797900 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.367500 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.677400 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.787500 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.000000 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.489898 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_std: 0.019170 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.015808 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.013187 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.015220 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.012126 [S 2022-10-19 17:06:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.013493 [I 2022-10-19 17:07:10] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-19 17:07:10] ...trap/engines/engine.py.470: Saving model... [W 2022-10-19 17:07:10] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-19 17:07:10] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-19 17:07:10] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-19 17:07:13] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-19 17:07:13] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 17:07:19] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 17:07:19] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-19 17:07:19] ...trap/engines/engine.py.470: Saving model... [I 2022-10-19 17:07:22] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 17:07:28] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 17:07:28] ...trap/engines/engine.py.163: Training model on trainset for epoch 10 [I 2022-10-19 17:07:28] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-19 20:39:56] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-19 20:39:56] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-19 20:39:56] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-19 20:39:58] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-19 20:40:03] ...trap/engines/engine.py.321: eval: epoch 10 | batch 0/1578 [I 2022-10-19 20:40:03] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 3:58:11 [I 2022-10-19 20:40:03] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.011038 [S 2022-10-19 21:23:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.015348 [S 2022-10-19 21:23:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.012427 [S 2022-10-19 21:23:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.013385 [S 2022-10-19 21:23:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.008402 [I 2022-10-19 21:23:56] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-19 21:23:56] ...trap/engines/engine.py.470: Saving model... [W 2022-10-19 21:23:56] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-19 21:23:56] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-19 21:23:56] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-19 21:23:59] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-19 21:24:00] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 21:24:05] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 21:24:05] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-19 21:24:05] ...trap/engines/engine.py.470: Saving model... [I 2022-10-19 21:24:08] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-19 21:24:14] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-19 21:24:14] ...trap/engines/engine.py.163: Training model on trainset for epoch 11 [I 2022-10-19 21:24:14] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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train: epoch 11 | batch 7425/7425 [I 2022-10-20 00:55:18] ...trap/engines/engine.py.228: elapsed: 3:31:03 | left: 0:00:00 [I 2022-10-20 00:55:18] ...trap/engines/engine.py.229: process: 1.14916 | load: 0.35953 [I 2022-10-20 00:55:18] ...trap/engines/engine.py.230: loss: 0.43443 [I 2022-10-20 00:55:18] ...optimizers/trijoint.py.151: total_norm: 18.088869 [S 2022-10-20 00:55:20] ...trap/engines/engine.py.129: train_epoch.epoch: 11 [S 2022-10-20 00:55:20] ...trap/engines/engine.py.129: train_epoch.loss: 0.4163599777560397 [I 2022-10-20 00:55:20] ...iterions/vlp_triplet.py.80: margin = 0.10500000000000002 [I 2022-10-20 00:55:21] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 11 [I 2022-10-20 00:55:21] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.008663 [S 2022-10-20 01:38:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.010084 [S 2022-10-20 01:38:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.006466 [S 2022-10-20 01:38:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.013118 [S 2022-10-20 01:38:19] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.011771 [I 2022-10-20 01:38:40] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-20 01:38:40] ...trap/engines/engine.py.470: Saving model... [W 2022-10-20 01:38:40] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-20 01:38:40] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-20 01:38:40] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-20 01:38:43] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-20 01:38:43] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-20 01:38:49] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-20 01:38:49] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-20 01:38:49] ...trap/engines/engine.py.470: Saving model... [I 2022-10-20 01:38:52] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-20 01:38:58] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-20 01:38:58] ...trap/engines/engine.py.163: Training model on trainset for epoch 12 [I 2022-10-20 01:38:58] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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image_from: database [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: import: recipe1m.datasets.factory [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: kw_path: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_ingr_kw.json [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_ingr_kw.json [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_ingr_kw.json [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: name: recipe1m_13m [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: nb_classes: 1048 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: nb_threads: 4 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: orig_ids_eval: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: path_ids: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/original_ids.json [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: engine: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-20 12:40:16] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-20 12:40:17] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a103', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-20 12:40:17] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-20 12:40:17] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-20 12:40:17] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-20 12:42:05] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-20 12:42:18] ...tasets/recipe1m_13m.py.293: randkw_p... 0.3 [I 2022-10-20 12:44:00] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-20 12:44:01] ...tasets/recipe1m_13m.py.293: randkw_p... None [I 2022-10-20 12:44:01] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-20 12:44:01] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-20 12:44:01] ...strap/models/factory.py.21: Creating model... [I 2022-10-20 12:44:04] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-20 12:44:07] ...e_networks/networks.py.145: cuda [I 2022-10-20 12:44:09] ...networks/tfood_vicha.py.49: Load VCs encoder... [I 2022-10-20 12:44:10] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-20 12:44:10] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-20 12:44:10] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-20 12:44:10] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-20 12:44:14] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-20 12:44:14] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-20 12:44:14] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-20 12:44:15] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-20 12:44:15] ...trap/engines/engine.py.440: Loading model... [I 2022-10-20 12:44:20] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-20 12:44:25] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-20 12:44:25] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-20 12:44:25] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-20 12:44:25] ...trap/engines/engine.py.163: Training model on trainset for epoch 12 [I 2022-10-20 12:44:25] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [I 2022-10-20 12:44:40] ...trap/engines/engine.py.224: train: epoch 12 | batch 0/7425 [I 2022-10-20 12:44:40] ...trap/engines/engine.py.228: elapsed: 0:00:15 | left: 1 day, 7:34:51 [I 2022-10-20 12:44:40] ...trap/engines/engine.py.229: process: 15.31194 | load: 10.81337 [I 2022-10-20 12:44:40] ...trap/engines/engine.py.230: loss: 0.33306 [I 2022-10-20 12:44:40] ...optimizers/trijoint.py.151: total_norm: 17.966921 [I 2022-10-20 12:44:55] ...trap/engines/engine.py.224: train: epoch 12 | batch 10/7425 [I 2022-10-20 12:44:55] ...trap/engines/engine.py.228: elapsed: 0:00:29 | left: 6:16:44 [I 2022-10-20 12:44:55] ...trap/engines/engine.py.229: process: 0.75706 | load: 0.00015 [I 2022-10-20 12:44:55] ...trap/engines/engine.py.230: loss: 0.42299 [I 2022-10-20 12:44:55] ...optimizers/trijoint.py.151: total_norm: 17.196692 [I 2022-10-20 12:45:16] ...trap/engines/engine.py.224: train: epoch 12 | batch 20/7425 [I 2022-10-20 12:45:16] ...trap/engines/engine.py.228: elapsed: 0:00:51 | left: 4:43:17 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[W 2022-10-20 15:51:46] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-20 15:51:46] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-20 15:51:46] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-20 15:51:49] ...trap/engines/engine.py.321: eval: epoch 12 | batch 0/1578 [I 2022-10-20 15:51:49] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:03:59 [I 2022-10-20 15:51:49] ...trap/engines/engine.py.326: process: 9.27726 | load: 8.20359 [I 2022-10-20 15:51:53] ...tstrap/views/plotly.py.125: Plotly view generated in 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...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_mean: 2.10 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_mean: 0.418800 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.712200 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.806800 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.389400 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.699800 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.798200 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.000000 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.300000 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_std: 0.017417 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.016893 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.012576 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.016693 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.014211 [S 2022-10-20 16:28:42] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.012568 [I 2022-10-20 16:29:02] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-20 16:29:02] ...trap/engines/engine.py.470: Saving model... [W 2022-10-20 16:29:03] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-20 16:29:03] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-20 16:29:03] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-20 16:29:06] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-20 16:29:06] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-20 16:29:12] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-20 16:29:12] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-20 16:29:12] ...trap/engines/engine.py.470: Saving model... [I 2022-10-20 16:29:15] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-20 16:29:20] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-20 16:29:20] ...trap/engines/engine.py.163: Training model on trainset for epoch 13 [I 2022-10-20 16:29:20] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-20 19:34:16] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-20 19:34:16] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-20 19:34:16] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-20 19:34:18] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-20 19:34:23] ...trap/engines/engine.py.321: eval: epoch 13 | batch 0/1578 [I 2022-10-20 19:34:23] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:13:03 [I 2022-10-20 19:34:23] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.010973 [S 2022-10-20 20:12:24] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.012657 [S 2022-10-20 20:12:24] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.007930 [S 2022-10-20 20:12:24] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.010761 [S 2022-10-20 20:12:24] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.013724 [I 2022-10-20 20:12:40] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-20 20:12:40] ...trap/engines/engine.py.470: Saving model... [W 2022-10-20 20:12:40] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-20 20:12:40] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-20 20:12:40] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-20 20:12:44] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-20 20:12:44] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-20 20:12:50] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-20 20:12:50] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-20 20:12:50] ...trap/engines/engine.py.470: Saving model... [I 2022-10-20 20:12:54] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-20 20:13:00] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-20 20:13:00] ...trap/engines/engine.py.163: Training model on trainset for epoch 14 [I 2022-10-20 20:13:00] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-20 23:20:45] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-20 23:20:45] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-20 23:20:45] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-20 23:20:47] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-20 23:20:52] ...trap/engines/engine.py.321: eval: epoch 14 | batch 0/1578 [I 2022-10-20 23:20:52] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:10:52 [I 2022-10-20 23:20:52] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.013618 [S 2022-10-20 23:58:33] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.015020 [S 2022-10-20 23:58:33] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.016568 [S 2022-10-20 23:58:33] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.012730 [S 2022-10-20 23:58:33] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.015416 [I 2022-10-20 23:58:50] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-20 23:58:50] ...trap/engines/engine.py.470: Saving model... [W 2022-10-20 23:58:50] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-20 23:58:50] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-20 23:58:50] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-20 23:58:55] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-20 23:58:55] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-20 23:59:01] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-20 23:59:01] ...trap/engines/engine.py.163: Training model on trainset for epoch 15 [I 2022-10-20 23:59:01] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-21 03:05:18] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-21 03:05:19] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-21 03:05:19] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-21 03:05:21] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-21 03:05:25] ...trap/engines/engine.py.321: eval: epoch 15 | batch 0/1578 [I 2022-10-21 03:05:25] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:09:50 [I 2022-10-21 03:05:25] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.010854 [S 2022-10-21 03:43:06] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011198 [S 2022-10-21 03:43:06] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.013705 [S 2022-10-21 03:43:06] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.016618 [S 2022-10-21 03:43:06] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.014540 [I 2022-10-21 03:43:23] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-21 03:43:23] ...trap/engines/engine.py.470: Saving model... [W 2022-10-21 03:43:24] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-21 03:43:24] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-21 03:43:24] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-21 03:43:28] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-21 03:43:28] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-21 03:43:34] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-21 03:43:34] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-21 03:43:34] ...trap/engines/engine.py.470: Saving model... [I 2022-10-21 03:43:37] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-21 03:43:44] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-21 03:43:44] ...trap/engines/engine.py.163: Training model on trainset for epoch 16 [I 2022-10-21 03:43:44] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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process: 0.80133 | load: 0.00020 [I 2022-10-21 06:39:34] ...trap/engines/engine.py.230: loss: 0.44101 [I 2022-10-21 06:39:34] ...optimizers/trijoint.py.151: total_norm: 22.971252 [I 2022-10-21 06:39:51] ...trap/engines/engine.py.224: train: epoch 16 | batch 6950/7425 [I 2022-10-21 06:39:51] ...trap/engines/engine.py.228: elapsed: 2:56:07 | left: 0:12:39 [I 2022-10-21 06:39:51] ...trap/engines/engine.py.229: process: 0.85116 | load: 0.00016 [I 2022-10-21 06:39:51] ...trap/engines/engine.py.230: loss: 0.45454 [I 2022-10-21 06:39:51] ...optimizers/trijoint.py.151: total_norm: 17.361895 [I 2022-10-21 06:40:05] ...trap/engines/engine.py.224: train: epoch 16 | batch 6960/7425 [I 2022-10-21 06:40:05] ...trap/engines/engine.py.228: elapsed: 2:56:20 | left: 0:10:13 [I 2022-10-21 06:40:05] ...trap/engines/engine.py.229: process: 1.23237 | load: 0.27740 [I 2022-10-21 06:40:05] ...trap/engines/engine.py.230: loss: 0.37061 [I 2022-10-21 06:40:05] ...optimizers/trijoint.py.151: total_norm: 24.545124 [I 2022-10-21 06:40:20] ...trap/engines/engine.py.224: train: epoch 16 | batch 6970/7425 [I 2022-10-21 06:40:20] ...trap/engines/engine.py.228: elapsed: 2:56:35 | left: 0:10:22 [I 2022-10-21 06:40:20] ...trap/engines/engine.py.229: process: 0.79647 | load: 0.00009 [I 2022-10-21 06:40:20] ...trap/engines/engine.py.230: loss: 0.59017 [I 2022-10-21 06:40:20] ...optimizers/trijoint.py.151: total_norm: 19.795710 [I 2022-10-21 08:22:17] ...ytorch/bootstrap/run.py.73: Saving environment info [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: options: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: dataset: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: aux_kw_path: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_titles_kw.json [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_titles_kw.json [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_titles_kw.json [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: batch_sampler: random [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: batch_size: 96 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: database: lmdb [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: dir: /gpfsdswork/dataset/Recipe1M+/images_recipe1M+ [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: eval_split: val [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: freq_mismatch: 0.0 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: image_from: database [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: import: recipe1m.datasets.factory [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: kw_path: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_ingr_kw.json [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_ingr_kw.json [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_ingr_kw.json [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: name: recipe1m_13m [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: nb_classes: 1048 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: nb_threads: 4 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: orig_ids_eval: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: path_ids: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/original_ids.json [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: engine: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-21 08:22:24] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-21 08:22:25] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a103', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-21 08:22:26] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-21 08:22:26] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-21 08:22:26] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-21 08:24:24] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-21 08:24:36] ...tasets/recipe1m_13m.py.293: randkw_p... 0.3 [I 2022-10-21 08:26:27] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-21 08:26:28] ...tasets/recipe1m_13m.py.293: randkw_p... None [I 2022-10-21 08:26:28] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-21 08:26:28] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-21 08:26:28] ...strap/models/factory.py.21: Creating model... [I 2022-10-21 08:26:33] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-21 08:26:37] ...e_networks/networks.py.145: cuda [I 2022-10-21 08:26:38] ...networks/tfood_vicha.py.49: Load VCs encoder... [I 2022-10-21 08:26:40] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-21 08:26:40] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-21 08:26:40] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-21 08:26:40] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-21 08:26:42] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-21 08:26:42] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-21 08:26:42] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-21 08:26:47] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-21 08:26:47] ...trap/engines/engine.py.440: Loading model... [I 2022-10-21 08:26:53] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-21 08:26:58] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-21 08:26:58] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-21 08:26:58] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-21 08:26:58] ...trap/engines/engine.py.163: Training model on trainset for epoch 16 [I 2022-10-21 08:26:58] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [I 2022-10-21 08:27:12] ...trap/engines/engine.py.224: train: epoch 16 | batch 0/7425 [I 2022-10-21 08:27:12] ...trap/engines/engine.py.228: elapsed: 0:00:13 | left: 1 day, 4:48:29 [I 2022-10-21 08:27:12] ...trap/engines/engine.py.229: process: 13.96757 | load: 8.88152 [I 2022-10-21 08:27:12] ...trap/engines/engine.py.230: loss: 0.40987 [I 2022-10-21 08:27:12] ...optimizers/trijoint.py.151: total_norm: 14.975813 [I 2022-10-21 08:27:22] ...trap/engines/engine.py.224: train: epoch 16 | batch 10/7425 [I 2022-10-21 08:27:22] ...trap/engines/engine.py.228: elapsed: 0:00:24 | left: 5:02:04 [I 2022-10-21 08:27:22] ...trap/engines/engine.py.229: process: 0.90696 | load: 0.00021 [I 2022-10-21 08:27:22] ...trap/engines/engine.py.230: loss: 0.38643 [I 2022-10-21 08:27:22] ...optimizers/trijoint.py.151: total_norm: 15.663125 [I 2022-10-21 08:27:39] ...trap/engines/engine.py.224: train: epoch 16 | batch 20/7425 [I 2022-10-21 08:27:39] ...trap/engines/engine.py.228: elapsed: 0:00:40 | left: 3:45:55 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...optimizers/trijoint.py.151: total_norm: 23.547680 [I 2022-10-21 08:28:23] ...trap/engines/engine.py.224: train: epoch 16 | batch 50/7425 [I 2022-10-21 08:28:23] ...trap/engines/engine.py.228: elapsed: 0:01:24 | left: 2:41:23 [I 2022-10-21 08:28:23] ...trap/engines/engine.py.229: process: 0.79965 | load: 0.00018 [I 2022-10-21 08:28:23] ...trap/engines/engine.py.230: loss: 0.34931 [I 2022-10-21 08:28:23] ...optimizers/trijoint.py.151: total_norm: 14.852977 [I 2022-10-21 08:28:39] ...trap/engines/engine.py.224: train: epoch 16 | batch 60/7425 [I 2022-10-21 08:28:39] ...trap/engines/engine.py.228: elapsed: 0:01:41 | left: 3:13:56 [I 2022-10-21 08:28:39] ...trap/engines/engine.py.229: process: 2.29695 | load: 1.48874 [I 2022-10-21 08:28:39] ...trap/engines/engine.py.230: loss: 0.46864 [I 2022-10-21 08:28:39] ...optimizers/trijoint.py.151: total_norm: 17.681202 [I 2022-10-21 08:28:56] ...trap/engines/engine.py.224: train: epoch 16 | batch 70/7425 [I 2022-10-21 08:28:56] 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[I 2022-10-21 08:31:25] ...trap/engines/engine.py.224: train: epoch 16 | batch 170/7425 [I 2022-10-21 08:31:25] ...trap/engines/engine.py.228: elapsed: 0:04:27 | left: 2:41:55 [I 2022-10-21 08:31:25] ...trap/engines/engine.py.229: process: 0.84000 | load: 0.00018 [I 2022-10-21 08:31:25] ...trap/engines/engine.py.230: loss: 0.41312 [I 2022-10-21 08:31:25] ...optimizers/trijoint.py.151: total_norm: 22.805235 [I 2022-10-21 08:31:41] ...trap/engines/engine.py.224: train: epoch 16 | batch 180/7425 [I 2022-10-21 08:31:41] ...trap/engines/engine.py.228: elapsed: 0:04:42 | left: 2:54:15 [I 2022-10-21 08:31:41] ...trap/engines/engine.py.229: process: 0.76624 | load: 0.00008 [I 2022-10-21 08:31:41] ...trap/engines/engine.py.230: loss: 0.41871 [I 2022-10-21 08:31:41] ...optimizers/trijoint.py.151: total_norm: 18.653006 [I 2022-10-21 08:31:54] ...trap/engines/engine.py.224: train: epoch 16 | batch 190/7425 [I 2022-10-21 08:31:54] ...trap/engines/engine.py.228: elapsed: 0:04:56 | left: 2:28:22 [I 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...optimizers/trijoint.py.151: total_norm: 18.169039 [I 2022-10-21 08:32:37] ...trap/engines/engine.py.224: train: epoch 16 | batch 220/7425 [I 2022-10-21 08:32:37] ...trap/engines/engine.py.228: elapsed: 0:05:39 | left: 2:44:37 [I 2022-10-21 08:32:37] ...trap/engines/engine.py.229: process: 0.76487 | load: 0.00008 [I 2022-10-21 08:32:37] ...trap/engines/engine.py.230: loss: 0.49593 [I 2022-10-21 08:32:37] ...optimizers/trijoint.py.151: total_norm: 19.072868 [I 2022-10-21 08:32:52] ...trap/engines/engine.py.224: train: epoch 16 | batch 230/7425 [I 2022-10-21 08:32:52] ...trap/engines/engine.py.228: elapsed: 0:05:53 | left: 2:37:28 [I 2022-10-21 08:32:52] ...trap/engines/engine.py.229: process: 0.85259 | load: 0.00018 [I 2022-10-21 08:32:52] ...trap/engines/engine.py.230: loss: 0.42535 [I 2022-10-21 08:32:52] ...optimizers/trijoint.py.151: total_norm: 21.601776 [I 2022-10-21 08:33:07] ...trap/engines/engine.py.224: train: epoch 16 | batch 240/7425 [I 2022-10-21 08:33:07] 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11:32:53] ...optimizers/trijoint.py.151: total_norm: 17.581619 [I 2022-10-21 11:33:10] ...trap/engines/engine.py.224: train: epoch 16 | batch 7360/7425 [I 2022-10-21 11:33:10] ...trap/engines/engine.py.228: elapsed: 3:06:11 | left: 0:01:42 [I 2022-10-21 11:33:10] ...trap/engines/engine.py.229: process: 0.80635 | load: 0.00009 [I 2022-10-21 11:33:10] ...trap/engines/engine.py.230: loss: 0.50392 [I 2022-10-21 11:33:10] ...optimizers/trijoint.py.151: total_norm: 22.219555 [I 2022-10-21 11:33:24] ...trap/engines/engine.py.224: