HH w|A brain.Event:2R. ,tensorboard.summary.writer.event_file_writer`V=e`/# tA*  hp_metric5 VA* _hparams_/experimentJ hparams  " hidden_dim " transformer_dim " transformer_dim_scale " initial_embedding_dim " position_embedding_dim " num_embedding_layers " num_encoder_layers " num_branch_embedding_layers " num_branch_encoder_layers " num_jet_embedding_layers " num_jet_encoder_layers " num_detector_layers " num_regression_layers " num_classification_layers " split_symmetric_attention " num_attention_heads " transformer_activation " skip_connections "& "initial_embedding_skip_connections " linear_block_type " transformer_type " linear_activation " normalization " masking " linear_prelu_activation " use_pairwise_interactions " num_pairwise_features " pairwise_embedding_dim " pairwise_input_source " use_moe " num_experts " num_experts_per_tok " moe_loss_scale " event_info_file " training_file " validation_file " testing_file " normalize_features " limit_to_num_jets " balance_particles " balance_jets " balance_classifications " partial_events " dataset_limit " dataset_randomization " train_validation_split " limit_val_batches " batch_size " num_dataloader_workers " mask_sequence_vectors " combine_pair_loss " optimizer " learning_rate " focal_gamma " combinatorial_scale " learning_rate_warmup_epochs " learning_rate_cycles " assignment_loss_scale " detection_loss_scale " kl_loss_scale " regression_loss_scale " classification_loss_scale " use_mass_classification " balance_losses " l2_penalty " gradient_clip " dropout " epochs " num_gpu " verbose_output " usable_gpus " trial_time " trial_output_dir *  hp_metricNf' : ēA*  _hparams_/session_start_infoJ  hparams " assignment_loss_scale ?  skip_connections ? $ use_mass_classification   balance_particles   normalize_features ?  optimizerAdamW # train_validation_split ffffff?  balance_losses ? ( learning_rate_warmup_epochs ? & num_branch_encoder_layers @  limit_val_batches ?  num_experts  @ " regression_loss_scale   l2_penalty -C6*?  usable_gpus  epochs Y@ / "initial_embedding_skip_connections ?  moe_loss_scale {Gz?  balance_jets   num_gpu ?  validation_file num_experts_per_tok @  dropout b_1?  kl_loss_scale  & split_symmetric_attention ?  normalization  LayerNorm combinatorial_scale  ! num_embedding_layers @  num_encoder_layers @ # num_dataloader_workers  @ $ linear_prelu_activation ?  testing_file & classification_loss_scale  H training_file75/data/spatop/tpm70_wpm30_FB350_training/all_merged.h5  transformer_dim `@ J event_info_file75/data/spatop/event_files/v11/tt_hadronic_v7_full.yaml  hidden_dim `@  gradient_clip $@ " num_pairwise_features @  linear_activationgelu  verbose_output   masking Filling & num_classification_layers @  trial_time  combine_pair_lossmin " transformer_dim_scale @ num_detector_layers @  dataset_limit ?  learning_rate PE3i#?  linear_block_typeGRU ! learning_rate_cycles ? " mask_sequence_vectors ? " num_regression_layers @ num_attention_heads  @ ! detection_loss_scale ?  focal_gamma   batch_size @  partial_events ? " dataset_randomization  $ balance_classifications   pairwise_input_source transformer_activationgelu # pairwise_embedding_dim  @ " initial_embedding_dim `@ % num_jet_embedding_layers  # num_jet_encoder_layers @ # trial_output_dir ./test_output ( num_branch_embedding_layers @  transformer_typeGated & use_pairwise_interactions   limit_to_num_jets   use_moe  # position_embedding_dim `@?<ȷR ܓA*1 / _hparams_/session_end_infoJ  hparams"KĀ