| from omegaconf import MISSING | |
| from .hear_fsd import HearFSD | |
| __all__ = ["HearNsynth5hr"] | |
| class HearNsynth5hr(HearFSD): | |
| def default_config(self) -> dict: | |
| return dict( | |
| start=0, | |
| stop=None, | |
| target_dir=MISSING, | |
| cache_dir=None, | |
| remove_all_cache=False, | |
| prepare_data=dict( | |
| dataset_root=MISSING, | |
| ), | |
| build_batch_sampler=dict( | |
| train=dict( | |
| batch_size=32, | |
| shuffle=True, | |
| ), | |
| valid=dict( | |
| batch_size=1, | |
| ), | |
| test=dict( | |
| batch_size=1, | |
| ), | |
| ), | |
| build_upstream=dict( | |
| name=MISSING, | |
| ), | |
| build_featurizer=dict( | |
| layer_selections=None, | |
| normalize=False, | |
| ), | |
| build_downstream=dict( | |
| hidden_layers=2, | |
| pooling_type="MeanPooling", | |
| ), | |
| build_model=dict( | |
| upstream_trainable=False, | |
| ), | |
| build_task=dict( | |
| prediction_type="multiclass", | |
| scores=["pitch_acc", "chroma_acc"], | |
| ), | |
| build_optimizer=dict( | |
| name="Adam", | |
| conf=dict( | |
| lr=1.0e-3, | |
| ), | |
| ), | |
| build_scheduler=dict( | |
| name="ExponentialLR", | |
| gamma=0.9, | |
| ), | |
| save_model=dict(), | |
| save_task=dict(), | |
| train=dict( | |
| total_steps=150000, | |
| log_step=100, | |
| eval_step=1000, | |
| save_step=100, | |
| gradient_clipping=1.0, | |
| gradient_accumulate=1, | |
| valid_metric="pitch_acc", | |
| valid_higher_better=True, | |
| auto_resume=True, | |
| resume_ckpt_dir=None, | |
| ), | |
| evaluate=dict(), | |
| ) | |