train: epoch 16 | batch 7370/7425 [I 2022-10-21 11:33:24] ...trap/engines/engine.py.228: elapsed: 3:06:26 | left: 0:01:15 [I 2022-10-21 11:33:24] ...trap/engines/engine.py.229: process: 0.77926 | load: 0.00022 [I 2022-10-21 11:33:24] ...trap/engines/engine.py.230: loss: 0.37249 [I 2022-10-21 11:33:24] ...optimizers/trijoint.py.151: total_norm: 18.456049 [I 2022-10-21 11:33:45] ...trap/engines/engine.py.224: train: epoch 16 | batch 7380/7425 [I 2022-10-21 11:33:45] 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[W 2022-10-21 11:35:02] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-21 11:35:02] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-21 11:35:02] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-21 11:35:04] ...trap/engines/engine.py.321: eval: epoch 16 | batch 0/1578 [I 2022-10-21 11:35:04] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 3:58:08 [I 2022-10-21 11:35:04] ...trap/engines/engine.py.326: process: 9.05454 | load: 8.19909 [I 2022-10-21 11:35:10] ...tstrap/views/plotly.py.125: Plotly view generated in 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eval_epoch.metric.recall_at_1_im2recipe_std: 0.014507 [S 2022-10-21 12:16:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.014312 [S 2022-10-21 12:16:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.012339 [S 2022-10-21 12:16:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.016462 [S 2022-10-21 12:16:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.006204 [S 2022-10-21 12:16:34] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.011522 [I 2022-10-21 12:16:58] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-21 12:16:58] ...trap/engines/engine.py.470: Saving model... [W 2022-10-21 12:16:58] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-21 12:16:58] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-21 12:16:58] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-21 12:17:02] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-21 12:17:02] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-21 12:17:08] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-21 12:17:08] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-21 12:17:08] ...trap/engines/engine.py.470: Saving model... [I 2022-10-21 12:17:11] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-21 12:17:17] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-21 12:17:17] ...trap/engines/engine.py.163: Training model on trainset for epoch 17 [I 2022-10-21 12:17:17] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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15:28:20] ...optimizers/trijoint.py.151: total_norm: 22.473209 [I 2022-10-21 15:28:36] ...trap/engines/engine.py.224: train: epoch 17 | batch 7360/7425 [I 2022-10-21 15:28:36] ...trap/engines/engine.py.228: elapsed: 3:11:18 | left: 0:01:53 [I 2022-10-21 15:28:36] ...trap/engines/engine.py.229: process: 3.68741 | load: 2.88732 [I 2022-10-21 15:28:36] ...trap/engines/engine.py.230: loss: 0.43433 [I 2022-10-21 15:28:36] ...optimizers/trijoint.py.151: total_norm: 17.256483 [I 2022-10-21 15:28:49] ...trap/engines/engine.py.224: train: epoch 17 | batch 7370/7425 [I 2022-10-21 15:28:49] ...trap/engines/engine.py.228: elapsed: 3:11:31 | left: 0:01:11 [I 2022-10-21 15:28:49] ...trap/engines/engine.py.229: process: 0.76971 | load: 0.00014 [I 2022-10-21 15:28:49] ...trap/engines/engine.py.230: loss: 0.40526 [I 2022-10-21 15:28:49] ...optimizers/trijoint.py.151: total_norm: 18.672308 [I 2022-10-21 15:29:06] ...trap/engines/engine.py.224: train: epoch 17 | batch 7380/7425 [I 2022-10-21 15:29:06] 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train: epoch 17 | batch 7425/7425 [I 2022-10-21 15:30:13] ...trap/engines/engine.py.228: elapsed: 3:12:55 | left: 0:00:00 [I 2022-10-21 15:30:13] ...trap/engines/engine.py.229: process: 0.74123 | load: 0.00002 [I 2022-10-21 15:30:13] ...trap/engines/engine.py.230: loss: 0.39190 [I 2022-10-21 15:30:13] ...optimizers/trijoint.py.151: total_norm: 18.919786 [S 2022-10-21 15:30:15] ...trap/engines/engine.py.129: train_epoch.epoch: 17 [S 2022-10-21 15:30:15] ...trap/engines/engine.py.129: train_epoch.loss: 0.4077114611723627 [I 2022-10-21 15:30:15] ...iterions/vlp_triplet.py.80: margin = 0.135 [I 2022-10-21 15:30:16] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 17 [I 2022-10-21 15:30:16] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [W 2022-10-21 15:30:19] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-21 15:30:19] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-21 15:30:19] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-21 15:30:21] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-21 15:30:26] ...trap/engines/engine.py.321: eval: epoch 17 | batch 0/1578 [I 2022-10-21 15:30:26] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:15:04 [I 2022-10-21 15:30:26] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.008695 [S 2022-10-21 16:08:28] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.012763 [S 2022-10-21 16:08:28] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.011189 [S 2022-10-21 16:08:28] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.007483 [S 2022-10-21 16:08:28] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.010989 [I 2022-10-21 16:08:47] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-21 16:08:47] ...trap/engines/engine.py.470: Saving model... [W 2022-10-21 16:08:47] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-21 16:08:47] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-21 16:08:47] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-21 16:08:51] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-21 16:08:52] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-21 16:08:57] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-21 16:08:57] ...trap/engines/engine.py.163: Training model on trainset for epoch 18 [I 2022-10-21 16:08:57] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-21 19:23:01] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-21 19:23:01] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-21 19:23:01] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-21 19:23:03] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-21 19:23:07] ...trap/engines/engine.py.321: eval: epoch 18 | batch 0/1578 [I 2022-10-21 19:23:07] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:54:30 [I 2022-10-21 19:23:07] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.010973 [S 2022-10-21 20:02:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011289 [S 2022-10-21 20:02:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.020241 [S 2022-10-21 20:02:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.017130 [S 2022-10-21 20:02:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.009174 [I 2022-10-21 20:02:53] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-21 20:02:53] ...trap/engines/engine.py.470: Saving model... [W 2022-10-21 20:02:53] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-21 20:02:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-21 20:02:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-21 20:02:57] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-21 20:02:58] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-21 20:03:03] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-21 20:03:03] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-21 20:03:03] ...trap/engines/engine.py.470: Saving model... [I 2022-10-21 20:03:06] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-21 20:03:12] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-21 20:03:12] ...trap/engines/engine.py.163: Training model on trainset for epoch 19 [I 2022-10-21 20:03:12] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-21 23:16:14] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-21 23:16:14] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-21 23:16:14] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-21 23:16:16] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-21 23:16:21] ...trap/engines/engine.py.321: eval: epoch 19 | batch 0/1578 [I 2022-10-21 23:16:21] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:55:40 [I 2022-10-21 23:16:21] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.010477 [S 2022-10-21 23:55:06] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.008015 [S 2022-10-21 23:55:06] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.011187 [S 2022-10-21 23:55:06] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.011031 [S 2022-10-21 23:55:06] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.011280 [I 2022-10-21 23:55:21] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-21 23:55:21] ...trap/engines/engine.py.470: Saving model... [W 2022-10-21 23:55:22] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-21 23:55:22] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-21 23:55:22] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-21 23:55:26] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-21 23:55:27] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-21 23:55:32] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-21 23:55:32] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-21 23:55:32] ...trap/engines/engine.py.470: Saving model... [I 2022-10-21 23:55:35] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-21 23:55:40] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-21 23:55:40] ...trap/engines/engine.py.163: Training model on trainset for epoch 20 [I 2022-10-21 23:55:40] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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...ytorch/bootstrap/run.py.75: nb_classes: 1048 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: nb_threads: 4 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: orig_ids_eval: True [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: path_ids: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/original_ids.json [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: engine: [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-22 08:27:02] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-22 08:27:03] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-22 08:27:04] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a103', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-22 08:27:04] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-22 08:27:04] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-22 08:27:04] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-22 08:28:56] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-22 08:29:09] ...tasets/recipe1m_13m.py.293: randkw_p... 0.3 [I 2022-10-22 08:30:51] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-22 08:30:52] ...tasets/recipe1m_13m.py.293: randkw_p... None [I 2022-10-22 08:30:52] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-22 08:30:52] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-22 08:30:52] ...strap/models/factory.py.21: Creating model... [I 2022-10-22 08:30:57] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-22 08:31:00] ...e_networks/networks.py.145: cuda [I 2022-10-22 08:31:01] ...networks/tfood_vicha.py.49: Load VCs encoder... [I 2022-10-22 08:31:03] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-22 08:31:03] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-22 08:31:03] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-22 08:31:03] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-22 08:31:05] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-22 08:31:05] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-22 08:31:05] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-22 08:31:09] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-22 08:31:09] ...trap/engines/engine.py.440: Loading model... [I 2022-10-22 08:31:15] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-22 08:31:20] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-22 08:31:20] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-22 08:31:20] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-22 08:31:20] ...trap/engines/engine.py.163: Training model on trainset for epoch 20 [I 2022-10-22 08:31:20] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-22 11:36:48] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-22 11:36:48] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-22 11:36:48] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-22 11:36:52] ...trap/engines/engine.py.321: eval: epoch 20 | batch 0/1578 [I 2022-10-22 11:36:52] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:02:29 [I 2022-10-22 11:36:52] ...trap/engines/engine.py.326: process: 9.22030 | load: 8.39680 [I 2022-10-22 11:36:56] ...tstrap/views/plotly.py.125: Plotly view generated in 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...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_mean: 2.00 [S 2022-10-22 12:14:03] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_mean: 0.443300 [S 2022-10-22 12:14:03] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.739200 [S 2022-10-22 12:14:03] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.831300 [S 2022-10-22 12:14:03] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.417300 [S 2022-10-22 12:14:03] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.725400 [S 2022-10-22 12:14:03] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.819700 [S 2022-10-22 12:14:03] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.000000 [S 2022-10-22 12:14:03] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.000000 [S 2022-10-22 12:14:03] ...strap/engines/engine.py.72: 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[W 2022-10-22 12:14:19] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-22 12:14:19] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-22 12:14:19] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-22 12:14:23] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-22 12:14:24] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-22 12:14:29] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-22 12:14:29] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-22 12:14:29] ...trap/engines/engine.py.470: Saving model... [I 2022-10-22 12:14:32] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-22 12:14:37] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-22 12:14:37] ...trap/engines/engine.py.163: Training model on trainset for epoch 21 [I 2022-10-22 12:14:37] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-22 15:20:15] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-22 15:20:15] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-22 15:20:15] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-22 15:20:18] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-22 15:20:21] ...trap/engines/engine.py.321: eval: epoch 21 | batch 0/1578 [I 2022-10-22 15:20:21] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:52:46 [I 2022-10-22 15:20:21] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.010375 [S 2022-10-22 15:57:36] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.010445 [S 2022-10-22 15:57:36] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.016474 [S 2022-10-22 15:57:36] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.014625 [S 2022-10-22 15:57:36] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.011454 [I 2022-10-22 15:57:50] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-22 15:57:50] ...trap/engines/engine.py.470: Saving model... [W 2022-10-22 15:57:51] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-22 15:57:51] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-22 15:57:51] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-22 15:57:55] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-22 15:57:56] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-22 15:58:01] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-22 15:58:01] ...trap/engines/engine.py.163: Training model on trainset for epoch 22 [I 2022-10-22 15:58:01] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-22 19:06:00] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-22 19:06:00] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-22 19:06:00] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-22 19:06:03] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-22 19:06:05] ...trap/engines/engine.py.321: eval: epoch 22 | batch 0/1578 [I 2022-10-22 19:06:05] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:33:49 [I 2022-10-22 19:06:05] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.014845 [S 2022-10-22 19:44:46] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.013023 [S 2022-10-22 19:44:46] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.010982 [S 2022-10-22 19:44:46] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.016577 [S 2022-10-22 19:44:46] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.011982 [I 2022-10-22 19:45:01] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-22 19:45:01] ...trap/engines/engine.py.470: Saving model... [W 2022-10-22 19:45:01] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-22 19:45:01] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-22 19:45:01] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-22 19:45:05] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-22 19:45:07] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-22 19:45:11] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-22 19:45:11] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-22 19:45:11] ...trap/engines/engine.py.470: Saving model... [I 2022-10-22 19:45:14] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-22 19:45:20] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-22 19:45:20] ...trap/engines/engine.py.163: Training model on trainset for epoch 23 [I 2022-10-22 19:45:20] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-22 23:06:54] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-22 23:06:54] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-22 23:06:54] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-22 23:06:57] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-22 23:07:01] ...trap/engines/engine.py.321: eval: epoch 23 | batch 0/1578 [I 2022-10-22 23:07:01] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:10:44 [I 2022-10-22 23:07:01] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.010147 [S 2022-10-22 23:48:38] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.012758 [S 2022-10-22 23:48:38] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.018496 [S 2022-10-22 23:48:38] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.012516 [S 2022-10-22 23:48:38] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.011209 [I 2022-10-22 23:48:53] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-22 23:48:53] ...trap/engines/engine.py.470: Saving model... [W 2022-10-22 23:48:54] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-22 23:48:54] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-22 23:48:54] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-22 23:48:58] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-22 23:49:00] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-22 23:49:04] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-22 23:49:04] ...trap/engines/engine.py.163: Training model on trainset for epoch 24 [I 2022-10-22 23:49:04] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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...trap/engines/engine.py.230: loss: 0.34334 [I 2022-10-23 02:26:39] ...optimizers/trijoint.py.151: total_norm: 17.203695 [I 2022-10-23 02:26:54] ...trap/engines/engine.py.224: train: epoch 24 | batch 5710/7425 [I 2022-10-23 02:26:54] ...trap/engines/engine.py.228: elapsed: 2:37:50 | left: 0:39:49 [I 2022-10-23 02:26:54] ...trap/engines/engine.py.229: process: 0.82509 | load: 0.00008 [I 2022-10-23 02:26:54] ...trap/engines/engine.py.230: loss: 0.32390 [I 2022-10-23 02:26:54] ...optimizers/trijoint.py.151: total_norm: 14.905617 [I 2022-10-23 09:02:10] ...ytorch/bootstrap/run.py.73: Saving environment info [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: options: [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: dataset: [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: aux_kw_path: [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_titles_kw.json [S 2022-10-23 09:02:17] 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...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: engine: [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: seed: 1338 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09:02:17] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-23 09:02:17] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-23 09:02:18] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-23 09:02:19] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a101', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-23 09:02:19] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-23 09:02:19] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-23 09:02:19] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-23 09:04:14] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-23 09:04:28] ...tasets/recipe1m_13m.py.293: randkw_p... 0.3 [I 2022-10-23 09:06:12] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-23 09:06:13] ...tasets/recipe1m_13m.py.293: randkw_p... None [I 2022-10-23 09:06:13] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-23 09:06:13] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-23 09:06:13] ...strap/models/factory.py.21: Creating model... [I 2022-10-23 09:06:18] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-23 09:06:21] ...e_networks/networks.py.145: cuda [I 2022-10-23 09:06:23] ...networks/tfood_vicha.py.49: Load VCs encoder... [I 2022-10-23 09:06:24] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-23 09:06:24] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-23 09:06:24] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-23 09:06:24] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-23 09:06:31] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-23 09:06:31] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-23 09:06:31] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-23 09:06:36] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-23 09:06:36] ...trap/engines/engine.py.440: Loading model... [I 2022-10-23 09:06:40] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-23 09:06:46] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-23 09:06:46] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-23 09:06:46] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-23 09:06:46] ...trap/engines/engine.py.163: Training model on trainset for epoch 24 [I 2022-10-23 09:06:46] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [I 2022-10-23 09:06:59] ...trap/engines/engine.py.224: train: epoch 24 | batch 0/7425 [I 2022-10-23 09:06:59] ...trap/engines/engine.py.228: elapsed: 0:00:13 | left: 1 day, 2:54:48 [I 2022-10-23 09:06:59] ...trap/engines/engine.py.229: process: 13.04897 | load: 7.69504 [I 2022-10-23 09:06:59] ...trap/engines/engine.py.230: loss: 0.42011 [I 2022-10-23 09:06:59] ...optimizers/trijoint.py.151: total_norm: 17.830709 [I 2022-10-23 09:07:11] ...trap/engines/engine.py.224: train: epoch 24 | batch 10/7425 [I 2022-10-23 09:07:11] ...trap/engines/engine.py.228: elapsed: 0:00:25 | left: 5:19:22 [I 2022-10-23 09:07:11] ...trap/engines/engine.py.229: process: 0.80272 | load: 0.00014 [I 2022-10-23 09:07:11] ...trap/engines/engine.py.230: loss: 0.34964 [I 2022-10-23 09:07:11] ...optimizers/trijoint.py.151: total_norm: 16.818413 [I 2022-10-23 09:07:30] ...trap/engines/engine.py.224: train: epoch 24 | batch 20/7425 [I 2022-10-23 09:07:30] ...trap/engines/engine.py.228: elapsed: 0:00:44 | left: 4:22:23 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...optimizers/trijoint.py.151: total_norm: 17.873598 [I 2022-10-23 09:08:18] ...trap/engines/engine.py.224: train: epoch 24 | batch 50/7425 [I 2022-10-23 09:08:18] ...trap/engines/engine.py.228: elapsed: 0:01:32 | left: 3:21:33 [I 2022-10-23 09:08:18] ...trap/engines/engine.py.229: process: 0.79028 | load: 0.00013 [I 2022-10-23 09:08:18] ...trap/engines/engine.py.230: loss: 0.41072 [I 2022-10-23 09:08:18] ...optimizers/trijoint.py.151: total_norm: 20.345268 [I 2022-10-23 09:08:35] ...trap/engines/engine.py.224: train: epoch 24 | batch 60/7425 [I 2022-10-23 09:08:35] ...trap/engines/engine.py.228: elapsed: 0:01:49 | left: 3:46:46 [I 2022-10-23 09:08:35] ...trap/engines/engine.py.229: process: 3.86328 | load: 3.04102 [I 2022-10-23 09:08:35] ...trap/engines/engine.py.230: loss: 0.31451 [I 2022-10-23 09:08:35] ...optimizers/trijoint.py.151: total_norm: 16.169968 [I 2022-10-23 09:08:48] ...trap/engines/engine.py.224: train: epoch 24 | batch 70/7425 [I 2022-10-23 09:08:48] ...trap/engines/engine.py.228: elapsed: 0:02:02 | left: 2:54:19 [I 2022-10-23 09:08:48] ...trap/engines/engine.py.229: process: 0.79193 | load: 0.00014 [I 2022-10-23 09:08:48] ...trap/engines/engine.py.230: loss: 0.37363 [I 2022-10-23 09:08:48] ...optimizers/trijoint.py.151: total_norm: 16.932344 [I 2022-10-23 09:09:05] ...trap/engines/engine.py.224: train: epoch 24 | batch 80/7425 [I 2022-10-23 09:09:05] ...trap/engines/engine.py.228: elapsed: 0:02:19 | left: 3:44:21 [I 2022-10-23 09:09:05] ...trap/engines/engine.py.229: process: 3.86127 | load: 3.04223 [I 2022-10-23 09:09:05] ...trap/engines/engine.py.230: loss: 0.28935 [I 2022-10-23 09:09:05] ...optimizers/trijoint.py.151: total_norm: 12.063917 [I 2022-10-23 09:09:19] ...trap/engines/engine.py.224: train: epoch 24 | batch 90/7425 [I 2022-10-23 09:09:19] ...trap/engines/engine.py.228: elapsed: 0:02:33 | left: 2:52:05 [I 2022-10-23 09:09:19] ...trap/engines/engine.py.229: process: 0.79280 | load: 0.00014 [I 2022-10-23 09:09:19] ...trap/engines/engine.py.230: loss: 0.39910 [I 2022-10-23 09:09:19] ...optimizers/trijoint.py.151: total_norm: 18.650644 [I 2022-10-23 09:09:37] ...trap/engines/engine.py.224: train: epoch 24 | batch 100/7425 [I 2022-10-23 09:09:37] ...trap/engines/engine.py.228: elapsed: 0:02:51 | left: 3:39:51 [I 2022-10-23 09:09:37] ...trap/engines/engine.py.229: process: 3.61773 | load: 2.80136 [I 2022-10-23 09:09:37] ...trap/engines/engine.py.230: loss: 0.37633 [I 2022-10-23 09:09:37] ...optimizers/trijoint.py.151: total_norm: 20.748396 [I 2022-10-23 09:09:50] ...trap/engines/engine.py.224: train: epoch 24 | batch 110/7425 [I 2022-10-23 09:09:50] ...trap/engines/engine.py.228: elapsed: 0:03:04 | left: 2:43:40 [I 2022-10-23 09:09:50] ...trap/engines/engine.py.229: process: 0.80018 | load: 0.00014 [I 2022-10-23 09:09:50] ...trap/engines/engine.py.230: loss: 0.33814 [I 2022-10-23 09:09:50] ...optimizers/trijoint.py.151: total_norm: 17.177622 [I 2022-10-23 09:10:07] ...trap/engines/engine.py.224: 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[I 2022-10-23 09:11:25] ...trap/engines/engine.py.224: train: epoch 24 | batch 170/7425 [I 2022-10-23 09:11:25] ...trap/engines/engine.py.228: elapsed: 0:04:39 | left: 3:14:21 [I 2022-10-23 09:11:25] ...trap/engines/engine.py.229: process: 0.78728 | load: 0.00015 [I 2022-10-23 09:11:25] ...trap/engines/engine.py.230: loss: 0.33300 [I 2022-10-23 09:11:25] ...optimizers/trijoint.py.151: total_norm: 23.850309 [I 2022-10-23 09:11:41] ...trap/engines/engine.py.224: train: epoch 24 | batch 180/7425 [I 2022-10-23 09:11:41] ...trap/engines/engine.py.228: elapsed: 0:04:55 | left: 3:25:57 [I 2022-10-23 09:11:41] ...trap/engines/engine.py.229: process: 3.43630 | load: 2.59768 [I 