# pytorch_lightning==1.9.3 seed_everything: 123 trainer: logger: class_path: pytorch_lightning.loggers.TensorBoardLogger init_args: save_dir: logs name: exp_contrastive_reg_sameclip version: null log_graph: false default_hp_metric: true prefix: '' sub_dir: null enable_checkpointing: true callbacks: - class_path: pytorch_lightning.callbacks.ModelCheckpoint init_args: dirpath: null filename: best-val-loss-{epoch}-{step} monitor: loss/val verbose: false save_last: null save_top_k: 1 save_weights_only: false mode: min auto_insert_metric_name: true every_n_train_steps: null train_time_interval: null every_n_epochs: null save_on_train_epoch_end: null - class_path: pytorch_lightning.callbacks.ModelCheckpoint init_args: dirpath: null filename: best-eer-val-{epoch}-{step} monitor: EER evaluation proj/val verbose: false save_last: null save_top_k: 1 save_weights_only: false mode: min auto_insert_metric_name: true every_n_train_steps: null train_time_interval: null every_n_epochs: null save_on_train_epoch_end: null - class_path: pytorch_lightning.callbacks.ModelCheckpoint init_args: dirpath: null filename: best-rank-val-{epoch}-{step} monitor: Order evaluation mean proj/val verbose: false save_last: null save_top_k: 1 save_weights_only: false mode: min auto_insert_metric_name: true every_n_train_steps: null train_time_interval: null every_n_epochs: null save_on_train_epoch_end: null - class_path: pytorch_lightning.callbacks.ModelCheckpoint init_args: dirpath: null filename: best-alignment-val-{epoch}-{step} monitor: Alignment evaluation proj/val verbose: false save_last: null save_top_k: 1 save_weights_only: false mode: min auto_insert_metric_name: true every_n_train_steps: null train_time_interval: null every_n_epochs: null save_on_train_epoch_end: null - class_path: pytorch_lightning.callbacks.ModelCheckpoint init_args: dirpath: null filename: best-uniformity-val-{epoch}-{step} monitor: Uniformity evaluation proj/val verbose: false save_last: null save_top_k: 1 save_weights_only: false mode: min auto_insert_metric_name: true every_n_train_steps: null train_time_interval: null every_n_epochs: null save_on_train_epoch_end: null - class_path: pytorch_lightning.callbacks.ModelCheckpoint init_args: dirpath: null filename: cptk-{epoch}-{step} monitor: null verbose: false save_last: null save_top_k: -1 save_weights_only: false mode: min auto_insert_metric_name: true every_n_train_steps: null train_time_interval: null every_n_epochs: 25 save_on_train_epoch_end: null - class_path: callbacks.evaluation.OrderEvaluation init_args: log_n_epochs: 5 on_train: true use_projection: true - class_path: callbacks.evaluation.EEREvaluation init_args: use_more_neg: false log_n_epochs: 5 on_train: false use_projection: true - class_path: callbacks.evaluation.HypersphereEvaluation init_args: log_n_epochs: 5 on_train: true use_projection: true default_root_dir: null gradient_clip_val: null gradient_clip_algorithm: null num_nodes: 1 num_processes: null devices: 1 gpus: null auto_select_gpus: null tpu_cores: null ipus: null enable_progress_bar: true overfit_batches: 0.0 track_grad_norm: -1 check_val_every_n_epoch: 1 fast_dev_run: false accumulate_grad_batches: null max_epochs: 100000 min_epochs: null max_steps: 1000000000 min_steps: null max_time: null limit_train_batches: null limit_val_batches: null limit_test_batches: null limit_predict_batches: null val_check_interval: null log_every_n_steps: 50 accelerator: gpu strategy: ddp sync_batchnorm: false precision: 32 enable_model_summary: true num_sanity_val_steps: 2 resume_from_checkpoint: null profiler: null benchmark: null deterministic: null reload_dataloaders_every_n_epochs: 0 auto_lr_find: false replace_sampler_ddp: true detect_anomaly: false auto_scale_batch_size: false plugins: null amp_backend: null amp_level: null move_metrics_to_cpu: false multiple_trainloader_mode: max_size_cycle inference_mode: true ckpt_path: null model: class_path: models.trainer.ContrastiveTrainer init_args: feature_extractor: spec_layer: melspectogram n_fft: 2048 hop_length: 512 backbone: backbone: efficientnet_b0 pretrained: true embedding_dim: 1000 projection: input_dim: 1000 output_dim: 128 l2_normalize: true optimizer1_init: class_path: torch.optim.Adam init_args: lr: 0.0001 weight_decay: 1.0e-05 use_contrastive_loss: true temp: 0.2 nr_negative: 250 decouple: true use_norm_reg: false max_norm_hinge: 4.0 norm_hinge_fact: 10.0 use_invariance_loss: false fact_inv_loss: 1.0 use_covariance_reg: true fact_cov: 100.0 use_variance_reg: true fact_var: 25.0 gamma: 1.0 use_vicreg_loss: false use_align_loss: false fact_align_loss: 0.25 fact_unif_loss: 0.5 use_uniform_loss: false mask_batch: false compute_test_loss: false data: class_path: data.vocals.VocalsDataModule init_args: augs_neg: enable: false gaussian_noise: 0.5 pitch_shift_naive: 0 time_stretch: 0 gain: 0.5 shift: 0 parametric_eq: 0 tanh_distortion: 0 time_mask: 0 formant_shift_parselmouth: 0 pitch_shift_parselmouth: 0 pitch_range_parselmouth: 0 pitch_shift_parselmouth_prob: 0 positive_examples: same_clip dataset_dirs: - tencys_vocals - ghero_vocals_3 - ghero_vocals_4 batch_size: 120 batch_size_val: 120 nr_samples: 176000 normalize: true num_workers: 40 sr: 44100 batch_sampling_mode: sample_clips eval_frac: 0.105 group_name_is_folder: true group_by_artist: true augs: enable: true gaussian_noise: 0.5 pitch_shift_naive: 0 time_stretch: 0 gain: 0.5 shift: 0 parametric_eq: 0 tanh_distortion: 0 time_mask: 0.5 formant_shift_parselmouth: 0 pitch_shift_parselmouth: - 1 - 1.3 pitch_range_parselmouth: 1.5 pitch_shift_parselmouth_prob: 0.5 transform_override: false verbose: true use_random_loader: false max_groups: -1 multi_epoch: 1 classification: false