Add spatial shape constraint docs and test for SwinUNETR (#6771)

[Cado87]

Fixes #6771 .

Description

Adds documentation of spatial shape constraints for SwinUNETR. Each input
spatial dimension must be divisible by patch_size ** 5 (32 by default with
patch_size=2). The runtime validation logic already existed in _check_input_size()
but was undocumented. This PR adds a Spatial Shape Constraints section to the
class docstring, updates the patch_size arg description in __init__, and adds
a test to verify that forward() raises ValueError for invalid spatial shapes.

Types of changes

• Non-breaking change (fix or new feature that would not break existing functionality).
• Breaking change (fix or new feature that would cause existing functionality to change).
• New tests added to cover the changes.
• Integration tests passed locally by running ./runtests.sh -f -u --net --coverage.
• Quick tests passed locally by running ./runtests.sh --quick --unittests --disttests.
• In-line docstrings updated.
• Documentation updated, tested make html command in the docs/ folder.

[coderabbitai]

📝 Walkthrough

Walkthrough

Updated SwinUNETR class docstrings to explicitly document that input spatial dimensions must be divisible by patch_size ** 5. Added a Raises: entry documenting the ValueError condition. Added a unit test validating that the constraint is enforced for both 2D and 3D configurations. No runtime logic was modified; validation already exists in _check_input_size().

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~12 minutes

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 25.00% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	Title directly describes the main change: adding spatial shape constraint documentation and tests for SwinUNETR.
Description check	✅ Passed	Description includes all required sections with clear explanation of changes, proper types selection, and docstring updates acknowledged.
Linked Issues check	✅ Passed	PR addresses issue #6771 by documenting spatial shape constraints (divisibility by patch_size**5) through docstrings and unit tests, fulfilling the request for code logic and documentation.
Out of Scope Changes check	✅ Passed	All changes stay focused on documenting and testing existing spatial shape constraints; no unrelated modifications introduced.

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✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests

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[coderabbitai]

🧹 Nitpick comments (1)

tests/networks/nets/test_swin_unetr.py (1)

93-103: Consider adding one non-default patch_size case.

This verifies the default (patch_size=2) path well. Add one invalid-shape assertion for patch_size=3 to directly cover the generalized patch_size ** 5 contract.

Proposed test extension

     def test_invalid_input_shape(self):
         # spatial dims not divisible by patch_size**5 (default patch_size=2, so must be divisible by 32)
         net = SwinUNETR(in_channels=1, out_channels=2, feature_size=24, spatial_dims=3)
         with self.assertRaises(ValueError):
             net(torch.randn(1, 1, 33, 64, 64))  # 33 is not divisible by 32

         net_2d = SwinUNETR(in_channels=1, out_channels=2, feature_size=24, spatial_dims=2)
         with self.assertRaises(ValueError):
             net_2d(torch.randn(1, 1, 48, 33))  # 33 is not divisible by 32
+
+        net_2d_patch3 = SwinUNETR(in_channels=1, out_channels=2, feature_size=24, spatial_dims=2, patch_size=3)
+        with self.assertRaises(ValueError):
+            net_2d_patch3(torch.randn(1, 1, 33, 33))  # 33 is not divisible by 3**5 (243)

As per coding guidelines, "Ensure new or modified definitions will be covered by existing or new unit tests."

🤖 Prompt for AI Agents

Verify each finding against the current code and only fix it if needed.

In `@tests/networks/nets/test_swin_unetr.py` around lines 93 - 103, Add a new
invalid-shape assertion in the same test (test_invalid_input_shape) that
instantiates SwinUNETR with a non-default patch_size (e.g., patch_size=3) and
calls the model with an input tensor whose spatial dimensions are not divisible
by that patch_size (e.g., use torch.randn(1, 1, 10, 48, 48) for spatial_dims=3)
wrapped in self.assertRaises(ValueError); this will exercise the SwinUNETR
constructor/check logic (SwinUNETR) for non-default patch sizes and ensure the
generalized patch_size validation path is covered.

🤖 Prompt for all review comments with AI agents

Verify each finding against the current code and only fix it if needed.

Nitpick comments:
In `@tests/networks/nets/test_swin_unetr.py`:
- Around line 93-103: Add a new invalid-shape assertion in the same test
(test_invalid_input_shape) that instantiates SwinUNETR with a non-default
patch_size (e.g., patch_size=3) and calls the model with an input tensor whose
spatial dimensions are not divisible by that patch_size (e.g., use
torch.randn(1, 1, 10, 48, 48) for spatial_dims=3) wrapped in
self.assertRaises(ValueError); this will exercise the SwinUNETR
constructor/check logic (SwinUNETR) for non-default patch sizes and ensure the
generalized patch_size validation path is covered.

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ℹ️ Review info

⚙️ Run configuration

Configuration used: Path: .coderabbit.yaml

Review profile: CHILL

Plan: Pro

Run ID: 8e650413-a978-4d3a-999c-17bfa4eb13df

📥 Commits

Reviewing files that changed from the base of the PR and between cc92126 and cb21557.

📒 Files selected for processing (2)

• monai/networks/nets/swin_unetr.py
• tests/networks/nets/test_swin_unetr.py

[ericspod]

Hi @Cado87 thanks for the network shape analysis!