2022-10-23 09:11:41] ...trap/engines/engine.py.230: loss: 0.43175 [I 2022-10-23 09:11:41] ...optimizers/trijoint.py.151: total_norm: 17.140299 [I 2022-10-23 09:11:55] ...trap/engines/engine.py.224: train: epoch 24 | batch 190/7425 [I 2022-10-23 09:11:55] ...trap/engines/engine.py.228: elapsed: 0:05:09 | left: 2:43:07 [I 2022-10-23 09:11:55] ...trap/engines/engine.py.229: process: 0.79698 | load: 0.00008 [I 2022-10-23 09:11:55] ...trap/engines/engine.py.230: loss: 0.40939 [I 2022-10-23 09:11:55] ...optimizers/trijoint.py.151: total_norm: 19.484692 [I 2022-10-23 09:12:12] ...trap/engines/engine.py.224: train: epoch 24 | batch 200/7425 [I 2022-10-23 09:12:12] ...trap/engines/engine.py.228: elapsed: 0:05:26 | left: 3:37:03 [I 2022-10-23 09:12:12] ...trap/engines/engine.py.229: process: 2.34274 | load: 1.54475 [I 2022-10-23 09:12:12] ...trap/engines/engine.py.230: loss: 0.28078 [I 2022-10-23 09:12:12] ...optimizers/trijoint.py.151: total_norm: 12.770876 [I 2022-10-23 09:12:27] ...trap/engines/engine.py.224: train: epoch 24 | batch 210/7425 [I 2022-10-23 09:12:27] ...trap/engines/engine.py.228: elapsed: 0:05:41 | left: 3:00:53 [I 2022-10-23 09:12:27] ...trap/engines/engine.py.229: process: 0.79744 | load: 0.00007 [I 2022-10-23 09:12:27] ...trap/engines/engine.py.230: loss: 0.38276 [I 2022-10-23 09:12:27] ...optimizers/trijoint.py.151: total_norm: 18.563585 [I 2022-10-23 09:12:47] ...trap/engines/engine.py.224: train: epoch 24 | batch 220/7425 [I 2022-10-23 09:12:47] ...trap/engines/engine.py.228: elapsed: 0:06:01 | left: 4:02:21 [I 2022-10-23 09:12:47] ...trap/engines/engine.py.229: process: 3.62749 | load: 2.79970 [I 2022-10-23 09:12:47] ...trap/engines/engine.py.230: loss: 0.32286 [I 2022-10-23 09:12:47] ...optimizers/trijoint.py.151: total_norm: 12.384936 [I 2022-10-23 09:13:02] ...trap/engines/engine.py.224: train: epoch 24 | batch 230/7425 [I 2022-10-23 09:13:02] ...trap/engines/engine.py.228: elapsed: 0:06:16 | left: 3:03:24 [I 2022-10-23 09:13:02] ...trap/engines/engine.py.229: process: 0.80144 | load: 0.00014 [I 2022-10-23 09:13:02] ...trap/engines/engine.py.230: loss: 0.44988 [I 2022-10-23 09:13:02] ...optimizers/trijoint.py.151: total_norm: 16.590387 [I 2022-10-23 09:13:20] ...trap/engines/engine.py.224: train: epoch 24 | batch 240/7425 [I 2022-10-23 09:13:20] 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[I 2022-10-23 12:15:16] ...trap/engines/engine.py.224: train: epoch 24 | batch 7310/7425 [I 2022-10-23 12:15:16] ...trap/engines/engine.py.228: elapsed: 3:08:30 | left: 0:03:19 [I 2022-10-23 12:15:16] ...trap/engines/engine.py.229: process: 3.23588 | load: 2.42272 [I 2022-10-23 12:15:16] ...trap/engines/engine.py.230: loss: 0.28437 [I 2022-10-23 12:15:16] ...optimizers/trijoint.py.151: total_norm: 18.194197 [I 2022-10-23 12:15:30] ...trap/engines/engine.py.224: train: epoch 24 | batch 7320/7425 [I 2022-10-23 12:15:30] ...trap/engines/engine.py.228: elapsed: 3:08:44 | left: 0:02:57 [I 2022-10-23 12:15:30] ...trap/engines/engine.py.229: process: 2.93687 | load: 2.10714 [I 2022-10-23 12:15:30] ...trap/engines/engine.py.230: loss: 0.33269 [I 2022-10-23 12:15:30] ...optimizers/trijoint.py.151: total_norm: 21.301842 [I 2022-10-23 12:15:43] ...trap/engines/engine.py.224: train: epoch 24 | batch 7330/7425 [I 2022-10-23 12:15:43] ...trap/engines/engine.py.228: elapsed: 3:08:57 | left: 0:02:02 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12:16:13] ...optimizers/trijoint.py.151: total_norm: 19.324314 [I 2022-10-23 12:16:28] ...trap/engines/engine.py.224: train: epoch 24 | batch 7360/7425 [I 2022-10-23 12:16:28] ...trap/engines/engine.py.228: elapsed: 3:09:42 | left: 0:01:50 [I 2022-10-23 12:16:28] ...trap/engines/engine.py.229: process: 3.37231 | load: 2.56589 [I 2022-10-23 12:16:28] ...trap/engines/engine.py.230: loss: 0.39208 [I 2022-10-23 12:16:28] ...optimizers/trijoint.py.151: total_norm: 19.802034 [I 2022-10-23 12:16:42] ...trap/engines/engine.py.224: train: epoch 24 | batch 7370/7425 [I 2022-10-23 12:16:42] ...trap/engines/engine.py.228: elapsed: 3:09:56 | left: 0:01:11 [I 2022-10-23 12:16:42] ...trap/engines/engine.py.229: process: 0.79524 | load: 0.00008 [I 2022-10-23 12:16:42] ...trap/engines/engine.py.230: loss: 0.43336 [I 2022-10-23 12:16:42] ...optimizers/trijoint.py.151: total_norm: 21.604450 [I 2022-10-23 12:16:59] ...trap/engines/engine.py.224: train: epoch 24 | batch 7380/7425 [I 2022-10-23 12:16:59] 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train: epoch 24 | batch 7425/7425 [I 2022-10-23 12:18:02] ...trap/engines/engine.py.228: elapsed: 3:11:16 | left: 0:00:00 [I 2022-10-23 12:18:02] ...trap/engines/engine.py.229: process: 0.79298 | load: 0.00002 [I 2022-10-23 12:18:02] ...trap/engines/engine.py.230: loss: 0.42093 [I 2022-10-23 12:18:02] ...optimizers/trijoint.py.151: total_norm: 17.322760 [S 2022-10-23 12:18:04] ...trap/engines/engine.py.129: train_epoch.epoch: 24 [S 2022-10-23 12:18:04] ...trap/engines/engine.py.129: train_epoch.loss: 0.37421166619705826 [I 2022-10-23 12:18:04] ...iterions/vlp_triplet.py.80: margin = 0.17 [I 2022-10-23 12:18:05] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 24 [I 2022-10-23 12:18:05] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [W 2022-10-23 12:18:10] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-23 12:18:10] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-23 12:18:10] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-23 12:18:13] ...trap/engines/engine.py.321: eval: epoch 24 | batch 0/1578 [I 2022-10-23 12:18:13] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:44:07 [I 2022-10-23 12:18:13] ...trap/engines/engine.py.326: process: 8.52182 | load: 7.03472 [I 2022-10-23 12:18:18] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-23 12:18:26] ...trap/engines/engine.py.321: eval: epoch 24 | batch 10/1578 [I 2022-10-23 12:18:26] ...trap/engines/engine.py.325: elapsed: 0:00:21 | left: 0:54:45 [I 2022-10-23 12:18:26] ...trap/engines/engine.py.326: process: 0.39813 | load: 0.00007 [I 2022-10-23 12:18:42] ...trap/engines/engine.py.321: eval: epoch 24 | batch 20/1578 [I 2022-10-23 12:18:42] ...trap/engines/engine.py.325: elapsed: 0:00:37 | left: 0:48:00 [I 2022-10-23 12:18:42] ...trap/engines/engine.py.326: process: 4.48653 | load: 4.02608 [I 2022-10-23 12:18:55] ...trap/engines/engine.py.321: eval: epoch 24 | batch 30/1578 [I 2022-10-23 12:18:55] ...trap/engines/engine.py.325: elapsed: 0:00:50 | left: 0:34:17 [I 2022-10-23 12:18:55] ...trap/engines/engine.py.326: process: 0.38644 | load: 0.00007 [I 2022-10-23 12:19:11] ...trap/engines/engine.py.321: eval: epoch 24 | batch 40/1578 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eval_epoch.metric.recall_at_1_im2recipe_std: 0.015492 [S 2022-10-23 12:57:14] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.016487 [S 2022-10-23 12:57:14] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.014921 [S 2022-10-23 12:57:14] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.015055 [S 2022-10-23 12:57:14] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.018819 [S 2022-10-23 12:57:14] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.014804 [I 2022-10-23 12:57:30] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-23 12:57:30] ...trap/engines/engine.py.470: Saving model... [W 2022-10-23 12:57:30] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-23 12:57:30] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-23 12:57:30] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-23 12:57:34] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-23 12:57:36] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-23 12:57:40] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-23 12:57:40] ...trap/engines/engine.py.163: Training model on trainset for epoch 25 [I 2022-10-23 12:57:40] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-23 16:15:57] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-23 16:15:57] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-23 16:15:57] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-23 16:16:00] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-23 16:16:04] ...trap/engines/engine.py.321: eval: epoch 25 | batch 0/1578 [I 2022-10-23 16:16:04] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:00:56 [I 2022-10-23 16:16:04] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.017940 [S 2022-10-23 16:56:59] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011534 [S 2022-10-23 16:56:59] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.015641 [S 2022-10-23 16:56:59] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.012697 [S 2022-10-23 16:56:59] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.011595 [I 2022-10-23 16:57:15] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-23 16:57:15] ...trap/engines/engine.py.470: Saving model... [W 2022-10-23 16:57:16] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-23 16:57:16] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-23 16:57:16] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-23 16:57:20] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-23 16:57:23] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-23 16:57:27] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-23 16:57:27] ...trap/engines/engine.py.163: Training model on trainset for epoch 26 [I 2022-10-23 16:57:27] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-23 20:12:23] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-23 20:12:23] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-23 20:12:23] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-23 20:12:26] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-23 20:12:29] ...trap/engines/engine.py.321: eval: epoch 26 | batch 0/1578 [I 2022-10-23 20:12:29] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:47:58 [I 2022-10-23 20:12:29] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.017877 [S 2022-10-23 20:51:49] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.013268 [S 2022-10-23 20:51:49] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.011391 [S 2022-10-23 20:51:49] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.011029 [S 2022-10-23 20:51:49] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.014521 [I 2022-10-23 20:52:05] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-23 20:52:05] ...trap/engines/engine.py.470: Saving model... [W 2022-10-23 20:52:05] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-23 20:52:05] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-23 20:52:05] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-23 20:52:09] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-23 20:52:12] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-23 20:52:16] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-23 20:52:16] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-23 20:52:16] ...trap/engines/engine.py.470: Saving model... [I 2022-10-23 20:52:19] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-23 20:52:24] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-23 20:52:24] ...trap/engines/engine.py.163: Training model on trainset for epoch 27 [I 2022-10-23 20:52:24] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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train: epoch 27 | batch 7425/7425 [I 2022-10-24 00:09:02] ...trap/engines/engine.py.228: elapsed: 3:16:38 | left: 0:00:00 [I 2022-10-24 00:09:02] ...trap/engines/engine.py.229: process: 0.80208 | load: 0.00016 [I 2022-10-24 00:09:02] ...trap/engines/engine.py.230: loss: 0.36818 [I 2022-10-24 00:09:02] ...optimizers/trijoint.py.151: total_norm: 21.345680 [S 2022-10-24 00:09:04] ...trap/engines/engine.py.129: train_epoch.epoch: 27 [S 2022-10-24 00:09:04] ...trap/engines/engine.py.129: train_epoch.loss: 0.3692904338501484 [I 2022-10-24 00:09:04] ...iterions/vlp_triplet.py.80: margin = 0.18500000000000003 [I 2022-10-24 00:09:06] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 27 [I 2022-10-24 00:09:06] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [W 2022-10-24 00:09:08] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-24 00:09:08] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-24 00:09:08] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-24 00:09:12] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-24 00:09:15] ...trap/engines/engine.py.321: eval: epoch 27 | batch 0/1578 [I 2022-10-24 00:09:15] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:10:22 [I 2022-10-24 00:09:15] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.011243 [S 2022-10-24 00:49:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.010724 [S 2022-10-24 00:49:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.018805 [S 2022-10-24 00:49:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.009561 [S 2022-10-24 00:49:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.008149 [I 2022-10-24 00:50:11] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-24 00:50:11] ...trap/engines/engine.py.470: Saving model... [W 2022-10-24 00:50:12] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-24 00:50:12] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-24 00:50:12] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-24 00:50:16] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-24 00:50:19] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-24 00:50:23] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-24 00:50:23] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-24 00:50:23] ...trap/engines/engine.py.470: Saving model... [I 2022-10-24 00:50:26] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-24 00:50:32] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-24 00:50:32] ...trap/engines/engine.py.163: Training model on trainset for epoch 28 [I 2022-10-24 00:50:32] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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image_from: database [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: import: recipe1m.datasets.factory [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: kw_path: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_ingr_kw.json [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_ingr_kw.json [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_ingr_kw.json [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: name: recipe1m_13m [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: nb_classes: 1048 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: nb_threads: 4 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: orig_ids_eval: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: path_ids: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/original_ids.json [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: engine: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-24 08:37:12] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-24 08:37:13] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a101', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-24 08:37:13] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-24 08:37:13] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-24 08:37:13] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-24 08:39:12] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-24 08:39:25] ...tasets/recipe1m_13m.py.293: randkw_p... 0.3 [I 2022-10-24 08:41:12] ...tasets/recipe1m_13m.py.280: Load VCs... [I 2022-10-24 08:41:13] ...tasets/recipe1m_13m.py.293: randkw_p... None [I 2022-10-24 08:41:13] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-24 08:41:13] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-24 08:41:13] ...strap/models/factory.py.21: Creating model... [I 2022-10-24 08:41:18] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-24 08:41:22] ...e_networks/networks.py.145: cuda [I 2022-10-24 08:41:23] ...networks/tfood_vicha.py.49: Load VCs encoder... [I 2022-10-24 08:41:25] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-24 08:41:25] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-24 08:41:25] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-24 08:41:25] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-24 08:41:27] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-24 08:41:27] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-24 08:41:27] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-24 08:41:32] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-24 08:41:32] ...trap/engines/engine.py.440: Loading model... [I 2022-10-24 08:41:38] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-24 08:41:44] ...etworks/tfood_vicha.py.184: training aux kw modules [I 2022-10-24 08:41:44] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-24 08:41:44] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-24 08:41:44] ...trap/engines/engine.py.163: Training model on trainset for epoch 28 [I 2022-10-24 08:41:44] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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train: epoch 28 | batch 7425/7425 [I 2022-10-24 12:10:29] ...trap/engines/engine.py.228: elapsed: 3:28:45 | left: 0:00:00 [I 2022-10-24 12:10:29] ...trap/engines/engine.py.229: process: 4.61678 | load: 3.78190 [I 2022-10-24 12:10:29] ...trap/engines/engine.py.230: loss: 0.45954 [I 2022-10-24 12:10:29] ...optimizers/trijoint.py.151: total_norm: 25.502575 [S 2022-10-24 12:10:31] ...trap/engines/engine.py.129: train_epoch.epoch: 28 [S 2022-10-24 12:10:31] ...trap/engines/engine.py.129: train_epoch.loss: 0.36825147147147186 [I 2022-10-24 12:10:31] ...iterions/vlp_triplet.py.80: margin = 0.19 [I 2022-10-24 12:10:33] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 28 [I 2022-10-24 12:10:33] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [W 2022-10-24 12:10:39] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-24 12:10:39] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-24 12:10:39] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-24 12:10:44] ...trap/engines/engine.py.321: eval: epoch 28 | batch 0/1578 [I 2022-10-24 12:10:44] ...trap/engines/engine.py.325: elapsed: 0:00:11 | left: 4:57:03 [I 2022-10-24 12:10:44] ...trap/engines/engine.py.326: process: 11.29479 | load: 10.47490 [I 2022-10-24 12:10:48] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-24 12:10:57] ...trap/engines/engine.py.321: eval: epoch 28 | batch 10/1578 [I 2022-10-24 12:10:57] ...trap/engines/engine.py.325: elapsed: 0:00:23 | left: 1:01:18 [I 2022-10-24 12:10:57] ...trap/engines/engine.py.326: process: 0.50095 | load: 0.00007 [I 2022-10-24 12:11:17] ...trap/engines/engine.py.321: eval: epoch 28 | batch 20/1578 [I 2022-10-24 12:11:17] ...trap/engines/engine.py.325: elapsed: 0:00:43 | left: 1:00:12 [I 2022-10-24 12:11:17] ...trap/engines/engine.py.326: process: 5.48773 | load: 5.03680 [I 2022-10-24 12:11:30] ...trap/engines/engine.py.321: eval: epoch 28 | batch 30/1578 [I 2022-10-24 12:11:30] ...trap/engines/engine.py.325: elapsed: 0:00:57 | left: 0:38:01 [I 2022-10-24 12:11:30] ...trap/engines/engine.py.326: process: 0.43477 | load: 0.00016 [I 2022-10-24 12:11:50] ...trap/engines/engine.py.321: eval: epoch 28 | batch 40/1578 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[W 2022-10-24 12:52:33] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-24 12:52:33] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-24 12:52:33] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-24 12:52:37] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-24 12:52:40] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-24 12:52:44] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-24 12:52:44] ...trap/engines/engine.py.163: Training model on trainset for epoch 29 [I 2022-10-24 12:52:44] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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train: epoch 29 | batch 7425/7425 [I 2022-10-24 16:29:45] ...trap/engines/engine.py.228: elapsed: 3:37:00 | left: 0:00:00 [I 2022-10-24 16:29:45] ...trap/engines/engine.py.229: process: 1.52011 | load: 0.71502 [I 2022-10-24 16:29:45] ...trap/engines/engine.py.230: loss: 0.32215 [I 2022-10-24 16:29:45] ...optimizers/trijoint.py.151: total_norm: 16.271669 [S 2022-10-24 16:29:46] ...trap/engines/engine.py.129: train_epoch.epoch: 29 [S 2022-10-24 16:29:46] ...trap/engines/engine.py.129: train_epoch.loss: 0.3661987186260792 [I 2022-10-24 16:29:46] ...iterions/vlp_triplet.py.80: margin = 0.195 [I 2022-10-24 16:29:48] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 29 [I 2022-10-24 16:29:48] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. [W 2022-10-24 16:29:50] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-24 16:29:51] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-24 16:29:51] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-24 16:29:54] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-24 16:29:59] ...trap/engines/engine.py.321: eval: epoch 29 | batch 0/1578 [I 2022-10-24 16:29:59] ...trap/engines/engine.py.325: elapsed: 0:00:11 | left: 4:56:44 [I 2022-10-24 16:29:59] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.011534 [S 2022-10-24 17:12:44] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011482 [S 2022-10-24 17:12:44] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.016811 [S 2022-10-24 17:12:44] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.011367 [S 2022-10-24 17:12:44] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.008440 [I 2022-10-24 17:13:01] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-24 17:13:01] ...trap/engines/engine.py.470: Saving model... [W 2022-10-24 17:13:02] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-24 17:13:02] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-24 17:13:02] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-24 17:13:06] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-24 17:13:10] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-24 17:13:13] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-24 17:13:13] ...trap/engines/engine.py.163: Training model on trainset for epoch 30 [I 2022-10-24 17:13:13] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-24 20:49:00] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-24 20:49:00] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-24 20:49:00] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-24 20:49:03] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-24 20:49:06] ...trap/engines/engine.py.321: eval: epoch 30 | batch 0/1578 [I 2022-10-24 20:49:06] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:02:31 [I 2022-10-24 20:49:06] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.012305 [S 2022-10-24 21:30:15] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011706 [S 2022-10-24 21:30:15] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.014698 [S 2022-10-24 21:30:15] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.011560 [S 2022-10-24 21:30:15] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.012085 [I 2022-10-24 21:30:34] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-24 21:30:34] ...trap/engines/engine.py.470: Saving model... [W 2022-10-24 21:30:34] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-24 21:30:34] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-24 21:30:34] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-24 21:30:38] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-24 21:30:43] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-24 21:30:45] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-24 21:30:45] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-24 21:30:45] ...trap/engines/engine.py.470: Saving model... [I 2022-10-24 21:30:49] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-24 21:30:55] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-24 21:30:55] ...trap/engines/engine.py.163: Training model on trainset for epoch 31 [I 2022-10-24 21:30:55] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-25 01:06:52] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-25 01:06:52] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-25 01:06:52] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-25 01:06:58] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-25 01:07:02] ...trap/engines/engine.py.321: eval: epoch 31 | batch 0/1578 [I 2022-10-25 01:07:02] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:18:44 [I 2022-10-25 01:07:02] 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[W 2022-10-25 01:52:55] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-25 01:52:55] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-25 01:52:55] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-25 01:52:59] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-25 01:53:04] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-25 01:53:06] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-25 01:53:06] ...trap/engines/engine.py.163: Training model on trainset for epoch 32 [I 2022-10-25 01:53:06] ...tasets/recipe1m_13m.py.454: Dataset will be sampled with "random" batch_sampler. 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...ytorch/bootstrap/run.py.75: aux_kw_path: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_titles_kw.json [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_titles_kw.json [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_titles_kw.json [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: batch_sampler: random [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: batch_size: 96 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: database: lmdb [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: dir: /gpfsdswork/dataset/Recipe1M+/images_recipe1M+ [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: eval_split: val [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: freq_mismatch: 0.0 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: image_from: database [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: import: recipe1m.datasets.factory [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: kw_path: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_ingr_kw.json [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_ingr_kw.json [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_ingr_kw.json [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: name: recipe1m_13m [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: nb_classes: 1048 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: nb_threads: 4 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: orig_ids_eval: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: path_ids: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/original_ids.json [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: engine: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-25 08:24:59] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-25 08:25:00] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a103', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-25 08:25:01] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-25 08:25:01] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-25 08:25:01] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-25 08:26:55] ...tasets/recipe1m_13m.py.281: Load VCs... [I 2022-10-25 08:27:08] ...tasets/recipe1m_13m.py.294: randkw_p... 0.3 [I 2022-10-25 08:28:51] ...tasets/recipe1m_13m.py.281: Load VCs... [I 2022-10-25 08:28:51] ...tasets/recipe1m_13m.py.294: randkw_p... None [I 2022-10-25 08:28:52] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-25 08:28:52] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-25 08:28:52] ...strap/models/factory.py.21: Creating model... [I 2022-10-25 08:28:56] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-25 08:29:00] ...e_networks/networks.py.145: cuda [I 2022-10-25 08:29:01] ...networks/tfood_vicha.py.48: Load VCs encoder... [I 2022-10-25 08:29:03] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-25 08:29:03] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-25 08:29:03] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-25 08:29:03] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-25 08:29:09] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-25 08:29:09] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-25 08:29:09] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-25 08:29:14] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-25 08:29:14] ...trap/engines/engine.py.440: Loading model... [I 2022-10-25 08:29:20] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-25 08:29:25] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-25 08:29:25] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-25 08:29:25] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-25 08:29:25] ...trap/engines/engine.py.163: Training model on trainset for epoch 32 [I 2022-10-25 08:29:25] ...tasets/recipe1m_13m.py.455: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-25 11:57:54] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-25 11:57:54] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-25 11:57:54] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-25 11:57:59] ...trap/engines/engine.py.321: eval: epoch 32 | batch 0/1578 [I 2022-10-25 11:57:59] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:15:18 [I 2022-10-25 11:57:59] ...trap/engines/engine.py.326: process: 9.70760 | load: 8.89618 [I 2022-10-25 11:58:02] ...tstrap/views/plotly.py.125: Plotly view generated in 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[W 2022-10-25 12:41:15] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-25 12:41:15] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-25 12:41:15] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-25 12:41:19] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-25 12:41:22] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-25 12:41:26] ...trap/engines/engine.py.478: Saving engine... 