spatial_resample raises TypeError when spatial_size is None and spatial_rank is 1

Comienza en monai/transforms/spatial/functional.py:159 y compara su predicado con el valor predeterminado de monai/utils/misc.py:261; inspecciona otros llamadores de fall_back_tuple que proporcionen predicados explícitos. Ejecuta tests/data/test_nifti_rw.py y tests/data/test_image_rw.py, y confirma que los tamaños espaciales None recurren correctamente al valor alternativo sin TypeError.

Describe the bug

spatial_resample passes lambda x: x >= 0 to fall_back_tuple, but that helper's default predicate is lambda x: x and x > 0, whose x and short-circuits on None. The override does not, so a None element raises TypeError instead of falling back to the default — which is the documented behaviour of fall_back_tuple, and its own docstring says so:

>>> fall_back_tuple((-1, None), (32, 32))
(32, 32)

monai/transforms/spatial/functional.py:159:

spatial_size = torch.tensor(
    fall_back_tuple(ensure_tuple(spatial_size)[:spatial_rank], in_spatial_size, lambda x: x >= 0)
)

spatial_size reaches that line as None whenever the caller did not supply one and spatial_rank <= 1: the branch above it, elif spatial_size is None and spatial_rank > 1, is the only thing that replaces None, so with a rank of 1 the None survives into ensure_tuple(None) → (None,) → None >= 0.

To Reproduce

import numpy as np
from monai.data.image_writer import NibabelWriter

w = NibabelWriter()
w.set_data_array(np.random.rand(3, 5), channel_dim=None)
w.set_metadata({"affine": np.diag([1, 1, 1]), "original_affine": np.diag([1.4, 1, 1])})

File "monai/data/image_writer.py", line 604, in set_metadata
File "monai/data/image_writer.py", line 273, in resample_if_needed
File "monai/transforms/spatial/array.py", line 229, in __call__
File "monai/transforms/spatial/functional.py", line 159, in <lambda>
    fall_back_tuple(ensure_tuple(spatial_size)[:spatial_rank], in_spatial_size, lambda x: x >= 0)
TypeError: '>=' not supported between instances of 'NoneType' and 'int'

Instrumenting spatial_resample confirms it is entered with spatial_size=None and img.shape=(1, 3, 5).

Expected behavior

None means "no size given for this axis" and should fall back to the corresponding in_spatial_size entry, exactly as fall_back_tuple's docstring describes.

Screenshots / test impact

This is not a corner case reachable only by hand — it fails 8 tests on current dev:

• tests/data/test_nifti_rw.py — test_write_2d, test_write_3d
• tests/data/test_image_rw.py — 4 failures + 4 errors across TestRegRes / writer round-trips

Reproduced on unmodified dev (c1240a2d4) in two independent environments:

So it is not a new-dependency artifact. git log -L159,159 dates that line to #6068 (Feb 2023).

Environment

MONAI version: 1.6.0rc1+58.gc1240a2d4
Python: 3.10 and 3.12 (both affected)
PyTorch: 2.11.0 and 2.13.0 (both affected)
numpy: 2.2.6
nibabel: 5.4.2

Additional context

The narrowest fix is to make the predicate None-safe at the call site, matching the helper's default:

lambda x: x is not None and x >= 0

Worth checking the other fall_back_tuple callers that pass an explicit func for the same hazard — any predicate that does not short-circuit on None inherits it.