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spatial_resample raises TypeError when spatial_size is None and spatial_rank is 1

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Valutazione

Difficoltà
2/5
Tempo stimato
1-3 ore
Idoneità per principianti
85/100
Tipo di issue
Bug
Chiarezza
Specificata chiaramente
Stato di attività
Attiva
Stack tecnologico
python, pytorch
Ambito
computer-vision

Direzione di ricerca

Inizia da monai/transforms/spatial/functional.py:159 e confronta il relativo predicato con quello predefinito in monai/utils/misc.py:261; esamina gli altri chiamanti di fall_back_tuple che forniscono predicati espliciti. Esegui tests/data/test_nifti_rw.py e tests/data/test_image_rw.py e verifica che le dimensioni spaziali None ricadano correttamente sul valore di fallback senza TypeError.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

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:
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.

Lingua principale
Python
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Merge medio
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PR unite (30g)
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