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16:10:15] ...optimizers/trijoint.py.151: total_norm: 14.587315 [I 2022-10-25 16:10:33] ...trap/engines/engine.py.224: train: epoch 33 | batch 7360/7425 [I 2022-10-25 16:10:33] ...trap/engines/engine.py.228: elapsed: 3:29:07 | left: 0:02:04 [I 2022-10-25 16:10:33] ...trap/engines/engine.py.229: process: 3.50888 | load: 2.69302 [I 2022-10-25 16:10:33] ...trap/engines/engine.py.230: loss: 0.29469 [I 2022-10-25 16:10:33] ...optimizers/trijoint.py.151: total_norm: 15.995934 [I 2022-10-25 16:10:48] ...trap/engines/engine.py.224: train: epoch 33 | batch 7370/7425 [I 2022-10-25 16:10:48] ...trap/engines/engine.py.228: elapsed: 3:29:21 | left: 0:01:21 [I 2022-10-25 16:10:48] ...trap/engines/engine.py.229: process: 0.82842 | load: 0.00014 [I 2022-10-25 16:10:48] ...trap/engines/engine.py.230: loss: 0.43530 [I 2022-10-25 16:10:48] ...optimizers/trijoint.py.151: total_norm: 18.382700 [I 2022-10-25 16:11:04] ...trap/engines/engine.py.224: train: epoch 33 | batch 7380/7425 [I 2022-10-25 16:11:04] 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[W 2022-10-25 16:12:27] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-25 16:12:27] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-25 16:12:27] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-25 16:12:30] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-25 16:12:34] ...trap/engines/engine.py.321: eval: epoch 33 | batch 0/1578 [I 2022-10-25 16:12:34] ...trap/engines/engine.py.325: elapsed: 0:00:10 | left: 4:27:52 [I 2022-10-25 16:12:34] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.010147 [S 2022-10-25 16:54:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.008605 [S 2022-10-25 16:54:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.010616 [S 2022-10-25 16:54:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.007652 [S 2022-10-25 16:54:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.008403 [I 2022-10-25 16:55:07] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-25 16:55:07] ...trap/engines/engine.py.470: Saving model... [W 2022-10-25 16:55:08] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-25 16:55:08] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-25 16:55:08] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-25 16:55:12] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-25 16:55:16] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-25 16:55:19] ...trap/engines/engine.py.478: Saving engine... 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20:15:10] ...optimizers/trijoint.py.151: total_norm: 14.604115 [I 2022-10-25 20:15:27] ...trap/engines/engine.py.224: train: epoch 34 | batch 7360/7425 [I 2022-10-25 20:15:27] ...trap/engines/engine.py.228: elapsed: 3:20:07 | left: 0:01:55 [I 2022-10-25 20:15:27] ...trap/engines/engine.py.229: process: 2.85814 | load: 2.02791 [I 2022-10-25 20:15:27] ...trap/engines/engine.py.230: loss: 0.26922 [I 2022-10-25 20:15:27] ...optimizers/trijoint.py.151: total_norm: 14.403435 [I 2022-10-25 20:15:40] ...trap/engines/engine.py.224: train: epoch 34 | batch 7370/7425 [I 2022-10-25 20:15:40] ...trap/engines/engine.py.228: elapsed: 3:20:20 | left: 0:01:12 [I 2022-10-25 20:15:40] ...trap/engines/engine.py.229: process: 0.81167 | load: 0.00017 [I 2022-10-25 20:15:40] ...trap/engines/engine.py.230: loss: 0.30772 [I 2022-10-25 20:15:40] ...optimizers/trijoint.py.151: total_norm: 18.057871 [I 2022-10-25 20:16:00] ...trap/engines/engine.py.224: train: epoch 34 | batch 7380/7425 [I 2022-10-25 20:16:00] 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train: epoch 34 | batch 7425/7425 [I 2022-10-25 20:17:16] ...trap/engines/engine.py.228: elapsed: 3:21:56 | left: 0:00:00 [I 2022-10-25 20:17:16] ...trap/engines/engine.py.229: process: 0.81102 | load: 0.00002 [I 2022-10-25 20:17:16] ...trap/engines/engine.py.230: loss: 0.42177 [I 2022-10-25 20:17:16] ...optimizers/trijoint.py.151: total_norm: 20.079588 [S 2022-10-25 20:17:17] ...trap/engines/engine.py.129: train_epoch.epoch: 34 [S 2022-10-25 20:17:17] ...trap/engines/engine.py.129: train_epoch.loss: 0.3612328089077358 [I 2022-10-25 20:17:17] ...iterions/vlp_triplet.py.80: margin = 0.22000000000000003 [I 2022-10-25 20:17:19] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 34 [I 2022-10-25 20:17:20] ...tasets/recipe1m_13m.py.455: Dataset will be sampled with "random" batch_sampler. [W 2022-10-25 20:17:22] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-25 20:17:22] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-25 20:17:22] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-25 20:17:26] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-25 20:17:29] ...trap/engines/engine.py.321: eval: epoch 34 | batch 0/1578 [I 2022-10-25 20:17:29] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:15:45 [I 2022-10-25 20:17:29] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.014258 [S 2022-10-25 21:02:10] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.008215 [S 2022-10-25 21:02:10] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.014082 [S 2022-10-25 21:02:10] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.010703 [S 2022-10-25 21:02:10] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.005936 [I 2022-10-25 21:02:25] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-25 21:02:25] ...trap/engines/engine.py.470: Saving model... [W 2022-10-25 21:02:26] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-25 21:02:26] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-25 21:02:26] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-25 21:02:30] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-25 21:02:34] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-25 21:02:37] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-25 21:02:37] ...trap/engines/engine.py.163: Training model on trainset for epoch 35 [I 2022-10-25 21:02:37] ...tasets/recipe1m_13m.py.455: Dataset will be sampled with "random" batch_sampler. 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train: epoch 35 | batch 7425/7425 [I 2022-10-26 00:27:01] ...trap/engines/engine.py.228: elapsed: 3:24:23 | left: 0:00:00 [I 2022-10-26 00:27:01] ...trap/engines/engine.py.229: process: 0.81659 | load: 0.00010 [I 2022-10-26 00:27:01] ...trap/engines/engine.py.230: loss: 0.35263 [I 2022-10-26 00:27:01] ...optimizers/trijoint.py.151: total_norm: 20.751772 [S 2022-10-26 00:27:03] ...trap/engines/engine.py.129: train_epoch.epoch: 35 [S 2022-10-26 00:27:03] ...trap/engines/engine.py.129: train_epoch.loss: 0.3592769403081842 [I 2022-10-26 00:27:03] ...iterions/vlp_triplet.py.80: margin = 0.22500000000000003 [I 2022-10-26 00:27:04] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 35 [I 2022-10-26 00:27:04] ...tasets/recipe1m_13m.py.455: Dataset will be sampled with "random" batch_sampler. [W 2022-10-26 00:27:07] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-26 00:27:07] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-26 00:27:07] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-26 00:27:11] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-26 00:27:14] ...trap/engines/engine.py.321: eval: epoch 35 | batch 0/1578 [I 2022-10-26 00:27:14] ...trap/engines/engine.py.325: elapsed: 0:00:10 | left: 4:23:33 [I 2022-10-26 00:27:14] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.007382 [S 2022-10-26 01:08:28] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.008276 [S 2022-10-26 01:08:28] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.012552 [S 2022-10-26 01:08:28] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.007652 [S 2022-10-26 01:08:28] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.008658 [I 2022-10-26 01:08:45] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-26 01:08:45] ...trap/engines/engine.py.470: Saving model... [W 2022-10-26 01:08:45] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-26 01:08:45] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-26 01:08:45] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-26 01:08:49] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-26 01:08:53] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-26 01:08:57] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-26 01:08:57] ...trap/engines/engine.py.163: Training model on trainset for epoch 36 [I 2022-10-26 01:08:57] ...tasets/recipe1m_13m.py.455: Dataset will be sampled with "random" batch_sampler. 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...ytorch/bootstrap/run.py.75: aux_kw_path: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_titles_kw.json [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_titles_kw.json [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_titles_kw.json [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: batch_sampler: random [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: batch_size: 96 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: database: lmdb [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: dir: /gpfsdswork/dataset/Recipe1M+/images_recipe1M+ [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: eval_split: val [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: freq_mismatch: 0.0 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: image_from: database [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: import: recipe1m.datasets.factory [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: kw_path: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_ingr_kw.json [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_ingr_kw.json [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_ingr_kw.json [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: name: recipe1m_13m [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: nb_classes: 1048 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: nb_threads: 4 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: orig_ids_eval: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: path_ids: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/original_ids.json [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: engine: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-26 06:59:08] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-26 06:59:09] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a101', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-26 06:59:10] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-26 06:59:10] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-26 06:59:10] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-26 07:01:05] ...tasets/recipe1m_13m.py.282: Load VCs... [I 2022-10-26 07:01:19] ...tasets/recipe1m_13m.py.295: randkw_p... 0.3 [I 2022-10-26 07:03:02] ...tasets/recipe1m_13m.py.282: Load VCs... [I 2022-10-26 07:03:03] ...tasets/recipe1m_13m.py.295: randkw_p... None [I 2022-10-26 07:03:03] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-26 07:03:03] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-26 07:03:03] ...strap/models/factory.py.21: Creating model... [I 2022-10-26 07:03:08] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-26 07:03:12] ...e_networks/networks.py.145: cuda [I 2022-10-26 07:03:13] ...networks/tfood_vicha.py.48: Load VCs encoder... [I 2022-10-26 07:03:15] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-26 07:03:15] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-26 07:03:15] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-26 07:03:15] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-26 07:03:21] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-26 07:03:21] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-26 07:03:22] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-26 07:03:26] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-26 07:03:26] ...trap/engines/engine.py.440: Loading model... [I 2022-10-26 07:03:31] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-26 07:03:37] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-26 07:03:37] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-26 07:03:37] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-26 07:03:37] ...trap/engines/engine.py.163: Training model on trainset for epoch 36 [I 2022-10-26 07:03:37] ...tasets/recipe1m_13m.py.458: Dataset will be sampled with "random" batch_sampler. [E 2022-10-26 07:03:39] ...torch/bootstrap/run.py.201: Traceback (most recent call last): File "/gpfs7kw/linkhome/rech/genisi01/ugz83ue/tfood/bootstrap.pytorch/bootstrap/run.py", line 186, in main run(path_opts=path_opts, rank=rank) File "/gpfs7kw/linkhome/rech/genisi01/ugz83ue/tfood/bootstrap.pytorch/bootstrap/run.py", line 120, in run engine.train() File "/gpfs7kw/linkhome/rech/genisi01/ugz83ue/tfood/bootstrap.pytorch/bootstrap/engines/engine.py", line 129, in train self.train_epoch(self.model, self.dataset['train'], self.optimizer, self.epoch) File "/gpfs7kw/linkhome/rech/genisi01/ugz83ue/tfood/bootstrap.pytorch/bootstrap/engines/engine.py", line 177, in train_epoch for i, batch in enumerate(batch_loader): File "/gpfswork/rech/dyf/ugz83ue/conda/envs/tfood/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 435, in __next__ data = self._next_data() File "/gpfswork/rech/dyf/ugz83ue/conda/envs/tfood/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1085, in _next_data return self._process_data(data) File "/gpfswork/rech/dyf/ugz83ue/conda/envs/tfood/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 1111, in _process_data data.reraise() File "/gpfswork/rech/dyf/ugz83ue/conda/envs/tfood/lib/python3.7/site-packages/torch/_utils.py", line 428, in reraise raise self.exc_type(msg) UnboundLocalError: Caught UnboundLocalError in DataLoader worker process 0. Original Traceback (most recent call last): File "/gpfswork/rech/dyf/ugz83ue/conda/envs/tfood/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 198, in _worker_loop data = fetcher.fetch(index) File "/gpfswork/rech/dyf/ugz83ue/conda/envs/tfood/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/gpfswork/rech/dyf/ugz83ue/conda/envs/tfood/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py", line 44, in data = [self.dataset[idx] for idx in possibly_batched_index] File "/gpfs7kw/linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/datasets/recipe1m_13m.py", line 326, in __getitem__ img_name = choice(image_entry[:num_images]) UnboundLocalError: local variable 'num_images' referenced before assignment [I 2022-10-28 12:05:31] ...ytorch/bootstrap/run.py.73: Saving environment info [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: options: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: dataset: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: aux_kw_path: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_titles_kw.json [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_titles_kw.json [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_titles_kw.json [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: batch_sampler: random [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: batch_size: 96 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: database: lmdb [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: dir: /gpfsdswork/dataset/Recipe1M+/images_recipe1M+ [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: eval_split: val [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: freq_mismatch: 0.0 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: image_from: database [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: import: recipe1m.datasets.factory [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: kw_path: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_ingr_kw.json [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_ingr_kw.json [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_ingr_kw.json [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: name: recipe1m_13m [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: nb_classes: 1048 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: nb_threads: 4 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: orig_ids_eval: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: path_ids: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/original_ids.json [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: engine: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-28 12:05:41] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-28 12:05:43] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a101', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-28 12:05:43] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-28 12:05:43] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-28 12:05:43] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-28 12:07:42] ...tasets/recipe1m_13m.py.282: Load VCs... [I 2022-10-28 12:07:55] ...tasets/recipe1m_13m.py.295: randkw_p... 0.3 [I 2022-10-28 12:09:38] ...tasets/recipe1m_13m.py.282: Load VCs... [I 2022-10-28 12:09:39] ...tasets/recipe1m_13m.py.295: randkw_p... None [I 2022-10-28 12:09:39] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-28 12:09:39] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-28 12:09:39] ...strap/models/factory.py.21: Creating model... [I 2022-10-28 12:09:44] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-28 12:09:48] ...e_networks/networks.py.145: cuda [I 2022-10-28 12:09:49] ...networks/tfood_vicha.py.48: Load VCs encoder... [I 2022-10-28 12:09:51] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-28 12:09:51] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-28 12:09:51] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-28 12:09:51] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-28 12:09:58] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-28 12:09:58] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-28 12:09:58] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-28 12:10:03] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-28 12:10:03] ...trap/engines/engine.py.440: Loading model... [I 2022-10-28 12:10:10] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-28 12:10:17] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-28 12:10:17] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-28 12:10:17] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-28 12:10:17] ...trap/engines/engine.py.163: Training model on trainset for epoch 36 [I 2022-10-28 12:10:17] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. [I 2022-10-28 12:10:30] ...trap/engines/engine.py.224: train: epoch 36 | batch 0/7425 [I 2022-10-28 12:10:30] ...trap/engines/engine.py.228: elapsed: 0:00:13 | left: 1 day, 4:41:40 [I 2022-10-28 12:10:30] ...trap/engines/engine.py.229: process: 13.91252 | load: 8.01544 [I 2022-10-28 12:10:30] ...trap/engines/engine.py.230: loss: 0.29850 [I 2022-10-28 12:10:30] ...optimizers/trijoint.py.151: total_norm: 14.546798 [I 2022-10-28 12:10:39] ...trap/engines/engine.py.224: train: epoch 36 | batch 10/7425 [I 2022-10-28 12:10:39] ...trap/engines/engine.py.228: elapsed: 0:00:22 | left: 4:34:46 [I 2022-10-28 12:10:39] ...trap/engines/engine.py.229: process: 0.80383 | load: 0.00016 [I 2022-10-28 12:10:39] ...trap/engines/engine.py.230: loss: 0.38427 [I 2022-10-28 12:10:39] ...optimizers/trijoint.py.151: total_norm: 19.538532 [I 2022-10-28 12:10:53] ...trap/engines/engine.py.224: train: epoch 36 | batch 20/7425 [I 2022-10-28 12:10:53] ...trap/engines/engine.py.228: elapsed: 0:00:36 | left: 3:04:54 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...optimizers/trijoint.py.151: total_norm: 30.301897 [I 2022-10-28 12:11:35] ...trap/engines/engine.py.224: train: epoch 36 | batch 50/7425 [I 2022-10-28 12:11:35] ...trap/engines/engine.py.228: elapsed: 0:01:18 | left: 2:47:36 [I 2022-10-28 12:11:35] ...trap/engines/engine.py.229: process: 0.80439 | load: 0.00016 [I 2022-10-28 12:11:35] ...trap/engines/engine.py.230: loss: 0.33574 [I 2022-10-28 12:11:35] ...optimizers/trijoint.py.151: total_norm: 18.575182 [I 2022-10-28 12:11:50] ...trap/engines/engine.py.224: train: epoch 36 | batch 60/7425 [I 2022-10-28 12:11:50] ...trap/engines/engine.py.228: elapsed: 0:01:33 | left: 3:13:32 [I 2022-10-28 12:11:50] ...trap/engines/engine.py.229: process: 2.47489 | load: 1.66367 [I 2022-10-28 12:11:50] ...trap/engines/engine.py.230: loss: 0.32025 [I 2022-10-28 12:11:50] ...optimizers/trijoint.py.151: total_norm: 16.094700 [I 2022-10-28 12:12:04] ...trap/engines/engine.py.224: train: epoch 36 | batch 70/7425 [I 2022-10-28 12:12:04] 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...optimizers/trijoint.py.151: total_norm: 13.836734 [I 2022-10-28 12:15:42] ...trap/engines/engine.py.224: train: epoch 36 | batch 220/7425 [I 2022-10-28 12:15:42] ...trap/engines/engine.py.228: elapsed: 0:05:24 | left: 3:08:23 [I 2022-10-28 12:15:42] ...trap/engines/engine.py.229: process: 1.90444 | load: 1.10965 [I 2022-10-28 12:15:42] ...trap/engines/engine.py.230: loss: 0.33150 [I 2022-10-28 12:15:42] ...optimizers/trijoint.py.151: total_norm: 15.313310 [I 2022-10-28 12:15:55] ...trap/engines/engine.py.224: train: epoch 36 | batch 230/7425 [I 2022-10-28 12:15:55] ...trap/engines/engine.py.228: elapsed: 0:05:38 | left: 2:44:43 [I 2022-10-28 12:15:55] ...trap/engines/engine.py.229: process: 0.80157 | load: 0.00013 [I 2022-10-28 12:15:55] ...trap/engines/engine.py.230: loss: 0.32297 [I 2022-10-28 12:15:55] ...optimizers/trijoint.py.151: total_norm: 14.385394 [I 2022-10-28 12:16:11] ...trap/engines/engine.py.224: train: epoch 36 | batch 240/7425 [I 2022-10-28 12:16:11] 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15:06:10] ...optimizers/trijoint.py.151: total_norm: 18.447660 [I 2022-10-28 15:06:26] ...trap/engines/engine.py.224: train: epoch 36 | batch 7360/7425 [I 2022-10-28 15:06:26] ...trap/engines/engine.py.228: elapsed: 2:56:09 | left: 0:01:53 [I 2022-10-28 15:06:26] ...trap/engines/engine.py.229: process: 3.69929 | load: 2.87541 [I 2022-10-28 15:06:26] ...trap/engines/engine.py.230: loss: 0.37627 [I 2022-10-28 15:06:26] ...optimizers/trijoint.py.151: total_norm: 17.592779 [I 2022-10-28 15:06:40] ...trap/engines/engine.py.224: train: epoch 36 | batch 7370/7425 [I 2022-10-28 15:06:40] ...trap/engines/engine.py.228: elapsed: 2:56:23 | left: 0:01:16 [I 2022-10-28 15:06:40] ...trap/engines/engine.py.229: process: 0.80168 | load: 0.00014 [I 2022-10-28 15:06:40] ...trap/engines/engine.py.230: loss: 0.29643 [I 2022-10-28 15:06:40] ...optimizers/trijoint.py.151: total_norm: 14.213676 [I 2022-10-28 15:06:55] ...trap/engines/engine.py.224: train: epoch 36 | batch 7380/7425 [I 2022-10-28 15:06:55] ...trap/engines/engine.py.228: elapsed: 2:56:38 | left: 0:01:19 [I 2022-10-28 15:06:55] ...trap/engines/engine.py.229: process: 3.86069 | load: 3.05492 [I 2022-10-28 15:06:55] ...trap/engines/engine.py.230: loss: 0.37188 [I 2022-10-28 15:06:55] ...optimizers/trijoint.py.151: total_norm: 13.389138 [I 2022-10-28 15:07:08] ...trap/engines/engine.py.224: train: epoch 36 | batch 7390/7425 [I 2022-10-28 15:07:08] ...trap/engines/engine.py.228: elapsed: 2:56:51 | left: 0:00:46 [I 2022-10-28 15:07:08] ...trap/engines/engine.py.229: process: 0.80106 | load: 0.00014 [I 2022-10-28 15:07:08] ...trap/engines/engine.py.230: loss: 0.38905 [I 2022-10-28 15:07:08] ...optimizers/trijoint.py.151: total_norm: 16.973724 [I 2022-10-28 15:07:22] ...trap/engines/engine.py.224: train: epoch 36 | batch 7400/7425 [I 2022-10-28 15:07:22] ...trap/engines/engine.py.228: elapsed: 2:57:05 | left: 0:00:36 [I 2022-10-28 15:07:22] ...trap/engines/engine.py.229: process: 2.84496 | load: 2.00907 [I 2022-10-28 15:07:22] ...trap/engines/engine.py.230: loss: 0.33897 [I 2022-10-28 15:07:22] ...optimizers/trijoint.py.151: total_norm: 16.936333 [I 2022-10-28 15:07:35] ...trap/engines/engine.py.224: train: epoch 36 | batch 7410/7425 [I 2022-10-28 15:07:35] ...trap/engines/engine.py.228: elapsed: 2:57:17 | left: 0:00:19 [I 2022-10-28 15:07:35] ...trap/engines/engine.py.229: process: 0.78779 | load: 0.00007 [I 2022-10-28 15:07:35] ...trap/engines/engine.py.230: loss: 0.32877 [I 2022-10-28 15:07:35] ...optimizers/trijoint.py.151: total_norm: 14.270121 [I 2022-10-28 15:07:50] ...trap/engines/engine.py.224: train: epoch 36 | batch 7420/7425 [I 2022-10-28 15:07:50] ...trap/engines/engine.py.228: elapsed: 2:57:33 | left: 0:00:06 [I 2022-10-28 15:07:50] ...trap/engines/engine.py.229: process: 0.87248 | load: 0.00017 [I 2022-10-28 15:07:50] ...trap/engines/engine.py.230: loss: 0.41835 [I 2022-10-28 15:07:50] ...optimizers/trijoint.py.151: total_norm: 16.731222 [I 2022-10-28 15:08:00] ...trap/engines/engine.py.224: train: epoch 36 | batch 7425/7425 [I 2022-10-28 15:08:00] ...trap/engines/engine.py.228: elapsed: 2:57:43 | left: 0:00:00 [I 2022-10-28 15:08:00] ...trap/engines/engine.py.229: process: 4.28555 | load: 3.44123 [I 2022-10-28 15:08:00] ...trap/engines/engine.py.230: loss: 0.38687 [I 2022-10-28 15:08:00] ...optimizers/trijoint.py.151: total_norm: 18.649874 [S 2022-10-28 15:08:02] ...trap/engines/engine.py.129: train_epoch.epoch: 36 [S 2022-10-28 15:08:02] ...trap/engines/engine.py.129: train_epoch.loss: 0.3602839078831441 [I 2022-10-28 15:08:02] ...iterions/vlp_triplet.py.80: margin = 0.23000000000000004 [I 2022-10-28 15:08:04] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 36 [I 2022-10-28 15:08:04] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. [W 2022-10-28 