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Fix shared-storage mutation in sliding-window inference - #9163
agourakis82 wants to merge 2 commits into
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Assisted-by: OpenAI Codex Signed-off-by: Demetrios Agourakis <demetrios@agourakis.med.br>
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📝 Walkthrough
Merge Risk: ⚪ Minimal · up to The change stops sliding-window inference from modifying inputs or outputs that share storage, and keeps numerical results unchanged. Tests cover the aliasing and dtype-rounding cases. No concrete merge-blocking risk is identified. Pre-merge checks |
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| Check name | Status | Explanation | Resolution |
|---|---|---|---|
| Description check |  |
The description explains the fix, regression coverage, benchmarks, and testing limitations. However, it omits the required issue reference, template headings, and change-type checklist, and it does no… | Add the issue reference, restore the required template sections, mark applicable change types including new tests, and state the test commands that were or were not run. |
| Docstring Coverage | |
Docstring coverage is 66.67% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 6 functions across 2 files. | Write docstrings for the functions missing them to satisfy the coverage threshold. |
✅ Passed checks (3 passed)
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Check name Status Explanation Title check The title clearly and concisely describes the primary fix: preventing shared-storage mutation during sliding-window inference. Linked Issues check Check skipped because no linked issues were found for this pull request. Out of Scope Changes check Check skipped because no linked issues were found for this pull request.
Full details: Description check
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Explanation
The description explains the fix, regression coverage, benchmarks, and testing limitations. However, it omits the required issue reference, template headings, and change-type checklist, and it does not mark the added tests.
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Inline comments:
Review comments at @tests/inferers/test_sliding_window_inference.py:
- Line 73: Add docstrings to `test_predictor_weighting_preserves_dtype_rounding`
and `test_predictor_output_alias_preserves_input`, without `Args`, `Returns`, or
`Raises` sections. Add a docstring to the nested `predictor` documenting its
`patch` parameter and its tensor, tuple, or dictionary return value; omit a
`Raises` section.
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monai/inferers/utils.pytests/inferers/test_sliding_window_inference.py
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Assisted-by: OpenAI Codex Signed-off-by: Demetrios Agourakis <demetrios@agourakis.med.br>
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The issue is the in-place weighting of predictor outputs. If an output shares storage with the input or another output, Gaussian blending can modify the input or apply the weights more than once.
The fix avoids modifying shared storage while preserving the existing mixed-precision rounding behavior. The added tests cover tensor, tuple and dictionary outputs, as well as dtype combinations, on CPU and CUDA.
All 42 regression subcases pass with the fix. Running the aliasing test against the original implementation produces 10 expected failures. Eight paired benchmarks on an NVIDIA L4 produced bitwise-identical outputs for valid baseline cases, with measured runtime increases of 1.01–3.36%. The additional peak PyTorch-allocated memory was zero in seven cases and 75,264 bytes in one.
These checks used synthetic inputs and a lightweight predictor, not clinical datasets or trained models. The full test suite was not run.