JiaruiLi/DeepHealthExpo
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Lighten TimesNet exposure backbone

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Jiarui Li
2026-07-09 14:23:28 +08:00
parent 54fedc620b
commit f7fb6b7718
5 changed files with 95 additions and 149 deletions
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22
train_next_step.py
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@@ -129,12 +129,12 @@ def parse_args() -> argparse.Namespace:
parser.add_argument("--dropout", type=float, default=0.0)
parser.add_argument("--exposure_cache_dir", type=str, default=None)
parser.add_argument("--mask_onset_exposure", action="store_true")
parser.add_argument("--exposure_d_model", type=int, default=None)
parser.add_argument("--exposure_d_model", type=int, default=64)
parser.add_argument("--exposure_n_layers", type=int, default=2)
parser.add_argument("--exposure_top_k", type=int, default=3)
parser.add_argument("--exposure_n_convnext_blocks", type=int, default=2)
parser.add_argument("--exposure_conv_kernel_size", type=int, default=7)
parser.add_argument("--exposure_mlp_ratio", type=float, default=4.0)
parser.add_argument("--exposure_top_k", type=int, default=2)
parser.add_argument("--exposure_n_backbone_blocks", type=int, default=1)
parser.add_argument("--exposure_backbone_kernel_size", type=int, default=5)
parser.add_argument("--exposure_backbone_expansion", type=float, default=2.0)
parser.add_argument("--no_exposure_gate", action="store_true")
parser.add_argument("--target_mode", type=str, default="uts",
choices=["delphi2m", "uts"])
@@ -280,9 +280,9 @@ def build_model(args: argparse.Namespace, dataset: HealthDataset) -> DeepHealth:
exposure_d_model=args.exposure_d_model,
exposure_n_layers=args.exposure_n_layers,
exposure_top_k=args.exposure_top_k,
exposure_n_convnext_blocks=args.exposure_n_convnext_blocks,
exposure_conv_kernel_size=args.exposure_conv_kernel_size,
exposure_mlp_ratio=args.exposure_mlp_ratio,
exposure_n_backbone_blocks=args.exposure_n_backbone_blocks,
exposure_backbone_kernel_size=args.exposure_backbone_kernel_size,
exposure_backbone_expansion=args.exposure_backbone_expansion,
exposure_use_gate=not args.no_exposure_gate,
)
@@ -490,9 +490,9 @@ def build_metadata(
"exposure_d_model": args.exposure_d_model,
"exposure_n_layers": int(args.exposure_n_layers),
"exposure_top_k": int(args.exposure_top_k),
"exposure_n_convnext_blocks": int(args.exposure_n_convnext_blocks),
"exposure_conv_kernel_size": int(args.exposure_conv_kernel_size),
"exposure_mlp_ratio": float(args.exposure_mlp_ratio),
"exposure_n_backbone_blocks": int(args.exposure_n_backbone_blocks),
"exposure_backbone_kernel_size": int(args.exposure_backbone_kernel_size),
"exposure_backbone_expansion": float(args.exposure_backbone_expansion),
"exposure_use_gate": not bool(args.no_exposure_gate),
"num_workers": int(args.num_workers),
"prefetch_factor": int(args.prefetch_factor),