15:08:10] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-28 15:08:10] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-28 15:08:10] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-28 15:08:15] ...trap/engines/engine.py.321: eval: epoch 36 | batch 0/1578 [I 2022-10-28 15:08:15] ...trap/engines/engine.py.325: elapsed: 0:00:10 | left: 4:36:56 [I 2022-10-28 15:08:15] ...trap/engines/engine.py.326: process: 10.53037 | load: 8.43249 [I 2022-10-28 15:08:20] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-28 15:08:24] ...trap/engines/engine.py.321: eval: epoch 36 | batch 10/1578 [I 2022-10-28 15:08:24] ...trap/engines/engine.py.325: elapsed: 0:00:20 | left: 0:54:44 [I 2022-10-28 15:08:24] ...trap/engines/engine.py.326: process: 0.81180 | load: 0.41935 [I 2022-10-28 15:08:42] ...trap/engines/engine.py.321: eval: epoch 36 | batch 20/1578 [I 2022-10-28 15:08:42] ...trap/engines/engine.py.325: elapsed: 0:00:37 | left: 0:45:10 [I 2022-10-28 15:08:42] ...trap/engines/engine.py.326: process: 1.61589 | load: 0.00015 [I 2022-10-28 15:08:53] ...trap/engines/engine.py.321: eval: epoch 36 | batch 30/1578 [I 2022-10-28 15:08:53] ...trap/engines/engine.py.325: elapsed: 0:00:49 | left: 0:32:55 [I 2022-10-28 15:08:53] ...trap/engines/engine.py.326: process: 1.46484 | load: 1.03878 [I 2022-10-28 15:09:07] ...trap/engines/engine.py.321: eval: epoch 36 | batch 40/1578 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eval_epoch.metric.recall_at_1_im2recipe_std: 0.017820 [S 2022-10-28 15:44:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.013134 [S 2022-10-28 15:44:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011379 [S 2022-10-28 15:44:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.014216 [S 2022-10-28 15:44:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.014179 [S 2022-10-28 15:44:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.011671 [I 2022-10-28 15:44:51] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-28 15:44:51] ...trap/engines/engine.py.470: Saving model... [W 2022-10-28 15:44:52] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-28 15:44:52] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-28 15:44:52] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-28 15:44:55] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-28 15:45:02] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-28 15:45:02] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-28 15:45:02] ...trap/engines/engine.py.163: Training model on trainset for epoch 37 [I 2022-10-28 15:45:02] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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[I 2022-10-28 19:05:52] ...trap/engines/engine.py.224: train: epoch 37 | batch 7310/7425 [I 2022-10-28 19:05:52] ...trap/engines/engine.py.228: elapsed: 3:20:49 | left: 0:03:02 [I 2022-10-28 19:05:52] ...trap/engines/engine.py.229: process: 1.89182 | load: 1.07648 [I 2022-10-28 19:05:52] ...trap/engines/engine.py.230: loss: 0.37743 [I 2022-10-28 19:05:52] ...optimizers/trijoint.py.151: total_norm: 17.631617 [I 2022-10-28 19:06:06] ...trap/engines/engine.py.224: train: epoch 37 | batch 7320/7425 [I 2022-10-28 19:06:06] ...trap/engines/engine.py.228: elapsed: 3:21:03 | left: 0:02:20 [I 2022-10-28 19:06:06] ...trap/engines/engine.py.229: process: 0.83067 | load: 0.00018 [I 2022-10-28 19:06:06] ...trap/engines/engine.py.230: loss: 0.47183 [I 2022-10-28 19:06:06] ...optimizers/trijoint.py.151: total_norm: 14.957063 [I 2022-10-28 19:06:22] ...trap/engines/engine.py.224: train: epoch 37 | batch 7330/7425 [I 2022-10-28 19:06:22] ...trap/engines/engine.py.228: elapsed: 3:21:19 | left: 0:02:33 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19:06:54] ...optimizers/trijoint.py.151: total_norm: 16.975792 [I 2022-10-28 19:07:07] ...trap/engines/engine.py.224: train: epoch 37 | batch 7360/7425 [I 2022-10-28 19:07:07] ...trap/engines/engine.py.228: elapsed: 3:22:04 | left: 0:01:25 [I 2022-10-28 19:07:07] ...trap/engines/engine.py.229: process: 0.81363 | load: 0.00013 [I 2022-10-28 19:07:07] ...trap/engines/engine.py.230: loss: 0.33721 [I 2022-10-28 19:07:07] ...optimizers/trijoint.py.151: total_norm: 24.600737 [I 2022-10-28 19:07:23] ...trap/engines/engine.py.224: train: epoch 37 | batch 7370/7425 [I 2022-10-28 19:07:23] ...trap/engines/engine.py.228: elapsed: 3:22:20 | left: 0:01:31 [I 2022-10-28 19:07:23] ...trap/engines/engine.py.229: process: 1.72438 | load: 0.91772 [I 2022-10-28 19:07:23] ...trap/engines/engine.py.230: loss: 0.35178 [I 2022-10-28 19:07:23] ...optimizers/trijoint.py.151: total_norm: 15.738887 [I 2022-10-28 19:07:36] ...trap/engines/engine.py.224: train: epoch 37 | batch 7380/7425 [I 2022-10-28 19:07:36] 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train: epoch 37 | batch 7425/7425 [I 2022-10-28 19:08:46] ...trap/engines/engine.py.228: elapsed: 3:23:43 | left: 0:00:00 [I 2022-10-28 19:08:46] ...trap/engines/engine.py.229: process: 2.58457 | load: 1.78805 [I 2022-10-28 19:08:46] ...trap/engines/engine.py.230: loss: 0.47176 [I 2022-10-28 19:08:46] ...optimizers/trijoint.py.151: total_norm: 20.433842 [S 2022-10-28 19:08:48] ...trap/engines/engine.py.129: train_epoch.epoch: 37 [S 2022-10-28 19:08:48] ...trap/engines/engine.py.129: train_epoch.loss: 0.3596805723917282 [I 2022-10-28 19:08:48] ...iterions/vlp_triplet.py.80: margin = 0.23500000000000004 [I 2022-10-28 19:08:50] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 37 [I 2022-10-28 19:08:50] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. [W 2022-10-28 19:08:53] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-28 19:08:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-28 19:08:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-28 19:08:57] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-28 19:08:59] ...trap/engines/engine.py.321: eval: epoch 37 | batch 0/1578 [I 2022-10-28 19:08:59] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:15:40 [I 2022-10-28 19:08:59] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.014519 [S 2022-10-28 19:51:01] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011220 [S 2022-10-28 19:51:01] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.011569 [S 2022-10-28 19:51:01] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.013379 [S 2022-10-28 19:51:01] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.009220 [I 2022-10-28 19:51:18] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-28 19:51:18] ...trap/engines/engine.py.470: Saving model... [W 2022-10-28 19:51:19] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-28 19:51:19] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-28 19:51:19] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-28 19:51:22] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-28 19:51:29] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-28 19:51:29] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-28 19:51:29] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-28 19:51:29] ...trap/engines/engine.py.470: Saving model... [I 2022-10-28 19:51:32] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-28 19:51:38] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-28 19:51:38] ...trap/engines/engine.py.163: Training model on trainset for epoch 38 [I 2022-10-28 19:51:38] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-28 23:01:46] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-28 23:01:46] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-28 23:01:46] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-28 23:01:50] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-28 23:01:52] ...trap/engines/engine.py.321: eval: epoch 38 | batch 0/1578 [I 2022-10-28 23:01:52] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 3:58:06 [I 2022-10-28 23:01:52] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.015731 [S 2022-10-28 23:38:27] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.012940 [S 2022-10-28 23:38:27] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.010789 [S 2022-10-28 23:38:27] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.012012 [S 2022-10-28 23:38:27] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.012998 [I 2022-10-28 23:38:45] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-28 23:38:45] ...trap/engines/engine.py.470: Saving model... [W 2022-10-28 23:38:46] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-28 23:38:46] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-28 23:38:46] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-28 23:38:49] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-28 23:38:56] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-28 23:38:57] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-28 23:38:57] ...trap/engines/engine.py.163: Training model on trainset for epoch 39 [I 2022-10-28 23:38:57] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-29 02:34:22] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-29 02:34:22] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-29 02:34:22] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-29 02:34:26] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-29 02:34:28] ...trap/engines/engine.py.321: eval: epoch 39 | batch 0/1578 [I 2022-10-29 02:34:28] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:00:47 [I 2022-10-29 02:34:28] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.006084 [S 2022-10-29 03:09:04] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.004609 [S 2022-10-29 03:09:04] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.010681 [S 2022-10-29 03:09:04] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.006400 [S 2022-10-29 03:09:04] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.007795 [I 2022-10-29 03:09:23] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-29 03:09:23] ...trap/engines/engine.py.470: Saving model... [W 2022-10-29 03:09:24] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-29 03:09:24] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-29 03:09:24] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-29 03:09:27] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-29 03:09:34] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-29 03:09:34] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-29 03:09:34] ...trap/engines/engine.py.163: Training model on trainset for epoch 40 [I 2022-10-29 03:09:35] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-29 06:04:39] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-29 06:04:39] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-29 06:04:39] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-29 06:04:44] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-29 06:04:44] ...trap/engines/engine.py.321: eval: epoch 40 | batch 0/1578 [I 2022-10-29 06:04:44] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:33:06 [I 2022-10-29 06:04:44] 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True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-29 10:05:06] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-29 10:05:08] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a103', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-29 10:05:08] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-29 10:05:08] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-29 10:05:08] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-29 10:07:14] ...tasets/recipe1m_13m.py.282: Load VCs... [I 2022-10-29 10:07:27] ...tasets/recipe1m_13m.py.295: randkw_p... 0.3 [I 2022-10-29 10:09:11] ...tasets/recipe1m_13m.py.282: Load VCs... [I 2022-10-29 10:09:11] ...tasets/recipe1m_13m.py.295: randkw_p... None [I 2022-10-29 10:09:11] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-29 10:09:12] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-29 10:09:12] ...strap/models/factory.py.21: Creating model... [I 2022-10-29 10:09:14] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-29 10:09:18] ...e_networks/networks.py.145: cuda [I 2022-10-29 10:09:19] ...networks/tfood_vicha.py.48: Load VCs encoder... [I 2022-10-29 10:09:21] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-29 10:09:21] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-29 10:09:21] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-29 10:09:21] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-29 10:09:25] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-29 10:09:25] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-29 10:09:25] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-29 10:09:34] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-29 10:09:34] ...trap/engines/engine.py.440: Loading model... [I 2022-10-29 10:09:41] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-29 10:09:49] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-29 10:09:49] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-29 10:09:49] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-29 10:09:49] ...trap/engines/engine.py.163: Training model on trainset for epoch 40 [I 2022-10-29 10:09:49] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. [I 2022-10-29 10:10:02] ...trap/engines/engine.py.224: train: epoch 40 | batch 0/7425 [I 2022-10-29 10:10:02] ...trap/engines/engine.py.228: elapsed: 0:00:13 | left: 1 day, 3:31:57 [I 2022-10-29 10:10:02] ...trap/engines/engine.py.229: process: 13.34911 | load: 8.15500 [I 2022-10-29 10:10:02] ...trap/engines/engine.py.230: loss: 0.35358 [I 2022-10-29 10:10:02] ...optimizers/trijoint.py.151: total_norm: 13.733320 [I 2022-10-29 10:10:13] ...trap/engines/engine.py.224: train: epoch 40 | batch 10/7425 [I 2022-10-29 10:10:13] ...trap/engines/engine.py.228: elapsed: 0:00:23 | left: 4:59:56 [I 2022-10-29 10:10:13] ...trap/engines/engine.py.229: process: 0.80386 | load: 0.00017 [I 2022-10-29 10:10:13] ...trap/engines/engine.py.230: loss: 0.39061 [I 2022-10-29 10:10:13] ...optimizers/trijoint.py.151: total_norm: 27.281763 [I 2022-10-29 10:10:32] ...trap/engines/engine.py.224: train: epoch 40 | batch 20/7425 [I 2022-10-29 10:10:32] ...trap/engines/engine.py.228: elapsed: 0:00:42 | left: 4:24:21 [I 2022-10-29 10:10:32] ...trap/engines/engine.py.229: process: 4.42420 | load: 3.59633 [I 2022-10-29 10:10:32] ...trap/engines/engine.py.230: loss: 0.32029 [I 2022-10-29 10:10:32] ...optimizers/trijoint.py.151: total_norm: 15.407389 [I 2022-10-29 10:10:47] ...trap/engines/engine.py.224: train: epoch 40 | batch 30/7425 [I 2022-10-29 10:10:47] ...trap/engines/engine.py.228: elapsed: 0:00:57 | left: 3:12:01 [I 2022-10-29 10:10:47] ...trap/engines/engine.py.229: process: 0.81558 | load: 0.00015 [I 2022-10-29 10:10:47] ...trap/engines/engine.py.230: loss: 0.29811 [I 2022-10-29 10:10:47] ...optimizers/trijoint.py.151: total_norm: 22.425968 [I 2022-10-29 10:11:05] ...trap/engines/engine.py.224: train: epoch 40 | batch 40/7425 [I 2022-10-29 10:11:05] ...trap/engines/engine.py.228: elapsed: 0:01:15 | left: 3:52:58 [I 2022-10-29 10:11:05] ...trap/engines/engine.py.229: process: 3.74732 | load: 2.90591 [I 2022-10-29 10:11:05] ...trap/engines/engine.py.230: loss: 0.35752 [I 2022-10-29 10:11:05] 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True [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-29 14:13:53] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-29 14:13:55] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a103', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-29 14:13:56] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-29 14:13:56] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-29 14:13:56] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-29 14:15:49] ...tasets/recipe1m_13m.py.282: Load VCs... [I 2022-10-29 14:16:02] ...tasets/recipe1m_13m.py.295: randkw_p... 0.3 [I 2022-10-29 14:17:45] ...tasets/recipe1m_13m.py.282: Load VCs... [I 2022-10-29 14:17:46] ...tasets/recipe1m_13m.py.295: randkw_p... None [I 2022-10-29 14:17:46] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-29 14:17:46] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-29 14:17:46] ...strap/models/factory.py.21: Creating model... [I 2022-10-29 14:17:51] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-29 14:17:54] ...e_networks/networks.py.145: cuda [I 2022-10-29 14:17:55] ...networks/tfood_vicha.py.48: Load VCs encoder... [I 2022-10-29 14:17:57] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-29 14:17:57] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-29 14:17:57] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-29 14:17:57] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-29 14:17:59] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-29 14:17:59] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-29 14:18:00] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-29 14:18:04] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-29 14:18:04] ...trap/engines/engine.py.440: Loading model... [I 2022-10-29 14:18:09] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-29 14:18:15] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-29 14:18:15] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-29 14:18:15] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-29 14:18:15] ...trap/engines/engine.py.163: Training model on trainset for epoch 40 [I 2022-10-29 14:18:15] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. [I 2022-10-29 14:18:27] ...trap/engines/engine.py.224: train: epoch 40 | batch 0/7425 [I 2022-10-29 14:18:27] ...trap/engines/engine.py.228: elapsed: 0:00:11 | left: 23:59:20 [I 2022-10-29 14:18:27] ...trap/engines/engine.py.229: process: 11.63109 | load: 7.06608 [I 2022-10-29 14:18:27] ...trap/engines/engine.py.230: loss: 0.35358 [I 2022-10-29 14:18:27] ...optimizers/trijoint.py.151: total_norm: 13.733320 [I 2022-10-29 14:18:36] ...trap/engines/engine.py.224: train: epoch 40 | batch 10/7425 [I 2022-10-29 14:18:36] ...trap/engines/engine.py.228: elapsed: 0:00:20 | left: 4:08:57 [I 2022-10-29 14:18:36] ...trap/engines/engine.py.229: process: 0.79685 | load: 0.00016 [I 2022-10-29 14:18:36] ...trap/engines/engine.py.230: loss: 0.39061 [I 2022-10-29 14:18:36] ...optimizers/trijoint.py.151: total_norm: 27.281763 [I 2022-10-29 14:18:51] ...trap/engines/engine.py.224: train: epoch 40 | batch 20/7425 [I 2022-10-29 14:18:51] ...trap/engines/engine.py.228: elapsed: 0:00:35 | left: 3:27:51 [I 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...optimizers/trijoint.py.151: total_norm: 12.027763 [I 2022-10-29 14:19:31] ...trap/engines/engine.py.224: train: epoch 40 | batch 50/7425 [I 2022-10-29 14:19:31] ...trap/engines/engine.py.228: elapsed: 0:01:15 | left: 2:26:13 [I 2022-10-29 14:19:31] ...trap/engines/engine.py.229: process: 0.84575 | load: 0.00021 [I 2022-10-29 14:19:31] ...trap/engines/engine.py.230: loss: 0.36803 [I 2022-10-29 14:19:31] ...optimizers/trijoint.py.151: total_norm: 14.188473 [I 2022-10-29 14:19:44] ...trap/engines/engine.py.224: train: epoch 40 | batch 60/7425 [I 2022-10-29 14:19:44] ...trap/engines/engine.py.228: elapsed: 0:01:28 | left: 2:35:31 [I 2022-10-29 14:19:44] ...trap/engines/engine.py.229: process: 1.61323 | load: 0.81032 [I 2022-10-29 14:19:44] ...trap/engines/engine.py.230: loss: 0.42074 [I 2022-10-29 14:19:44] ...optimizers/trijoint.py.151: total_norm: 15.309811 [I 2022-10-29 14:19:58] ...trap/engines/engine.py.224: train: epoch 40 | batch 70/7425 [I 2022-10-29 14:19:58] ...trap/engines/engine.py.228: elapsed: 0:01:43 | left: 2:49:12 [I 2022-10-29 14:19:58] ...trap/engines/engine.py.229: process: 0.80121 | load: 0.00016 [I 2022-10-29 14:19:58] ...trap/engines/engine.py.230: loss: 0.31776 [I 2022-10-29 14:19:58] ...optimizers/trijoint.py.151: total_norm: 14.640212 [I 2022-10-29 14:20:14] ...trap/engines/engine.py.224: train: epoch 40 | batch 80/7425 [I 2022-10-29 14:20:14] ...trap/engines/engine.py.228: elapsed: 0:01:58 | left: 3:01:29 [I 2022-10-29 14:20:14] ...trap/engines/engine.py.229: process: 2.49388 | load: 1.67553 [I 2022-10-29 14:20:14] ...trap/engines/engine.py.230: loss: 0.41901 [I 2022-10-29 14:20:14] ...optimizers/trijoint.py.151: total_norm: 19.304855 [I 2022-10-29 14:20:26] ...trap/engines/engine.py.224: train: epoch 40 | batch 90/7425 [I 2022-10-29 14:20:26] ...trap/engines/engine.py.228: elapsed: 0:02:11 | left: 2:41:02 [I 2022-10-29 14:20:26] ...trap/engines/engine.py.229: process: 0.80395 | load: 0.00016 [I 2022-10-29 14:20:26] ...trap/engines/engine.py.230: loss: 0.36663 [I 2022-10-29 14:20:26] ...optimizers/trijoint.py.151: total_norm: 28.559330 [I 2022-10-29 14:20:41] ...trap/engines/engine.py.224: train: epoch 40 | batch 100/7425 [I 2022-10-29 14:20:41] ...trap/engines/engine.py.228: elapsed: 0:02:25 | left: 2:57:29 [I 2022-10-29 14:20:41] ...trap/engines/engine.py.229: process: 0.80271 | load: 0.00016 [I 2022-10-29 14:20:41] ...trap/engines/engine.py.230: loss: 0.32017 [I 2022-10-29 14:20:41] ...optimizers/trijoint.py.151: total_norm: 14.183519 [I 2022-10-29 14:20:53] ...trap/engines/engine.py.224: train: epoch 40 | batch 110/7425 [I 2022-10-29 14:20:53] ...trap/engines/engine.py.228: elapsed: 0:02:38 | left: 2:19:06 [I 2022-10-29 14:20:53] ...trap/engines/engine.py.229: process: 0.81259 | load: 0.00015 [I 2022-10-29 14:20:53] ...trap/engines/engine.py.230: loss: 0.39515 [I 2022-10-29 14:20:53] ...optimizers/trijoint.py.151: total_norm: 15.297318 [I 2022-10-29 14:21:09] ...trap/engines/engine.py.224: train: epoch 40 | batch 120/7425 [I 2022-10-29 14:21:09] ...trap/engines/engine.py.228: elapsed: 0:02:53 | left: 2:58:08 [I 2022-10-29 14:21:09] ...trap/engines/engine.py.229: process: 0.80340 | load: 0.00014 [I 2022-10-29 14:21:09] ...trap/engines/engine.py.230: loss: 0.28146 [I 2022-10-29 14:21:09] ...optimizers/trijoint.py.151: total_norm: 11.503865 [I 2022-10-29 14:21:22] ...trap/engines/engine.py.224: train: epoch 40 | batch 130/7425 [I 2022-10-29 14:21:22] ...trap/engines/engine.py.228: elapsed: 0:03:06 | left: 2:43:59 [I 2022-10-29 14:21:22] ...trap/engines/engine.py.229: process: 1.57057 | load: 0.76426 [I 2022-10-29 14:21:22] ...trap/engines/engine.py.230: loss: 0.32969 [I 2022-10-29 14:21:22] ...optimizers/trijoint.py.151: total_norm: 14.752607 [I 2022-10-29 14:21:35] ...trap/engines/engine.py.224: train: epoch 40 | batch 140/7425 [I 2022-10-29 14:21:35] ...trap/engines/engine.py.228: elapsed: 0:03:19 | left: 2:37:50 [I 2022-10-29 14:21:35] ...trap/engines/engine.py.229: 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[I 2022-10-29 14:22:17] ...trap/engines/engine.py.224: train: epoch 40 | batch 170/7425 [I 2022-10-29 14:22:17] ...trap/engines/engine.py.228: elapsed: 0:04:02 | left: 2:26:55 [I 2022-10-29 14:22:17] ...trap/engines/engine.py.229: process: 0.79998 | load: 0.00017 [I 2022-10-29 14:22:17] ...trap/engines/engine.py.230: loss: 0.32902 [I 2022-10-29 14:22:17] ...optimizers/trijoint.py.151: total_norm: 14.032150 [I 2022-10-29 14:22:32] ...trap/engines/engine.py.224: train: epoch 40 | batch 180/7425 [I 2022-10-29 14:22:32] ...trap/engines/engine.py.228: elapsed: 0:04:17 | left: 2:53:49 [I 2022-10-29 14:22:32] ...trap/engines/engine.py.229: process: 0.80326 | load: 0.00013 [I 2022-10-29 14:22:32] ...trap/engines/engine.py.230: loss: 0.30688 [I 2022-10-29 14:22:32] ...optimizers/trijoint.py.151: total_norm: 15.007897 [I 2022-10-29 14:22:45] ...trap/engines/engine.py.224: train: epoch 40 | batch 190/7425 [I 2022-10-29 14:22:45] ...trap/engines/engine.py.228: elapsed: 0:04:29 | left: 2:35:54 [I 2022-10-29 14:22:45] ...trap/engines/engine.py.229: process: 1.33997 | load: 0.53221 [I 2022-10-29 14:22:45] ...trap/engines/engine.py.230: loss: 0.25049 [I 2022-10-29 14:22:45] ...optimizers/trijoint.py.151: total_norm: 13.588276 [I 2022-10-29 14:22:59] ...trap/engines/engine.py.224: train: epoch 40 | batch 200/7425 [I 2022-10-29 14:22:59] ...trap/engines/engine.py.228: elapsed: 0:04:44 | left: 2:41:15 [I 2022-10-29 14:22:59] ...trap/engines/engine.py.229: process: 0.79854 | load: 0.00007 [I 2022-10-29 14:22:59] ...trap/engines/engine.py.230: loss: 0.30980 [I 2022-10-29 14:22:59] ...optimizers/trijoint.py.151: total_norm: 16.571388 [I 2022-10-29 14:23:13] ...trap/engines/engine.py.224: train: epoch 40 | batch 210/7425 [I 2022-10-29 14:23:13] ...trap/engines/engine.py.228: elapsed: 0:04:58 | left: 3:00:18 [I 2022-10-29 14:23:13] ...trap/engines/engine.py.229: process: 2.87691 | load: 2.03943 [I 2022-10-29 14:23:13] ...trap/engines/engine.py.230: loss: 0.30327 [I 2022-10-29 14:23:13] ...optimizers/trijoint.py.151: total_norm: 14.269499 [I 2022-10-29 14:23:26] ...trap/engines/engine.py.224: train: epoch 40 | batch 220/7425 [I 2022-10-29 14:23:26] ...trap/engines/engine.py.228: elapsed: 0:05:11 | left: 2:46:26 [I 2022-10-29 14:23:26] ...trap/engines/engine.py.229: process: 0.80532 | load: 0.00008 [I 2022-10-29 14:23:26] ...trap/engines/engine.py.230: loss: 0.33378 [I 2022-10-29 14:23:26] ...optimizers/trijoint.py.151: total_norm: 14.090584 [I 2022-10-29 14:23:40] ...trap/engines/engine.py.224: train: epoch 40 | batch 230/7425 [I 2022-10-29 14:23:40] ...trap/engines/engine.py.228: elapsed: 0:05:25 | left: 2:28:52 [I 2022-10-29 14:23:40] ...trap/engines/engine.py.229: process: 0.80789 | load: 0.00017 [I 2022-10-29 14:23:40] ...trap/engines/engine.py.230: loss: 0.34697 [I 2022-10-29 14:23:40] ...optimizers/trijoint.py.151: total_norm: 30.142986 [I 2022-10-29 14:23:55] ...trap/engines/engine.py.224: train: epoch 40 | batch 240/7425 [I 2022-10-29 14:23:55] 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17:11:53] ...optimizers/trijoint.py.151: total_norm: 18.467440 [I 2022-10-29 17:12:10] ...trap/engines/engine.py.224: train: epoch 40 | batch 7360/7425 [I 2022-10-29 17:12:10] ...trap/engines/engine.py.228: elapsed: 2:53:55 | left: 0:01:59 [I 2022-10-29 17:12:10] ...trap/engines/engine.py.229: process: 0.80333 | load: 0.00007 [I 2022-10-29 17:12:10] ...trap/engines/engine.py.230: loss: 0.41299 [I 2022-10-29 17:12:10] ...optimizers/trijoint.py.151: total_norm: 14.301179 [I 2022-10-29 17:12:24] ...trap/engines/engine.py.224: train: epoch 40 | batch 7370/7425 [I 2022-10-29 17:12:24] ...trap/engines/engine.py.228: elapsed: 2:54:08 | left: 0:01:10 [I 2022-10-29 17:12:24] ...trap/engines/engine.py.229: process: 0.79331 | load: 0.00014 [I 2022-10-29 17:12:24] ...trap/engines/engine.py.230: loss: 0.35355 [I 2022-10-29 17:12:24] ...optimizers/trijoint.py.151: total_norm: 16.084459 [I 2022-10-29 17:12:42] ...trap/engines/engine.py.224: train: epoch 40 | batch 7380/7425 [I 2022-10-29 17:12:42] 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[W 2022-10-29 17:13:57] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-29 17:13:57] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-29 17:13:57] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-29 17:14:02] ...trap/engines/engine.py.321: eval: epoch 40 | batch 0/1578 [I 2022-10-29 17:14:02] ...trap/engines/engine.py.325: elapsed: 0:00:10 | left: 4:43:14 [I 2022-10-29 17:14:02] ...trap/engines/engine.py.326: process: 10.76934 | load: 8.76044 [I 2022-10-29 17:14:07] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-29 17:14:12] ...trap/engines/engine.py.321: eval: epoch 40 | batch 10/1578 [I 2022-10-29 17:14:12] ...trap/engines/engine.py.325: elapsed: 0:00:21 | left: 0:55:55 [I 2022-10-29 17:14:12] ...trap/engines/engine.py.326: process: 0.61792 | load: 0.00007 [I 2022-10-29 17:14:26] ...trap/engines/engine.py.321: eval: epoch 40 | batch 20/1578 [I 2022-10-29 17:14:26] ...trap/engines/engine.py.325: elapsed: 0:00:34 | left: 0:40:05 [I 2022-10-29 17:14:26] ...trap/engines/engine.py.326: process: 2.84677 | load: 2.18626 [I 2022-10-29 17:14:41] ...trap/engines/engine.py.321: eval: epoch 40 | batch 30/1578 [I 2022-10-29 17:14:41] ...trap/engines/engine.py.325: elapsed: 0:00:49 | left: 0:39:34 [I 2022-10-29 17:14:41] ...trap/engines/engine.py.326: process: 0.61235 | load: 0.00012 [I 2022-10-29 17:14:52] ...trap/engines/engine.py.321: eval: epoch 40 | batch 40/1578 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eval_epoch.metric.recall_at_1_im2recipe_std: 0.012120 [S 2022-10-29 17:49:30] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.009847 [S 2022-10-29 17:49:30] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.013138 [S 2022-10-29 17:49:30] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.007900 [S 2022-10-29 17:49:30] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.009780 [S 2022-10-29 17:49:30] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.014536 [I 2022-10-29 17:49:46] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-29 17:49:46] ...trap/engines/engine.py.470: Saving model... [W 2022-10-29 17:49:46] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-29 17:49:46] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-29 17:49:46] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-29 17:49:50] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-29 17:49:57] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-29 17:49:58] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-29 17:49:58] ...trap/engines/engine.py.163: Training model on trainset for epoch 41 [I 2022-10-29 17:49:58] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-29 20:37:07] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-29 20:37:07] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-29 20:37:07] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-29 20:37:12] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-29 20:37:12] ...trap/engines/engine.py.321: eval: epoch 41 | batch 0/1578 [I 2022-10-29 20:37:12] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:32:19 [I 2022-10-29 20:37:12] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.015047 [S 2022-10-29 21:08:41] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.015901 [S 2022-10-29 21:08:41] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.014458 [S 2022-10-29 21:08:41] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.015482 [S 2022-10-29 21:08:41] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.016056 [I 2022-10-29 21:08:56] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-29 21:08:56] ...trap/engines/engine.py.470: Saving model... [W 2022-10-29 21:08:57] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-29 21:08:57] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-29 21:08:57] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-29 21:09:01] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-29 21:09:08] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-29 21:09:09] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-29 21:09:09] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-29 21:09:09] ...trap/engines/engine.py.470: Saving model... [I 2022-10-29 21:09:12] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-29 21:09:18] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-29 21:09:18] ...trap/engines/engine.py.163: Training model on trainset for epoch 42 [I 2022-10-29 21:09:18] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-29 23:56:18] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-29 23:56:18] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-29 23:56:18] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-29 23:56:23] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-29 23:56:24] ...trap/engines/engine.py.321: eval: epoch 42 | batch 0/1578 [I 2022-10-29 23:56:24] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:47:10 [I 2022-10-29 23:56:24] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.007454 [S 2022-10-30 00:28:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.006630 [S 2022-10-30 00:28:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.012272 [S 2022-10-30 00:28:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.009080 [S 2022-10-30 00:28:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.005728 [I 2022-10-30 00:28:47] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.med_im2recipe_mean [I 2022-10-30 00:28:47] ...trap/engines/engine.py.470: Saving model... [W 2022-10-30 00:28:48] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-30 00:28:48] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-30 00:28:48] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-30 00:28:52] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-30 00:28:59] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-30 00:29:00] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-30 00:29:00] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-30 00:29:00] ...trap/engines/engine.py.470: Saving model... [I 2022-10-30 00:29:03] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-30 00:29:09] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-30 00:29:09] ...trap/engines/engine.py.163: Training model on trainset for epoch 43 [I 2022-10-30 00:29:09] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-30 02:18:21] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-30 02:18:21] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-30 02:18:21] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-30 02:18:26] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-30 02:18:27] ...trap/engines/engine.py.321: eval: epoch 43 | batch 0/1578 [I 2022-10-30 02:18:27] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:38:50 [I 2022-10-30 02:18:27] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.010689 [S 2022-10-30 02:48:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.010325 [S 2022-10-30 02:48:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.015848 [S 2022-10-30 02:48:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.011064 [S 2022-10-30 02:48:37] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.008355 [I 2022-10-30 02:48:53] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-30 02:48:53] ...trap/engines/engine.py.470: Saving model... [W 2022-10-30 02:48:53] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-30 02:48:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-30 02:48:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-30 02:48:58] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-30 02:49:04] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-30 02:49:06] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-30 02:49:06] ...trap/engines/engine.py.163: Training model on trainset for epoch 44 [I 2022-10-30 02:49:06] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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train: epoch 44 | batch 7425/7425 [I 2022-10-30 05:38:15] ...trap/engines/engine.py.228: elapsed: 2:49:08 | left: 0:00:00 [I 2022-10-30 05:38:15] ...trap/engines/engine.py.229: process: 0.78523 | load: 0.00002 [I 2022-10-30 05:38:15] ...trap/engines/engine.py.230: loss: 0.35166 [I 2022-10-30 05:38:15] ...optimizers/trijoint.py.151: total_norm: 20.448769 [S 2022-10-30 05:38:17] ...trap/engines/engine.py.129: train_epoch.epoch: 44 [S 2022-10-30 05:38:17] ...trap/engines/engine.py.129: train_epoch.loss: 0.3542908783284699 [I 2022-10-30 05:38:17] ...iterions/vlp_triplet.py.80: margin = 0.27 [I 2022-10-30 05:38:19] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 44 [I 2022-10-30 05:38:19] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. [W 2022-10-30 05:38:22] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-30 05:38:22] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-30 05:38:22] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-30 05:38:27] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-30 05:38:28] ...trap/engines/engine.py.321: eval: epoch 44 | batch 0/1578 [I 2022-10-30 05:38:28] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:54:53 [I 2022-10-30 05:38:28] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.010459 [S 2022-10-30 06:10:04] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.009135 [S 2022-10-30 06:10:04] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.020380 [S 2022-10-30 06:10:04] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.011472 [S 2022-10-30 06:10:04] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.012589 [I 2022-10-30 06:10:20] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-30 06:10:20] ...trap/engines/engine.py.470: Saving model... [W 2022-10-30 06:10:21] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-30 06:10:21] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-30 06:10:21] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-30 06:10:24] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-30 06:10:32] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-30 06:10:32] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-30 06:10:32] ...trap/engines/engine.py.163: Training model on trainset for epoch 45 [I 2022-10-30 06:10:32] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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07:35:16] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-30 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...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-30 07:35:16] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 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[I 2022-10-30 07:35:18] ...trap/datasets/factory.py.8: Creating dataset... 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...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: dir: /gpfsdswork/dataset/Recipe1M+/images_recipe1M+ [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: eval_split: val [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: freq_mismatch: 0.0 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: image_from: database [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: import: recipe1m.datasets.factory [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: kw_path: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_ingr_kw.json [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_ingr_kw.json [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_ingr_kw.json [S 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train [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: engine: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: exp: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: misc: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: model: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: network: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-30 07:35:56] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-30 07:35:58] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a101', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-30 07:35:59] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-30 07:35:59] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-30 07:35:59] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-30 07:37:41] ...tasets/recipe1m_13m.py.282: Load VCs... [I 2022-10-30 07:37:55] ...tasets/recipe1m_13m.py.295: randkw_p... 0.3 [I 2022-10-30 07:39:38] ...tasets/recipe1m_13m.py.282: Load VCs... [I 2022-10-30 07:39:39] ...tasets/recipe1m_13m.py.295: randkw_p... None [I 2022-10-30 07:39:39] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-30 07:39:39] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-30 07:39:39] ...strap/models/factory.py.21: Creating model... [I 2022-10-30 07:39:44] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-30 07:39:47] ...e_networks/networks.py.145: cuda [I 2022-10-30 07:39:49] ...networks/tfood_vicha.py.48: Load VCs encoder... [I 2022-10-30 07:39:51] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-30 07:39:51] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-30 07:39:51] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-30 07:39:51] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-30 07:39:54] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-30 07:39:54] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-30 07:39:54] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-30 07:39:57] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-30 07:39:57] ...trap/engines/engine.py.440: Loading model... [I 2022-10-30 07:40:05] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-30 07:40:16] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-30 07:40:16] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-30 07:40:16] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-30 07:40:16] ...trap/engines/engine.py.163: Training model on trainset for epoch 45 [I 2022-10-30 07:40:16] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. [I 2022-10-30 07:40:29] ...trap/engines/engine.py.224: train: epoch 45 | batch 0/7425 [I 2022-10-30 07:40:29] ...trap/engines/engine.py.228: elapsed: 0:00:13 | left: 1 day, 3:13:18 [I 2022-10-30 07:40:29] ...trap/engines/engine.py.229: process: 13.19841 | load: 8.53805 [I 2022-10-30 07:40:29] ...trap/engines/engine.py.230: loss: 0.39500 [I 2022-10-30 07:40:29] ...optimizers/trijoint.py.151: total_norm: 13.620970 [I 2022-10-30 07:40:38] ...trap/engines/engine.py.224: train: epoch 45 | batch 10/7425 [I 2022-10-30 07:40:38] ...trap/engines/engine.py.228: elapsed: 0:00:21 | left: 4:24:36 [I 2022-10-30 07:40:38] ...trap/engines/engine.py.229: process: 0.79810 | load: 0.00016 [I 2022-10-30 07:40:38] ...trap/engines/engine.py.230: loss: 0.34789 [I 2022-10-30 07:40:38] ...optimizers/trijoint.py.151: total_norm: 16.875994 [I 2022-10-30 07:40:52] ...trap/engines/engine.py.224: train: epoch 45 | batch 20/7425 [I 2022-10-30 07:40:52] ...trap/engines/engine.py.228: elapsed: 0:00:36 | left: 3:26:26 [I 2022-10-30 07:40:52] ...trap/engines/engine.py.229: process: 3.03424 | load: 2.20614 [I 2022-10-30 07:40:52] ...trap/engines/engine.py.230: loss: 0.30227 [I 2022-10-30 07:40:52] ...optimizers/trijoint.py.151: total_norm: 13.921872 [I 2022-10-30 07:41:07] ...trap/engines/engine.py.224: train: epoch 45 | batch 30/7425 [I 2022-10-30 07:41:07] ...trap/engines/engine.py.228: elapsed: 0:00:50 | left: 3:01:49 [I 2022-10-30 07:41:07] ...trap/engines/engine.py.229: process: 0.78784 | load: 0.00014 [I 2022-10-30 07:41:07] ...trap/engines/engine.py.230: loss: 0.36239 [I 2022-10-30 07:41:07] ...optimizers/trijoint.py.151: total_norm: 18.733725 [I 2022-10-30 07:41:21] ...trap/engines/engine.py.224: train: epoch 45 | batch 40/7425 [I 2022-10-30 07:41:21] ...trap/engines/engine.py.228: elapsed: 0:01:04 | left: 2:50:15 [I 2022-10-30 07:41:21] ...trap/engines/engine.py.229: process: 2.00119 | load: 1.19824 [I 2022-10-30 07:41:21] ...trap/engines/engine.py.230: loss: 0.27913 [I 2022-10-30 07:41:21] ...optimizers/trijoint.py.151: total_norm: 13.526467 [I 2022-10-30 07:41:34] ...trap/engines/engine.py.224: train: epoch 45 | batch 50/7425 [I 2022-10-30 07:41:34] ...trap/engines/engine.py.228: elapsed: 0:01:17 | left: 2:57:38 [I 2022-10-30 07:41:34] ...trap/engines/engine.py.229: process: 0.80143 | load: 0.00014 [I 2022-10-30 07:41:34] ...trap/engines/engine.py.230: loss: 0.41462 [I 2022-10-30 07:41:34] ...optimizers/trijoint.py.151: total_norm: 28.222733 [I 2022-10-30 07:41:48] ...trap/engines/engine.py.224: train: epoch 45 | batch 60/7425 [I 2022-10-30 07:41:48] ...trap/engines/engine.py.228: elapsed: 0:01:31 | left: 3:02:48 [I 2022-10-30 07:41:48] ...trap/engines/engine.py.229: process: 2.46039 | load: 1.67150 [I 2022-10-30 07:41:48] ...trap/engines/engine.py.230: loss: 0.34038 [I 2022-10-30 07:41:48] ...optimizers/trijoint.py.151: total_norm: 14.542924 [I 2022-10-30 07:42:01] ...trap/engines/engine.py.224: train: epoch 45 | batch 70/7425 [I 2022-10-30 07:42:01] 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[I 2022-10-30 10:25:53] ...trap/engines/engine.py.224: train: epoch 45 | batch 7310/7425 [I 2022-10-30 10:25:53] ...trap/engines/engine.py.228: elapsed: 2:45:36 | left: 0:02:15 [I 2022-10-30 10:25:53] ...trap/engines/engine.py.229: process: 0.80216 | load: 0.00024 [I 2022-10-30 10:25:53] ...trap/engines/engine.py.230: loss: 0.40489 [I 2022-10-30 10:25:53] ...optimizers/trijoint.py.151: total_norm: 16.695192 [I 2022-10-30 10:26:07] ...trap/engines/engine.py.224: train: epoch 45 | batch 7320/7425 [I 2022-10-30 10:26:07] ...trap/engines/engine.py.228: elapsed: 2:45:50 | left: 0:02:21 [I 2022-10-30 10:26:07] ...trap/engines/engine.py.229: process: 0.78951 | load: 0.00014 [I 2022-10-30 10:26:07] ...trap/engines/engine.py.230: loss: 0.37878 [I 2022-10-30 10:26:07] ...optimizers/trijoint.py.151: total_norm: 17.037594 [I 2022-10-30 10:26:19] ...trap/engines/engine.py.224: train: epoch 45 | batch 7330/7425 [I 2022-10-30 10:26:19] ...trap/engines/engine.py.228: elapsed: 2:46:02 | left: 0:01:50 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10:26:45] ...optimizers/trijoint.py.151: total_norm: 11.273786 [I 2022-10-30 10:27:01] ...trap/engines/engine.py.224: train: epoch 45 | batch 7360/7425 [I 2022-10-30 10:27:01] ...trap/engines/engine.py.228: elapsed: 2:46:44 | left: 0:01:34 [I 2022-10-30 10:27:01] ...trap/engines/engine.py.229: process: 0.80056 | load: 0.00007 [I 2022-10-30 10:27:01] ...trap/engines/engine.py.230: loss: 0.44321 [I 2022-10-30 10:27:01] ...optimizers/trijoint.py.151: total_norm: 15.666566 [I 2022-10-30 10:27:13] ...trap/engines/engine.py.224: train: epoch 45 | batch 7370/7425 [I 2022-10-30 10:27:13] ...trap/engines/engine.py.228: elapsed: 2:46:56 | left: 0:01:03 [I 2022-10-30 10:27:13] ...trap/engines/engine.py.229: process: 0.78664 | load: 0.00014 [I 2022-10-30 10:27:13] ...trap/engines/engine.py.230: loss: 0.30718 [I 2022-10-30 10:27:13] ...optimizers/trijoint.py.151: total_norm: 17.036205 [I 2022-10-30 10:27:27] ...trap/engines/engine.py.224: train: epoch 45 | batch 7380/7425 [I 2022-10-30 10:27:27] 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...trap/engines/engine.py.230: loss: 0.39430 [I 2022-10-30 10:27:52] ...optimizers/trijoint.py.151: total_norm: 14.586087 [I 2022-10-30 10:28:06] ...trap/engines/engine.py.224: train: epoch 45 | batch 7410/7425 [I 2022-10-30 10:28:06] ...trap/engines/engine.py.228: elapsed: 2:47:49 | left: 0:00:18 [I 2022-10-30 10:28:06] ...trap/engines/engine.py.229: process: 0.78955 | load: 0.00007 [I 2022-10-30 10:28:06] ...trap/engines/engine.py.230: loss: 0.37069 [I 2022-10-30 10:28:06] ...optimizers/trijoint.py.151: total_norm: 18.222437 [I 2022-10-30 10:28:21] ...trap/engines/engine.py.224: train: epoch 45 | batch 7420/7425 [I 2022-10-30 10:28:21] ...trap/engines/engine.py.228: elapsed: 2:48:04 | left: 0:00:07 [I 2022-10-30 10:28:21] ...trap/engines/engine.py.229: process: 0.80864 | load: 0.00009 [I 2022-10-30 10:28:21] ...trap/engines/engine.py.230: loss: 0.37187 [I 2022-10-30 10:28:21] ...optimizers/trijoint.py.151: total_norm: 17.971693 [I 2022-10-30 10:28:27] ...trap/engines/engine.py.224: train: epoch 45 | batch 7425/7425 [I 2022-10-30 10:28:27] ...trap/engines/engine.py.228: elapsed: 2:48:10 | left: 0:00:00 [I 2022-10-30 10:28:27] ...trap/engines/engine.py.229: process: 0.79326 | load: 0.00012 [I 2022-10-30 10:28:27] ...trap/engines/engine.py.230: loss: 0.31896 [I 2022-10-30 10:28:27] ...optimizers/trijoint.py.151: total_norm: 13.293089 [S 2022-10-30 10:28:28] ...trap/engines/engine.py.129: train_epoch.epoch: 45 [S 2022-10-30 10:28:28] ...trap/engines/engine.py.129: train_epoch.loss: 0.35370978555917226 [I 2022-10-30 10:28:28] ...iterions/vlp_triplet.py.80: margin = 0.275 [I 2022-10-30 10:28:31] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 45 [I 2022-10-30 10:28:31] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_mean: 2.00 [S 2022-10-30 10:57:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_mean: 0.466700 [S 2022-10-30 10:57:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.764000 [S 2022-10-30 10:57:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.843100 [S 2022-10-30 10:57:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.446200 [S 2022-10-30 10:57:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.742700 [S 2022-10-30 10:57:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.831500 [S 2022-10-30 10:57:35] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.000000 [S 2022-10-30 10:57:35] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.000000 [S 2022-10-30 10:57:35] ...strap/engines/engine.py.72: 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[W 2022-10-30 10:57:53] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-30 10:57:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-30 10:57:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-30 10:57:57] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-30 10:58:04] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-30 10:58:05] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-30 10:58:05] ...trap/engines/engine.py.163: Training model on trainset for epoch 46 [I 2022-10-30 10:58:05] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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train: epoch 46 | batch 7425/7425 [I 2022-10-30 13:48:23] ...trap/engines/engine.py.228: elapsed: 2:50:18 | left: 0:00:00 [I 2022-10-30 13:48:23] ...trap/engines/engine.py.229: process: 0.82057 | load: 0.03195 [I 2022-10-30 13:48:23] ...trap/engines/engine.py.230: loss: 0.32247 [I 2022-10-30 13:48:23] ...optimizers/trijoint.py.151: total_norm: 15.726694 [S 2022-10-30 13:48:25] ...trap/engines/engine.py.129: train_epoch.epoch: 46 [S 2022-10-30 13:48:25] ...trap/engines/engine.py.129: train_epoch.loss: 0.3534450084211818 [I 2022-10-30 13:48:25] ...iterions/vlp_triplet.py.80: margin = 0.28 [I 2022-10-30 13:48:27] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 46 [I 2022-10-30 13:48:27] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.010101 [S 2022-10-30 14:15:02] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011002 [S 2022-10-30 14:15:02] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.012800 [S 2022-10-30 14:15:02] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.015555 [S 2022-10-30 14:15:02] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.009780 [I 2022-10-30 14:15:19] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-10-30 14:15:19] ...trap/engines/engine.py.470: Saving model... [W 2022-10-30 14:15:20] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-30 14:15:20] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-30 14:15:20] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-30 14:15:24] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-30 14:15:32] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-30 14:15:32] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-30 14:15:32] ...trap/engines/engine.py.470: Saving model... [I 2022-10-30 14:15:32] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-30 14:15:35] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-30 14:15:41] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-30 14:15:41] ...trap/engines/engine.py.163: Training model on trainset for epoch 47 [I 2022-10-30 14:15:41] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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train: epoch 47 | batch 7425/7425 [I 2022-10-30 17:04:31] ...trap/engines/engine.py.228: elapsed: 2:48:50 | left: 0:00:00 [I 2022-10-30 17:04:31] ...trap/engines/engine.py.229: process: 0.79683 | load: 0.00002 [I 2022-10-30 17:04:31] ...trap/engines/engine.py.230: loss: 0.49240 [I 2022-10-30 17:04:31] ...optimizers/trijoint.py.151: total_norm: 18.823853 [S 2022-10-30 17:04:33] ...trap/engines/engine.py.129: train_epoch.epoch: 47 [S 2022-10-30 17:04:33] ...trap/engines/engine.py.129: train_epoch.loss: 0.35263212024964896 [I 2022-10-30 17:04:33] ...iterions/vlp_triplet.py.80: margin = 0.28500000000000003 [I 2022-10-30 17:04:35] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 47 [I 2022-10-30 17:04:35] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. [W 2022-10-30 17:04:38] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-30 17:04:38] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-30 17:04:38] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-30 17:04:43] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-30 17:04:44] ...trap/engines/engine.py.321: eval: epoch 47 | batch 0/1578 [I 2022-10-30 17:04:44] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:45:37 [I 2022-10-30 17:04:44] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.010179 [S 2022-10-30 17:32:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.010348 [S 2022-10-30 17:32:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.011623 [S 2022-10-30 17:32:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.010986 [S 2022-10-30 17:32:39] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.013009 [I 2022-10-30 17:32:57] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.med_im2recipe_mean [I 2022-10-30 17:32:57] ...trap/engines/engine.py.470: Saving model... [W 2022-10-30 17:32:58] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-30 17:32:58] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-30 17:32:58] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-30 17:33:02] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-30 17:33:10] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-30 17:33:10] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-30 17:33:10] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-30 17:33:10] ...trap/engines/engine.py.470: Saving model... [I 2022-10-30 17:33:13] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-30 17:33:19] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-30 17:33:19] ...trap/engines/engine.py.163: Training model on trainset for epoch 48 [I 2022-10-30 17:33:19] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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train: epoch 48 | batch 7425/7425 [I 2022-10-30 20:24:51] ...trap/engines/engine.py.228: elapsed: 2:51:32 | left: 0:00:00 [I 2022-10-30 20:24:51] ...trap/engines/engine.py.229: process: 0.78463 | load: 0.00009 [I 2022-10-30 20:24:51] ...trap/engines/engine.py.230: loss: 0.35070 [I 2022-10-30 20:24:51] ...optimizers/trijoint.py.151: total_norm: 16.521935 [S 2022-10-30 20:24:53] ...trap/engines/engine.py.129: train_epoch.epoch: 48 [S 2022-10-30 20:24:53] ...trap/engines/engine.py.129: train_epoch.loss: 0.35220782124077954 [I 2022-10-30 20:24:53] ...iterions/vlp_triplet.py.80: margin = 0.29000000000000004 [I 2022-10-30 20:24:56] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 48 [I 2022-10-30 20:24:56] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. [W 2022-10-30 20:24:59] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-30 20:24:59] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-30 20:24:59] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-30 20:25:04] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-30 20:25:05] ...trap/engines/engine.py.321: eval: epoch 48 | batch 0/1578 [I 2022-10-30 20:25:05] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:55:41 [I 2022-10-30 20:25:05] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.017303 [S 2022-10-30 20:55:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011020 [S 2022-10-30 20:55:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.013306 [S 2022-10-30 20:55:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.011243 [S 2022-10-30 20:55:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.010393 [I 2022-10-30 20:55:52] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-30 20:55:52] ...trap/engines/engine.py.470: Saving model... [W 2022-10-30 20:55:53] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-30 20:55:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-30 20:55:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-30 20:55:56] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-30 20:56:05] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-30 20:56:05] ...trap/engines/engine.py.163: Training model on trainset for epoch 49 [I 2022-10-30 20:56:05] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. 