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fix: support decollate for numpy scalars #8470

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fix: support decollate for numpy scalars #8470

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2 changes: 2 additions & 0 deletions monai/data/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -625,6 +625,8 @@ def decollate_batch(batch, detach: bool = True, pad=True, fill_value=None):
type(batch).__module__ == "numpy" and not isinstance(batch, Iterable)
):
return batch
if isinstance(batch, np.ndarray) and batch.ndim == 0:
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Thanks for the pr! Do you think it might be beneficial to convert the array into a tensor? This way, the data could be handled more consistently.

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We could, I think it does not matter for my use cases. As long as the function handles numpy scalars in the form of an array it is good for me!

I will add this change and convert it as a tensor there (L629) if you prefer :)

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Thanks for the quick fix!
May I ask the reason for only convert to tensor when batch.ndim == 0 here?

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@arthurdjn arthurdjn Jun 6, 2025 •
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I noticed a different behavior when using the decollate_batch function on torch tensors vs numpy arrays (see discussion #8472) so I don't want to convert numpy arrays to torch tensors as it will introduce some breaking changes

This PR only address the issue #8471 as I think it was not expected and should be supported (?).

batch = torch.from_numpy(batch)
if isinstance(batch, torch.Tensor):
if detach:
batch = batch.detach()
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