87 lines
1.7 KiB
Plaintext
87 lines
1.7 KiB
Plaintext
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# lightning.pytorch==2.1.3
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seed_everything: 1009
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trainer:
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accelerator: auto
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strategy: auto
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devices: auto
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num_nodes: 1
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precision: null
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logger: null
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callbacks:
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- class_path: callbacks.SaveImageCallback
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init_args:
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save_interval: 0
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final_dir: out
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fast_dev_run: false
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max_epochs: 10
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min_epochs: 10
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max_steps: -1
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min_steps: null
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max_time: null
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limit_train_batches: null
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limit_val_batches: 50
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limit_test_batches: null
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limit_predict_batches: null
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overfit_batches: 0.0
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val_check_interval: null
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check_val_every_n_epoch: 1
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num_sanity_val_steps: null
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log_every_n_steps: 3
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enable_checkpointing: null
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enable_progress_bar: null
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enable_model_summary: null
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accumulate_grad_batches: 1
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gradient_clip_val: null
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gradient_clip_algorithm: null
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deterministic: null
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benchmark: null
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inference_mode: true
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use_distributed_sampler: true
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profiler: null
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detect_anomaly: false
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barebones: false
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plugins: null
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sync_batchnorm: false
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reload_dataloaders_every_n_epochs: 0
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default_root_dir: null
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model:
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transform: tanh
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width: 512
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depth: 2
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bias: true
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alpha: 0.75
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data:
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val_size: 10000
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train_size: 10000
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batch_size: 256
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num_workers: 3
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ckpt_path: null
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optimizer:
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class_path: torch.optim.AdamW
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init_args:
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lr: 0.001
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betas:
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- 0.9
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- 0.999
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eps: 1.0e-08
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weight_decay: 0.01
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amsgrad: false
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maximize: false
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foreach: null
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capturable: false
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differentiable: false
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fused: null
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lr_scheduler:
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class_path: lightning.pytorch.cli.ReduceLROnPlateau
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init_args:
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monitor: hp_metric
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mode: min
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factor: 0.05
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patience: 5
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threshold: 0.0001
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threshold_mode: rel
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cooldown: 10
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min_lr: 0.0
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eps: 1.0e-08
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verbose: true
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