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Dataset will be sampled with "random" batch_sampler. 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.007324 [S 2022-10-31 00:21:09] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.008521 [S 2022-10-31 00:21:09] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.015635 [S 2022-10-31 00:21:09] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.006827 [S 2022-10-31 00:21:09] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.009187 [I 2022-10-31 00:21:27] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-31 00:21:27] ...trap/engines/engine.py.470: Saving model... [W 2022-10-31 00:21:28] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-31 00:21:28] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-31 00:21:28] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-31 00:21:31] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-31 00:21:40] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-31 00:21:40] ...trap/engines/engine.py.163: Training model on trainset for epoch 50 [I 2022-10-31 00:21:40] ...tasets/recipe1m_13m.py.460: Dataset will be sampled with "random" batch_sampler. [I 2022-10-31 00:21:40] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-31 00:21:49] ...trap/engines/engine.py.224: train: epoch 50 | batch 0/7425 [I 2022-10-31 00:21:49] ...trap/engines/engine.py.228: elapsed: 0:00:09 | left: 19:07:12 [I 2022-10-31 00:21:49] ...trap/engines/engine.py.229: process: 9.27037 | load: 8.43398 [I 2022-10-31 00:21:49] ...trap/engines/engine.py.230: loss: 0.31018 [I 2022-10-31 00:21:49] ...optimizers/trijoint.py.151: total_norm: 15.228596 [I 2022-10-31 00:22:02] ...trap/engines/engine.py.224: train: epoch 50 | batch 10/7425 [I 2022-10-31 00:22:02] ...trap/engines/engine.py.228: elapsed: 0:00:21 | left: 4:23:04 [I 2022-10-31 00:22:02] ...trap/engines/engine.py.229: process: 0.79160 | load: 0.00008 [I 2022-10-31 00:22:02] ...trap/engines/engine.py.230: loss: 0.35553 [I 2022-10-31 00:22:02] 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[I 2022-10-31 01:35:54] ...trap/engines/engine.py.224: train: epoch 50 | batch 3200/7425 [I 2022-10-31 01:35:54] ...trap/engines/engine.py.228: elapsed: 1:14:14 | left: 1:31:45 [I 2022-10-31 01:35:54] ...trap/engines/engine.py.229: process: 0.79620 | load: 0.00015 [I 2022-10-31 01:35:54] ...trap/engines/engine.py.230: loss: 0.31548 [I 2022-10-31 01:35:54] ...optimizers/trijoint.py.151: total_norm: 15.172147 [I 2022-10-31 11:08:31] ...ytorch/bootstrap/run.py.73: Saving environment info [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: options: [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: dataset: [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: aux_kw_path: [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: test: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_test_titles_kw.json [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: train: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_train_titles_kw.json 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...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: metric: [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-10-31 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...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: old: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-10-31 11:08:40] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-10-31 11:08:42] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a101', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-10-31 11:08:43] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-10-31 11:08:43] ...strap/engines/factory.py.9: Creating engine... [I 2022-10-31 11:08:43] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-10-31 11:10:33] ...tasets/recipe1m_13m.py.290: Load VCs... [I 2022-10-31 11:10:47] ...tasets/recipe1m_13m.py.303: randkw_p... 0.3 [I 2022-10-31 11:12:32] ...tasets/recipe1m_13m.py.290: Load VCs... [I 2022-10-31 11:12:33] ...tasets/recipe1m_13m.py.303: randkw_p... None [I 2022-10-31 11:12:33] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-10-31 11:12:33] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-10-31 11:12:33] ...strap/models/factory.py.21: Creating model... [I 2022-10-31 11:12:34] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-10-31 11:12:38] ...e_networks/networks.py.145: cuda [I 2022-10-31 11:12:39] ...networks/tfood_vicha.py.48: Load VCs encoder... [I 2022-10-31 11:12:40] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-10-31 11:12:40] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-31 11:12:40] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-10-31 11:12:40] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-10-31 11:12:43] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-31 11:12:43] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-31 11:12:43] ...otstrap/views/factory.py.8: Creating views... [I 2022-10-31 11:12:44] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-10-31 11:12:44] ...trap/engines/engine.py.440: Loading model... [I 2022-10-31 11:12:50] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-10-31 11:12:55] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-10-31 11:12:55] ...trap/engines/engine.py.453: Loading engine... [I 2022-10-31 11:12:55] ...trap/engines/engine.py.125: Launching training procedures [I 2022-10-31 11:12:55] ...trap/engines/engine.py.163: Training model on trainset for epoch 50 [I 2022-10-31 11:12:55] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. [I 2022-10-31 11:13:09] ...trap/engines/engine.py.224: train: epoch 50 | batch 0/7425 [I 2022-10-31 11:13:09] ...trap/engines/engine.py.228: elapsed: 0:00:13 | left: 1 day, 2:59:51 [I 2022-10-31 11:13:09] ...trap/engines/engine.py.229: process: 13.08975 | load: 8.49948 [I 2022-10-31 11:13:09] ...trap/engines/engine.py.230: loss: 0.31018 [I 2022-10-31 11:13:09] ...optimizers/trijoint.py.151: total_norm: 15.228596 [I 2022-10-31 11:13:18] ...trap/engines/engine.py.224: train: epoch 50 | batch 10/7425 [I 2022-10-31 11:13:18] ...trap/engines/engine.py.228: elapsed: 0:00:22 | left: 4:41:40 [I 2022-10-31 11:13:18] ...trap/engines/engine.py.229: process: 0.80220 | load: 0.00008 [I 2022-10-31 11:13:18] ...trap/engines/engine.py.230: loss: 0.35553 [I 2022-10-31 11:13:18] ...optimizers/trijoint.py.151: total_norm: 18.696877 [I 2022-10-31 11:13:34] ...trap/engines/engine.py.224: train: epoch 50 | batch 20/7425 [I 2022-10-31 11:13:34] ...trap/engines/engine.py.228: elapsed: 0:00:38 | left: 3:33:03 [I 2022-10-31 11:13:34] ...trap/engines/engine.py.229: process: 3.01816 | load: 2.16428 [I 2022-10-31 11:13:34] ...trap/engines/engine.py.230: loss: 0.36893 [I 2022-10-31 11:13:34] ...optimizers/trijoint.py.151: total_norm: 20.482363 [I 2022-10-31 11:13:47] ...trap/engines/engine.py.224: train: epoch 50 | batch 30/7425 [I 2022-10-31 11:13:47] ...trap/engines/engine.py.228: elapsed: 0:00:51 | left: 2:50:59 [I 2022-10-31 11:13:47] ...trap/engines/engine.py.229: process: 0.80813 | load: 0.00008 [I 2022-10-31 11:13:47] ...trap/engines/engine.py.230: loss: 0.30151 [I 2022-10-31 11:13:47] ...optimizers/trijoint.py.151: total_norm: 17.809778 [I 2022-10-31 11:14:04] ...trap/engines/engine.py.224: train: epoch 50 | batch 40/7425 [I 2022-10-31 11:14:04] ...trap/engines/engine.py.228: elapsed: 0:01:08 | left: 3:31:26 [I 2022-10-31 11:14:04] ...trap/engines/engine.py.229: process: 3.41547 | load: 2.56652 [I 2022-10-31 11:14:04] ...trap/engines/engine.py.230: loss: 0.32902 [I 2022-10-31 11:14:04] ...optimizers/trijoint.py.151: total_norm: 11.213674 [I 2022-10-31 11:14:18] ...trap/engines/engine.py.224: train: epoch 50 | batch 50/7425 [I 2022-10-31 11:14:18] ...trap/engines/engine.py.228: elapsed: 0:01:22 | left: 3:03:07 [I 2022-10-31 11:14:18] ...trap/engines/engine.py.229: process: 0.81397 | load: 0.00014 [I 2022-10-31 11:14:18] ...trap/engines/engine.py.230: loss: 0.42735 [I 2022-10-31 11:14:18] ...optimizers/trijoint.py.151: total_norm: 20.925133 [I 2022-10-31 11:14:33] ...trap/engines/engine.py.224: train: epoch 50 | batch 60/7425 [I 2022-10-31 11:14:33] ...trap/engines/engine.py.228: elapsed: 0:01:37 | left: 3:05:25 [I 2022-10-31 11:14:33] ...trap/engines/engine.py.229: process: 2.61767 | load: 1.78095 [I 2022-10-31 11:14:33] ...trap/engines/engine.py.230: loss: 0.41619 [I 2022-10-31 11:14:33] ...optimizers/trijoint.py.151: total_norm: 19.376930 [I 2022-10-31 11:14:47] ...trap/engines/engine.py.224: train: epoch 50 | batch 70/7425 [I 2022-10-31 11:14:47] ...trap/engines/engine.py.228: elapsed: 0:01:51 | left: 2:50:30 [I 2022-10-31 11:14:47] ...trap/engines/engine.py.229: process: 0.80024 | load: 0.00007 [I 2022-10-31 11:14:47] ...trap/engines/engine.py.230: loss: 0.31020 [I 2022-10-31 11:14:47] ...optimizers/trijoint.py.151: total_norm: 14.328290 [I 2022-10-31 11:15:02] ...trap/engines/engine.py.224: train: epoch 50 | batch 80/7425 [I 2022-10-31 11:15:02] ...trap/engines/engine.py.228: elapsed: 0:02:07 | left: 3:22:02 [I 2022-10-31 11:15:02] ...trap/engines/engine.py.229: process: 3.04695 | load: 2.23067 [I 2022-10-31 11:15:02] ...trap/engines/engine.py.230: loss: 0.31873 [I 2022-10-31 11:15:02] ...optimizers/trijoint.py.151: total_norm: 16.807442 [I 2022-10-31 11:15:17] ...trap/engines/engine.py.224: train: epoch 50 | batch 90/7425 [I 2022-10-31 11:15:17] ...trap/engines/engine.py.228: elapsed: 0:02:21 | left: 3:05:00 [I 2022-10-31 11:15:17] ...trap/engines/engine.py.229: process: 2.01610 | load: 1.20960 [I 2022-10-31 11:15:17] ...trap/engines/engine.py.230: loss: 0.40895 [I 2022-10-31 11:15:17] ...optimizers/trijoint.py.151: total_norm: 17.974648 [I 2022-10-31 11:15:31] ...trap/engines/engine.py.224: train: epoch 50 | batch 100/7425 [I 2022-10-31 11:15:31] ...trap/engines/engine.py.228: elapsed: 0:02:35 | left: 3:07:54 [I 2022-10-31 11:15:31] ...trap/engines/engine.py.229: process: 2.77188 | load: 1.93484 [I 2022-10-31 11:15:31] ...trap/engines/engine.py.230: loss: 0.35585 [I 2022-10-31 11:15:31] ...optimizers/trijoint.py.151: total_norm: 22.990110 [I 2022-10-31 11:15:45] ...trap/engines/engine.py.224: train: epoch 50 | batch 110/7425 [I 2022-10-31 11:15:45] ...trap/engines/engine.py.228: elapsed: 0:02:49 | left: 2:48:49 [I 2022-10-31 11:15:45] ...trap/engines/engine.py.229: process: 0.80389 | load: 0.00008 [I 2022-10-31 11:15:45] ...trap/engines/engine.py.230: loss: 0.38674 [I 2022-10-31 11:15:45] ...optimizers/trijoint.py.151: total_norm: 14.367065 [I 2022-10-31 11:16:01] ...trap/engines/engine.py.224: train: epoch 50 | batch 120/7425 [I 2022-10-31 11:16:01] ...trap/engines/engine.py.228: elapsed: 0:03:05 | left: 3:35:02 [I 2022-10-31 11:16:01] ...trap/engines/engine.py.229: process: 3.39106 | load: 2.55045 [I 2022-10-31 11:16:01] ...trap/engines/engine.py.230: loss: 0.32247 [I 2022-10-31 11:16:01] ...optimizers/trijoint.py.151: total_norm: 13.833717 [I 2022-10-31 11:16:16] ...trap/engines/engine.py.224: train: epoch 50 | batch 130/7425 [I 2022-10-31 11:16:16] ...trap/engines/engine.py.228: elapsed: 0:03:20 | left: 3:15:28 [I 2022-10-31 11:16:16] ...trap/engines/engine.py.229: process: 0.80937 | load: 0.00008 [I 2022-10-31 11:16:16] ...trap/engines/engine.py.230: loss: 0.39738 [I 2022-10-31 11:16:16] ...optimizers/trijoint.py.151: total_norm: 11.906488 [I 2022-10-31 11:16:35] ...trap/engines/engine.py.224: train: epoch 50 | batch 140/7425 [I 2022-10-31 11:16:35] ...trap/engines/engine.py.228: elapsed: 0:03:39 | left: 4:23:45 [I 2022-10-31 11:16:35] ...trap/engines/engine.py.229: process: 4.54820 | load: 3.71398 [I 2022-10-31 11:16:35] ...trap/engines/engine.py.230: loss: 0.31328 [I 2022-10-31 11:16:35] ...optimizers/trijoint.py.151: total_norm: 13.684250 [I 2022-10-31 11:16:57] ...trap/engines/engine.py.224: train: epoch 50 | batch 150/7425 [I 2022-10-31 11:16:57] ...trap/engines/engine.py.228: elapsed: 0:04:01 | left: 3:59:03 [I 2022-10-31 11:16:57] ...trap/engines/engine.py.229: process: 1.51470 | load: 0.70765 [I 2022-10-31 11:16:57] ...trap/engines/engine.py.230: loss: 0.29576 [I 2022-10-31 11:16:57] ...optimizers/trijoint.py.151: total_norm: 15.732280 [I 2022-10-31 11:17:11] ...trap/engines/engine.py.224: train: epoch 50 | batch 160/7425 [I 2022-10-31 11:17:11] ...trap/engines/engine.py.228: elapsed: 0:04:15 | left: 2:47:54 [I 2022-10-31 11:17:11] ...trap/engines/engine.py.229: process: 0.79998 | load: 0.00016 [I 2022-10-31 11:17:11] ...trap/engines/engine.py.230: loss: 0.35795 [I 2022-10-31 11:17:11] ...optimizers/trijoint.py.151: total_norm: 13.746000 [I 2022-10-31 11:17:28] ...trap/engines/engine.py.224: train: epoch 50 | batch 170/7425 [I 2022-10-31 11:17:28] ...trap/engines/engine.py.228: elapsed: 0:04:32 | left: 3:14:33 [I 2022-10-31 11:17:28] ...trap/engines/engine.py.229: process: 0.81827 | load: 0.00016 [I 2022-10-31 11:17:28] ...trap/engines/engine.py.230: loss: 0.35540 [I 2022-10-31 11:17:28] ...optimizers/trijoint.py.151: total_norm: 15.355440 [I 2022-10-31 11:17:44] ...trap/engines/engine.py.224: train: epoch 50 | batch 180/7425 [I 2022-10-31 11:17:44] ...trap/engines/engine.py.228: elapsed: 0:04:48 | left: 2:51:08 [I 2022-10-31 11:17:44] ...trap/engines/engine.py.229: process: 0.81339 | load: 0.00015 [I 2022-10-31 11:17:44] ...trap/engines/engine.py.230: loss: 0.34104 [I 2022-10-31 11:17:44] ...optimizers/trijoint.py.151: total_norm: 14.050769 [I 2022-10-31 11:18:01] ...trap/engines/engine.py.224: train: epoch 50 | batch 190/7425 [I 2022-10-31 11:18:01] ...trap/engines/engine.py.228: elapsed: 0:05:05 | left: 3:03:38 [I 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...trap/engines/engine.py.230: loss: 0.36715 [I 2022-10-31 14:07:36] ...optimizers/trijoint.py.151: total_norm: 19.490191 [I 2022-10-31 14:07:52] ...trap/engines/engine.py.224: train: epoch 50 | batch 7240/7425 [I 2022-10-31 14:07:52] ...trap/engines/engine.py.228: elapsed: 2:54:56 | left: 0:04:17 [I 2022-10-31 14:07:52] ...trap/engines/engine.py.229: process: 0.81367 | load: 0.00007 [I 2022-10-31 14:07:52] ...trap/engines/engine.py.230: loss: 0.36659 [I 2022-10-31 14:07:52] ...optimizers/trijoint.py.151: total_norm: 14.049526 [I 2022-10-31 14:08:03] ...trap/engines/engine.py.224: train: epoch 50 | batch 7250/7425 [I 2022-10-31 14:08:03] ...trap/engines/engine.py.228: elapsed: 2:55:07 | left: 0:03:14 [I 2022-10-31 14:08:03] ...trap/engines/engine.py.229: process: 0.80385 | load: 0.00014 [I 2022-10-31 14:08:03] ...trap/engines/engine.py.230: loss: 0.33433 [I 2022-10-31 14:08:03] ...optimizers/trijoint.py.151: total_norm: 14.445456 [I 2022-10-31 14:08:19] ...trap/engines/engine.py.224: 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[I 2022-10-31 14:09:27] ...trap/engines/engine.py.224: train: epoch 50 | batch 7310/7425 [I 2022-10-31 14:09:27] ...trap/engines/engine.py.228: elapsed: 2:56:31 | left: 0:02:30 [I 2022-10-31 14:09:27] ...trap/engines/engine.py.229: process: 0.82332 | load: 0.00015 [I 2022-10-31 14:09:27] ...trap/engines/engine.py.230: loss: 0.32961 [I 2022-10-31 14:09:27] ...optimizers/trijoint.py.151: total_norm: 14.900625 [I 2022-10-31 14:09:43] ...trap/engines/engine.py.224: train: epoch 50 | batch 7320/7425 [I 2022-10-31 14:09:43] ...trap/engines/engine.py.228: elapsed: 2:56:47 | left: 0:02:26 [I 2022-10-31 14:09:43] ...trap/engines/engine.py.229: process: 0.81486 | load: 0.00016 [I 2022-10-31 14:09:43] ...trap/engines/engine.py.230: loss: 0.39238 [I 2022-10-31 14:09:43] ...optimizers/trijoint.py.151: total_norm: 22.969685 [I 2022-10-31 14:09:57] ...trap/engines/engine.py.224: train: epoch 50 | batch 7330/7425 [I 2022-10-31 14:09:57] ...trap/engines/engine.py.228: elapsed: 2:57:01 | left: 0:02:11 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14:10:25] ...optimizers/trijoint.py.151: total_norm: 14.850486 [I 2022-10-31 14:10:43] ...trap/engines/engine.py.224: train: epoch 50 | batch 7360/7425 [I 2022-10-31 14:10:43] ...trap/engines/engine.py.228: elapsed: 2:57:47 | left: 0:01:54 [I 2022-10-31 14:10:43] ...trap/engines/engine.py.229: process: 3.11904 | load: 2.28045 [I 2022-10-31 14:10:43] ...trap/engines/engine.py.230: loss: 0.44664 [I 2022-10-31 14:10:43] ...optimizers/trijoint.py.151: total_norm: 18.868046 [I 2022-10-31 14:10:56] ...trap/engines/engine.py.224: train: epoch 50 | batch 7370/7425 [I 2022-10-31 14:10:56] ...trap/engines/engine.py.228: elapsed: 2:58:00 | left: 0:01:14 [I 2022-10-31 14:10:56] ...trap/engines/engine.py.229: process: 0.81513 | load: 0.00015 [I 2022-10-31 14:10:56] ...trap/engines/engine.py.230: loss: 0.24831 [I 2022-10-31 14:10:56] ...optimizers/trijoint.py.151: total_norm: 9.422346 [I 2022-10-31 14:11:11] ...trap/engines/engine.py.224: train: epoch 50 | batch 7380/7425 [I 2022-10-31 14:11:11] 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...trap/engines/engine.py.230: loss: 0.29748 [I 2022-10-31 14:11:42] ...optimizers/trijoint.py.151: total_norm: 15.798657 [I 2022-10-31 14:11:55] ...trap/engines/engine.py.224: train: epoch 50 | batch 7410/7425 [I 2022-10-31 14:11:55] ...trap/engines/engine.py.228: elapsed: 2:58:59 | left: 0:00:20 [I 2022-10-31 14:11:55] ...trap/engines/engine.py.229: process: 0.80989 | load: 0.00014 [I 2022-10-31 14:11:55] ...trap/engines/engine.py.230: loss: 0.46816 [I 2022-10-31 14:11:55] ...optimizers/trijoint.py.151: total_norm: 22.957674 [I 2022-10-31 14:12:14] ...trap/engines/engine.py.224: train: epoch 50 | batch 7420/7425 [I 2022-10-31 14:12:14] ...trap/engines/engine.py.228: elapsed: 2:59:18 | left: 0:00:08 [I 2022-10-31 14:12:14] ...trap/engines/engine.py.229: process: 3.35862 | load: 2.52864 [I 2022-10-31 14:12:14] ...trap/engines/engine.py.230: loss: 0.31972 [I 2022-10-31 14:12:14] ...optimizers/trijoint.py.151: total_norm: 14.628901 [I 2022-10-31 14:12:20] ...trap/engines/engine.py.224: train: epoch 50 | batch 7425/7425 [I 2022-10-31 14:12:20] ...trap/engines/engine.py.228: elapsed: 2:59:24 | left: 0:00:00 [I 2022-10-31 14:12:20] ...trap/engines/engine.py.229: process: 0.81140 | load: 0.00003 [I 2022-10-31 14:12:20] ...trap/engines/engine.py.230: loss: 0.39506 [I 2022-10-31 14:12:20] ...optimizers/trijoint.py.151: total_norm: 19.280933 [S 2022-10-31 14:12:22] ...trap/engines/engine.py.129: train_epoch.epoch: 50 [S 2022-10-31 14:12:22] ...trap/engines/engine.py.129: train_epoch.loss: 0.3515675136507954 [I 2022-10-31 14:12:22] ...iterions/vlp_triplet.py.80: margin = 0.3 [I 2022-10-31 14:12:24] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 50 [I 2022-10-31 14:12:24] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. [W 2022-10-31 14:12:28] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-31 14:12:28] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-31 14:12:28] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-31 14:12:33] ...trap/engines/engine.py.321: eval: epoch 50 | batch 0/1578 [I 2022-10-31 14:12:33] ...trap/engines/engine.py.325: elapsed: 0:00:08 | left: 3:56:04 [I 2022-10-31 14:12:33] ...trap/engines/engine.py.326: process: 8.97605 | load: 8.15863 [I 2022-10-31 14:12:34] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-31 14:12:45] ...trap/engines/engine.py.321: eval: epoch 50 | batch 10/1578 [I 2022-10-31 14:12:45] ...trap/engines/engine.py.325: elapsed: 0:00:20 | left: 0:53:16 [I 2022-10-31 14:12:45] ...trap/engines/engine.py.326: process: 0.40260 | load: 0.00008 [I 2022-10-31 14:12:59] ...trap/engines/engine.py.321: eval: epoch 50 | batch 20/1578 [I 2022-10-31 14:12:59] ...trap/engines/engine.py.325: elapsed: 0:00:34 | left: 0:37:26 [I 2022-10-31 14:12:59] ...trap/engines/engine.py.326: process: 2.73176 | load: 2.28850 [I 2022-10-31 14:13:12] ...trap/engines/engine.py.321: eval: epoch 50 | batch 30/1578 [I 2022-10-31 14:13:12] ...trap/engines/engine.py.325: elapsed: 0:00:47 | left: 0:35:48 [I 2022-10-31 14:13:12] ...trap/engines/engine.py.326: process: 0.44866 | load: 0.00016 [I 2022-10-31 14:13:26] ...trap/engines/engine.py.321: eval: epoch 50 | batch 40/1578 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eval_epoch.metric.recall_at_1_im2recipe_std: 0.012048 [S 2022-10-31 14:41:24] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.012223 [S 2022-10-31 14:41:24] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.008549 [S 2022-10-31 14:41:24] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.016243 [S 2022-10-31 14:41:24] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.010319 [S 2022-10-31 14:41:24] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.008249 [I 2022-10-31 14:41:40] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-31 14:41:40] ...trap/engines/engine.py.470: Saving model... [W 2022-10-31 14:41:41] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-31 14:41:41] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-31 14:41:41] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-31 14:41:45] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-31 14:41:53] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-31 14:41:55] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-31 14:41:55] ...trap/engines/engine.py.163: Training model on trainset for epoch 51 [I 2022-10-31 14:41:55] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. 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[W 2022-10-31 17:43:33] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-31 17:43:33] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-31 17:43:33] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-31 17:43:39] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-31 17:43:40] ...trap/engines/engine.py.321: eval: epoch 51 | batch 0/1578 [I 2022-10-31 17:43:40] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 3:59:51 [I 2022-10-31 17:43:40] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.017141 [S 2022-10-31 18:14:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.013691 [S 2022-10-31 18:14:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.017176 [S 2022-10-31 18:14:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.018170 [S 2022-10-31 18:14:55] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.016837 [I 2022-10-31 18:15:13] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-31 18:15:13] ...trap/engines/engine.py.470: Saving model... [W 2022-10-31 18:15:13] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-31 18:15:13] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-31 18:15:14] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-31 18:15:17] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-31 18:15:26] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-31 18:15:26] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-31 18:15:26] ...trap/engines/engine.py.163: Training model on trainset for epoch 52 [I 2022-10-31 18:15:26] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. 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train: epoch 52 | batch 7425/7425 [I 2022-10-31 21:20:03] ...trap/engines/engine.py.228: elapsed: 3:04:36 | left: 0:00:00 [I 2022-10-31 21:20:03] ...trap/engines/engine.py.229: process: 0.81149 | load: 0.00003 [I 2022-10-31 21:20:03] ...trap/engines/engine.py.230: loss: 0.26941 [I 2022-10-31 21:20:03] ...optimizers/trijoint.py.151: total_norm: 11.685964 [S 2022-10-31 21:20:05] ...trap/engines/engine.py.129: train_epoch.epoch: 52 [S 2022-10-31 21:20:05] ...trap/engines/engine.py.129: train_epoch.loss: 0.3504395579416059 [I 2022-10-31 21:20:05] ...iterions/vlp_triplet.py.80: margin = 0.3 [I 2022-10-31 21:20:07] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 52 [I 2022-10-31 21:20:07] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. [W 2022-10-31 21:20:10] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-31 21:20:10] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-31 21:20:10] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-31 21:20:16] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-31 21:20:17] ...trap/engines/engine.py.321: eval: epoch 52 | batch 0/1578 [I 2022-10-31 21:20:17] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:11:22 [I 2022-10-31 21:20:17] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.014506 [S 2022-10-31 21:52:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.011234 [S 2022-10-31 21:52:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.016193 [S 2022-10-31 21:52:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.015723 [S 2022-10-31 21:52:32] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.011365 [I 2022-10-31 21:52:50] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-10-31 21:52:50] ...trap/engines/engine.py.470: Saving model... [W 2022-10-31 21:52:51] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-10-31 21:52:51] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-10-31 21:52:51] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-10-31 21:52:55] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-10-31 21:53:04] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-10-31 21:53:04] ...trap/engines/engine.py.478: Saving engine... [I 2022-10-31 21:53:04] ...trap/engines/engine.py.163: Training model on trainset for epoch 53 [I 2022-10-31 21:53:04] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. 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train: epoch 53 | batch 7425/7425 [I 2022-11-01 01:01:03] ...trap/engines/engine.py.228: elapsed: 3:07:59 | left: 0:00:00 [I 2022-11-01 01:01:03] ...trap/engines/engine.py.229: process: 0.80698 | load: 0.00010 [I 2022-11-01 01:01:03] ...trap/engines/engine.py.230: loss: 0.39937 [I 2022-11-01 01:01:03] ...optimizers/trijoint.py.151: total_norm: 18.798769 [S 2022-11-01 01:01:05] ...trap/engines/engine.py.129: train_epoch.epoch: 53 [S 2022-11-01 01:01:05] ...trap/engines/engine.py.129: train_epoch.loss: 0.347592214665707 [I 2022-11-01 01:01:05] ...iterions/vlp_triplet.py.80: margin = 0.3 [I 2022-11-01 01:01:08] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 53 [I 2022-11-01 01:01:08] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. [W 2022-11-01 01:01:11] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-11-01 01:01:11] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-11-01 01:01:11] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-11-01 01:01:17] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-11-01 01:01:17] ...trap/engines/engine.py.321: eval: epoch 53 | batch 0/1578 [I 2022-11-01 01:01:17] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:03:11 [I 2022-11-01 01:01:17] 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.013025 [S 2022-11-01 01:33:16] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.010429 [S 2022-11-01 01:33:16] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.023037 [S 2022-11-01 01:33:16] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.013763 [S 2022-11-01 01:33:16] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.008942 [I 2022-11-01 01:33:33] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-11-01 01:33:33] ...trap/engines/engine.py.470: Saving model... [W 2022-11-01 01:33:34] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-11-01 01:33:34] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-11-01 01:33:34] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-11-01 01:33:38] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-11-01 01:33:47] ...trap/engines/engine.py.478: Saving engine... [I 2022-11-01 01:33:47] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-11-01 01:33:47] ...trap/engines/engine.py.470: Saving model... [I 2022-11-01 01:33:47] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-11-01 01:33:50] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-11-01 01:33:56] ...trap/engines/engine.py.478: Saving engine... [I 2022-11-01 01:33:56] ...trap/engines/engine.py.163: Training model on trainset for epoch 54 [I 2022-11-01 01:33:56] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. 