Project-MONAI / Project-MONAI/MONAI
spatial_resample raises TypeError when spatial_size is None and spatial_rank is 1
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Description
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_3dtests/data/test_image_rw.py— 4 failures + 4 errors acrossTestRegRes/ writer round-trips
Reproduced on unmodified dev (c1240a2d4) in two independent environments:
| Python 3.12 / torch 2.13.0 / numpy 2.x | fails |
| Python 3.10 / torch 2.11.0 (highest version CI tests) / numpy 2.2.6 | fails identically |
So it is not a new-dependency artifact. git log -L159,159 dates that line to #6068 (Feb 2023).
Environment
Ensuring you use the relevant python executable, please paste the output of:
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.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start at monai/transforms/spatial/functional.py:159 and compare its predicate with the default in monai/utils/misc.py:261; inspect other fall_back_tuple callers that provide explicit predicates. Run tests/data/test_nifti_rw.py and tests/data/test_image_rw.py, and confirm that None spatial sizes fall back correctly without TypeError.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision
- Issue type
- Bug
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Active
- Clarity
- Clearly specified
- Newbie friendliness
- 85/100