Describe the bug
compute_shape_offset in monai/data/utils.py (line 883) passes spatial_shape directly to np.array(). When spatial_shape is a PyTorch tensor, this triggers the non-tuple sequence multidimensional indexing deprecation that became a breaking change in PyTorch 2.9+.
To reproduce
Run any pipeline that goes through SaveImaged → NiftiWriter.set_metadata → resample_if_needed → spatial_resample → compute_shape_offset with PyTorch ≥ 2.9.
Expected behavior
No error. spatial_shape should be converted to a plain Python tuple before being passed to np.array.
Actual behavior
On PyTorch ≥ 2.9, this either raises an error or produces silently wrong results.
On PyTorch 2.8 it was a deprecation warning.
Environment
- MONAI: 1.5.2
- PyTorch: 2.10.0+cu129
- Python: 3.11
- OS: Windows 11
Suggested fix
# monai/data/utils.py, line 883
# Before:
shape = np.array(spatial_shape, copy=True, dtype=float)
# After:
shape = np.array(tuple(spatial_shape), copy=True, dtype=float)
Describe the bug
compute_shape_offsetinmonai/data/utils.py(line 883) passesspatial_shapedirectly tonp.array(). Whenspatial_shapeis a PyTorch tensor, this triggers the non-tuple sequence multidimensional indexing deprecation that became a breaking change in PyTorch 2.9+.To reproduce
Run any pipeline that goes through
SaveImaged→NiftiWriter.set_metadata→resample_if_needed→spatial_resample→compute_shape_offsetwith PyTorch ≥ 2.9.Expected behavior
No error.
spatial_shapeshould be converted to a plain Python tuple before being passed tonp.array.Actual behavior
On PyTorch ≥ 2.9, this either raises an error or produces silently wrong results.
On PyTorch 2.8 it was a deprecation warning.
Environment
Suggested fix