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[I 2022-11-01 04:39:02] ...trap/engines/engine.py.224: train: epoch 54 | batch 7310/7425 [I 2022-11-01 04:39:02] ...trap/engines/engine.py.228: elapsed: 3:05:05 | left: 0:04:09 [I 2022-11-01 04:39:02] ...trap/engines/engine.py.229: process: 5.60104 | load: 4.76743 [I 2022-11-01 04:39:02] ...trap/engines/engine.py.230: loss: 0.32267 [I 2022-11-01 04:39:02] ...optimizers/trijoint.py.151: total_norm: 18.047737 [I 2022-11-01 04:39:17] ...trap/engines/engine.py.224: train: epoch 54 | batch 7320/7425 [I 2022-11-01 04:39:17] ...trap/engines/engine.py.228: elapsed: 3:05:21 | left: 0:02:47 [I 2022-11-01 04:39:17] ...trap/engines/engine.py.229: process: 0.80734 | load: 0.00014 [I 2022-11-01 04:39:17] ...trap/engines/engine.py.230: loss: 0.37960 [I 2022-11-01 04:39:17] ...optimizers/trijoint.py.151: total_norm: 17.943033 [I 2022-11-01 04:39:33] ...trap/engines/engine.py.224: train: epoch 54 | batch 7330/7425 [I 2022-11-01 04:39:33] ...trap/engines/engine.py.228: elapsed: 3:05:36 | left: 0:02:43 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train: epoch 54 | batch 7425/7425 [I 2022-11-01 04:41:58] ...trap/engines/engine.py.228: elapsed: 3:08:02 | left: 0:00:00 [I 2022-11-01 04:41:58] ...trap/engines/engine.py.229: process: 0.80751 | load: 0.00010 [I 2022-11-01 04:41:58] ...trap/engines/engine.py.230: loss: 0.40235 [I 2022-11-01 04:41:58] ...optimizers/trijoint.py.151: total_norm: 22.340664 [S 2022-11-01 04:42:00] ...trap/engines/engine.py.129: train_epoch.epoch: 54 [S 2022-11-01 04:42:00] ...trap/engines/engine.py.129: train_epoch.loss: 0.34595435342272113 [I 2022-11-01 04:42:00] ...iterions/vlp_triplet.py.80: margin = 0.3 [I 2022-11-01 04:42:03] ...trap/engines/engine.py.268: Evaluating model on valset for epoch 54 [I 2022-11-01 04:42:03] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. [W 2022-11-01 04:42:06] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-11-01 04:42:06] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-11-01 04:42:06] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-11-01 04:42:12] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-11-01 04:42:12] ...trap/engines/engine.py.321: eval: epoch 54 | batch 0/1578 [I 2022-11-01 04:42:12] ...trap/engines/engine.py.325: elapsed: 0:00:09 | left: 4:09:34 [I 2022-11-01 04:42:12] 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...ytorch/bootstrap/run.py.75: orig_ids_eval: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: path_ids: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/original_ids.json [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: engine: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: exp: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: misc: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: model: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: metric: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: network: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: old: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-11-01 07:09:48] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-11-01 07:09:50] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a101', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-11-01 07:09:51] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-11-01 07:09:51] ...strap/engines/factory.py.9: Creating engine... [I 2022-11-01 07:09:51] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-11-01 07:11:46] ...tasets/recipe1m_13m.py.290: Load VCs... [I 2022-11-01 07:11:59] ...tasets/recipe1m_13m.py.303: randkw_p... 0.3 [I 2022-11-01 07:13:44] ...tasets/recipe1m_13m.py.290: Load VCs... [I 2022-11-01 07:13:44] ...tasets/recipe1m_13m.py.303: randkw_p... None [I 2022-11-01 07:13:45] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-11-01 07:13:45] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-11-01 07:13:45] ...strap/models/factory.py.21: Creating model... [I 2022-11-01 07:13:50] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-11-01 07:13:54] ...e_networks/networks.py.145: cuda [I 2022-11-01 07:13:55] ...networks/tfood_vicha.py.48: Load VCs encoder... [I 2022-11-01 07:13:56] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-11-01 07:13:57] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-11-01 07:13:57] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-11-01 07:13:57] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-11-01 07:13:59] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-11-01 07:13:59] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-11-01 07:13:59] ...otstrap/views/factory.py.8: Creating views... [I 2022-11-01 07:14:05] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-11-01 07:14:05] ...trap/engines/engine.py.440: Loading model... [I 2022-11-01 07:14:11] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-11-01 07:14:18] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-11-01 07:14:18] ...trap/engines/engine.py.453: Loading engine... [I 2022-11-01 07:14:18] ...trap/engines/engine.py.125: Launching training procedures [I 2022-11-01 07:14:18] ...trap/engines/engine.py.163: Training model on trainset for epoch 54 [I 2022-11-01 07:14:18] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. 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[W 2022-11-01 10:24:43] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-11-01 10:24:43] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-11-01 10:24:43] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-11-01 10:24:49] ...trap/engines/engine.py.321: eval: epoch 54 | batch 0/1578 [I 2022-11-01 10:24:49] ...trap/engines/engine.py.325: elapsed: 0:00:13 | left: 5:42:44 [I 2022-11-01 10:24:49] ...trap/engines/engine.py.326: process: 13.03212 | load: 10.64317 [I 2022-11-01 10:24:55] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-11-01 10:25:00] ...trap/engines/engine.py.321: eval: epoch 54 | batch 10/1578 [I 2022-11-01 10:25:00] ...trap/engines/engine.py.325: elapsed: 0:00:24 | left: 1:03:59 [I 2022-11-01 10:25:00] ...trap/engines/engine.py.326: process: 0.59063 | load: 0.00014 [I 2022-11-01 10:25:18] ...trap/engines/engine.py.321: eval: epoch 54 | batch 20/1578 [I 2022-11-01 10:25:18] ...trap/engines/engine.py.325: elapsed: 0:00:41 | left: 0:52:33 [I 2022-11-01 10:25:18] ...trap/engines/engine.py.326: process: 4.49338 | load: 3.85279 [I 2022-11-01 10:25:32] ...trap/engines/engine.py.321: eval: epoch 54 | batch 30/1578 [I 2022-11-01 10:25:32] ...trap/engines/engine.py.325: elapsed: 0:00:56 | left: 0:39:23 [I 2022-11-01 10:25:32] ...trap/engines/engine.py.326: process: 0.59160 | load: 0.00007 [I 2022-11-01 10:25:50] ...trap/engines/engine.py.321: eval: epoch 54 | batch 40/1578 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[W 2022-11-01 11:05:19] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-11-01 11:05:20] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-11-01 11:05:20] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-11-01 11:05:23] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-11-01 11:05:32] ...trap/engines/engine.py.478: Saving engine... [I 2022-11-01 11:05:32] ...trap/engines/engine.py.163: Training model on trainset for epoch 55 [I 2022-11-01 11:05:32] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.012225 [S 2022-11-01 14:52:58] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.010773 [S 2022-11-01 14:52:58] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.016870 [S 2022-11-01 14:52:58] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.008414 [S 2022-11-01 14:52:58] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.012589 [I 2022-11-01 14:53:15] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-11-01 14:53:15] ...trap/engines/engine.py.470: Saving model... [W 2022-11-01 14:53:16] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-11-01 14:53:16] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-11-01 14:53:16] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-11-01 14:53:20] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-11-01 14:53:29] ...trap/engines/engine.py.478: Saving engine... [I 2022-11-01 14:53:29] ...trap/engines/engine.py.163: Training model on trainset for epoch 56 [I 2022-11-01 14:53:29] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.014135 [S 2022-11-01 18:51:31] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.013409 [S 2022-11-01 18:51:31] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.009519 [S 2022-11-01 18:51:31] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.014094 [S 2022-11-01 18:51:31] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.016183 [I 2022-11-01 18:51:48] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-11-01 18:51:48] ...trap/engines/engine.py.470: Saving model... [W 2022-11-01 18:51:49] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-11-01 18:51:49] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-11-01 18:51:49] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-11-01 18:51:53] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-11-01 18:52:01] ...trap/engines/engine.py.478: Saving engine... [I 2022-11-01 18:52:01] ...trap/engines/engine.py.163: Training model on trainset for epoch 57 [I 2022-11-01 18:52:02] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. 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sampled with "random" batch_sampler. 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[W 2022-11-01 22:38:50] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-11-01 22:38:50] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-11-01 22:38:50] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-11-01 22:38:54] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-11-01 22:39:02] ...trap/engines/engine.py.478: Saving engine... [I 2022-11-01 22:39:02] ...trap/engines/engine.py.163: Training model on trainset for epoch 58 [I 2022-11-01 22:39:02] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. 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val: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/clip_da/layer1_recipe1m_13m_orig_val_ingr_kw.json [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: name: recipe1m_13m [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: nb_classes: 1048 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: nb_threads: 4 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: orig_ids_eval: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: path_ids: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/original_ids.json [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: path_image_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/recipe1m_13m/layer2+.json [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: path_text_json: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/tokenized_layer1.json [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: randkw_p: 0.3 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: randkw_p_aux: 0.5 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: tokenized_raw_text: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: train_split: train [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: use_vcs: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: vocab_path: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: engine: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: debug: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: name: logger [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: nb_epochs: 60 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: print_freq: 10 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: saving_criteria: ['eval_epoch.metric.med_im2recipe_mean:min', 'eval_epoch.metric.recall_at_1_im2recipe_mean:max'] [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: exp: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: dir: /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: resume: last [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: misc: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cuda: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: data_parrallel: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: logs_name: None [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: overrite: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: seed: 1338 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: model: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: criterion: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: tri_cross_encoder: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: itm_loss_weight: 1 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: keep_background: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: retrieval_strategy: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: aggregation: valid [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: margin: 0.05 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: margin_params: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: increment: 0.005 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: increment_margin: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: max_margin: 0.3 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: name: vlp_triplet [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: nb_samples: 9999 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: sampling: max_negative [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: substrategy: ['IRR', 'RII'] [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: substrategy_weights: [1.0, 1.0] [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: import: recipe1m.models.factory [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: metric: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: k_test: 10 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: nb_bags: 10 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: nb_matchs_per_bag: 1000 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: retrieval_dir: /gpfsscratch/rech/dyf/ugz83ue/tmp/recipe1m [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: trijoint: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: network: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: activations: ['tanh', 'normalize'] [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: aux_kwords: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: aux_kwords_encoder: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: avg_concat: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: bert_config: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/models/networks/recipe_networks/config_bert_albef.json [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cat_pos: 0 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: class_attention_fus: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cls_token_fus: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cross_decoder_image: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cross_decoder_recipe: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cross_encoder: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cross_encoder_params: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: class_attention: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cls_token: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cross_attention: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cross_decoder: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: double_decoder: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: get_tokens: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: load_backbones: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: n_layers: 4 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: query_img: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: cross_transformer: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: dim_emb: 1024 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: dim_image_out: 2048 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: dim_ingr_out: 300 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: dim_instr_in: 1024 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: dim_instr_out: 1024 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: freeze_im: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: freeze_rec: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: get_tokens: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: get_tokens_cross_decoder_recipe: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: hidden_size: 512 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: image_backbone_name: clip [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: image_res: 224 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: keep_embedding: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: kwords_same_level: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: last_cat_aux: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: n_heads: 4 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: n_heads_cross: 4 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: n_heads_cross_image: 4 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: n_heads_single: 4 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: n_layers: 2 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: n_layers_cross: 2 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: n_layers_cross_image: 1 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: n_layers_single: 2 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: name: trijoint [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: num_hidden_layers_kw: 2 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: old: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: path_ingrs: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab.pkl [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: path_vocab: /gpfsscratch/rech/dyf/ugz83ue/data/recipe1m/text/vocab_all.txt [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: recipe_encoder: tfoodvicha-transformer [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: text_encoder: bert-base-uncased [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: vision_width: 768 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: vit_all_tokens: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: with_ingrs: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: with_instrs: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: with_titles: True [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: with_classif: False [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: optimizer: [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: batch_size_factor: None [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: clip_grad: 8.0 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: import: recipe1m.optimizers.factory [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: lr: 1e-05 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: lr_img: 1e-06 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: name: trijoint_fixed_fine_tune [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: switch_epoch: 5 [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: path_opts: /linkhome/rech/genisi01/ugz83ue/tfood/recipe1m/options/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m.yaml [S 2022-11-02 01:10:14] ...ytorch/bootstrap/run.py.75: view: ['logs:train_epoch.loss', 'logs:train_epoch.bad_pairs', 'logs:eval_epoch.metric.med_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_1_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_5_im2recipe_mean', 'logs:eval_epoch.metric.recall_at_10_im2recipe_mean', 'logs:eval_epoch.metric.med_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_1_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_5_recipe2im_mean', 'logs:eval_epoch.metric.recall_at_10_recipe2im_mean', 'logs:optimizer.is_optimizer_recipe&image', 'logs:optimizer.total_norm'] [I 2022-11-02 01:10:17] ...ytorch/bootstrap/run.py.76: posix.uname_result(sysname='Linux', nodename='jean-zay-a101', release='4.18.0-305.57.1.el8_4.x86_64', version='#1 SMP Tue Jul 5 17:55:55 EDT 2022', machine='x86_64') [I 2022-11-02 01:10:17] ...ytorch/bootstrap/run.py.80: Available GPUs: [0, 1] [I 2022-11-02 01:10:17] ...strap/engines/factory.py.9: Creating engine... [I 2022-11-02 01:10:17] ...trap/datasets/factory.py.8: Creating dataset... [I 2022-11-02 01:12:05] ...tasets/recipe1m_13m.py.290: Load VCs... [I 2022-11-02 01:12:19] ...tasets/recipe1m_13m.py.303: randkw_p... 0.3 [I 2022-11-02 01:14:02] ...tasets/recipe1m_13m.py.290: Load VCs... [I 2022-11-02 01:14:03] ...tasets/recipe1m_13m.py.303: randkw_p... None [I 2022-11-02 01:14:03] ...rap/datasets/factory.py.18: Training will take place on trainset (712907 items) [I 2022-11-02 01:14:03] ...rap/datasets/factory.py.21: Evaluation will take place on valset (151637 items) [I 2022-11-02 01:14:03] ...strap/models/factory.py.21: Creating model... [I 2022-11-02 01:14:07] ...e_networks/networks.py.203: Loading CLIP Visual model... [I 2022-11-02 01:14:11] ...e_networks/networks.py.145: cuda [I 2022-11-02 01:14:12] ...networks/tfood_vicha.py.48: Load VCs encoder... [I 2022-11-02 01:14:13] .../criterions/trijoint.py.30: ignore_index=0 [I 2022-11-02 01:14:13] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-11-02 01:14:13] ...els/metrics/trijoint.py.46: self.save_ids False [I 2022-11-02 01:14:13] ...strap/models/factory.py.44: Enabling CUDA mode... [I 2022-11-02 01:14:16] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-11-02 01:14:16] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-11-02 01:14:16] ...otstrap/views/factory.py.8: Creating views... [I 2022-11-02 01:14:21] ...strap/engines/engine.py.98: Loading last checkpoint [I 2022-11-02 01:14:21] ...trap/engines/engine.py.440: Loading model... [I 2022-11-02 01:14:26] ...trap/engines/engine.py.446: Loading optimizer... [I 2022-11-02 01:14:32] ...etworks/tfood_vicha.py.183: training aux kw modules [I 2022-11-02 01:14:32] ...trap/engines/engine.py.453: Loading engine... [I 2022-11-02 01:14:32] ...trap/engines/engine.py.125: Launching training procedures [I 2022-11-02 01:14:32] ...trap/engines/engine.py.163: Training model on trainset for epoch 58 [I 2022-11-02 01:14:32] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. 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...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.016107 [S 2022-11-02 05:09:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.012731 [S 2022-11-02 05:09:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.012151 [S 2022-11-02 05:09:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.015557 [S 2022-11-02 05:09:52] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.012264 [I 2022-11-02 05:10:08] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-11-02 05:10:08] ...trap/engines/engine.py.470: Saving model... [W 2022-11-02 05:10:09] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-11-02 05:10:09] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-11-02 05:10:09] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-11-02 05:10:13] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-11-02 05:10:21] ...trap/engines/engine.py.478: Saving engine... [I 2022-11-02 05:10:21] ...trap/engines/engine.py.163: Training model on trainset for epoch 59 [I 2022-11-02 05:10:22] ...tasets/recipe1m_13m.py.468: Dataset will be sampled with "random" batch_sampler. 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sampled with "random" batch_sampler. 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[I 2022-11-02 09:01:34] ...trap/engines/engine.py.326: process: 0.29345 | load: 0.00014 [I 2022-11-02 09:01:46] ...trap/engines/engine.py.321: eval: epoch 59 | batch 1560/1578 [I 2022-11-02 09:01:46] ...trap/engines/engine.py.325: elapsed: 0:34:18 | left: 0:00:18 [I 2022-11-02 09:01:46] ...trap/engines/engine.py.326: process: 0.29795 | load: 0.00014 [I 2022-11-02 09:02:00] ...trap/engines/engine.py.321: eval: epoch 59 | batch 1570/1578 [I 2022-11-02 09:02:00] ...trap/engines/engine.py.325: elapsed: 0:34:33 | left: 0:00:10 [I 2022-11-02 09:02:00] ...trap/engines/engine.py.326: process: 0.29444 | load: 0.00007 [S 2022-11-02 09:02:11] ...trap/engines/engine.py.132: eval_epoch.epoch: 59 [I 2022-11-02 09:02:11] ...els/metrics/trijoint.py.98: Computing retrieval ranking for 10 x 1000 matchs [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_mean: 1.90 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_mean: 2.00 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_mean: 0.479800 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_mean: 0.766200 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_mean: 0.843400 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_mean: 0.453600 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_mean: 0.745000 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_mean: 0.830600 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.med_im2recipe_std: 0.300000 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.med_recipe2im_std: 0.000000 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_im2recipe_std: 0.013014 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_im2recipe_std: 0.015880 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_im2recipe_std: 0.010413 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_1_recipe2im_std: 0.010956 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_5_recipe2im_std: 0.014262 [S 2022-11-02 09:02:35] ...strap/engines/engine.py.72: eval_epoch.metric.recall_at_10_recipe2im_std: 0.011412 [I 2022-11-02 09:02:52] ...trap/engines/engine.py.138: Saving best checkpoint for strategy eval_epoch.metric.recall_at_1_im2recipe_mean [I 2022-11-02 09:02:52] ...trap/engines/engine.py.470: Saving model... [W 2022-11-02 09:02:53] ...otstrap/views/plotly.py.87: View 'train_epoch.bad_pairs' not in 'logs.json' [W 2022-11-02 09:02:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [W 2022-11-02 09:02:53] ...otstrap/views/plotly.py.93: Split 'optimizer' not in colors '['train_epoch', 'train_batch', 'val_epoch', 'val_batch', 'eval_epoch', 'eval_batch', 'test_epoch', 'test_batch', 'eval_pruned_epoch', 'eval_pruned_batch']' [I 2022-11-02 09:02:57] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-11-02 09:03:05] ...trap/engines/engine.py.478: Saving engine... [I 2022-11-02 09:03:05] ...trap/engines/engine.py.141: Saving last checkpoint [I 2022-11-02 09:03:05] ...trap/engines/engine.py.470: Saving model... [I 2022-11-02 09:03:07] ...tstrap/views/plotly.py.125: Plotly view generated in /gpfswork/rech/dyf/ugz83ue/logs/recipe1m/tfood_tfoodvicha_ttl_ingr_lastcataux_auxkwenc_clipvit_recipe1m_13m_orig_ids/view.html [I 2022-11-02 09:03:10] ...trap/engines/engine.py.474: Saving optimizer... [I 2022-11-02 09:03:15] ...trap/engines/engine.py.478: Saving engine... [I 2022-11-02 09:03:15] ...trap/engines/engine.py.145: Ending training procedures