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added torch_em load_model to supervised training #146

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added torch_em load_model to supervised training #146

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3fecc1f
added torch_em load_model to supervised training
lufre1 Nov 10, 2025
6263ed3
added docs for chekcpoint_path
lufre1 Nov 10, 2025
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5 changes: 5 additions & 0 deletions synapse_net/training/supervised_training.py
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Original file line number Diff line number Diff line change
Expand Up @@ -201,6 +201,7 @@ def supervised_training(
in_channels: int = 1,
out_channels: int = 2,
mask_channel: bool = False,
checkpoint_path: Optional[str] = None,
**loader_kwargs,
):
"""Run supervised segmentation training.
Expand Down Expand Up @@ -243,6 +244,7 @@ def supervised_training(
out_channels: The number of output channels of the UNet.
mask_channel: Whether the last channels in the labels should be used for masking the loss.
This can be used to implement more complex masking operations and is not compatible with `ignore_label`.
checkpoint_path: Path to the directory where 'best.pt' resides; continue training this model.
loader_kwargs: Additional keyword arguments for the dataloader.
"""
train_loader = get_supervised_loader(train_paths, raw_key, label_key, patch_shape, batch_size,
Expand All @@ -265,6 +267,9 @@ def supervised_training(
model = get_2d_model(out_channels=out_channels, in_channels=in_channels)
else:
model = get_3d_model(out_channels=out_channels, in_channels=in_channels)

if checkpoint_path:
model = torch_em.util.load_model(checkpoint=checkpoint_path)

loss, metric = None, None
# No ignore label -> we can use default loss.
Expand Down