[Fix][Relax]: ONNX Clip NaN bounds and preserve input NaN (ORT parity)#19535
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This pull request improves the ONNX Clip operator implementation in Relax to correctly handle NaN values in both the input tensor and the clip bounds (min/max). It introduces a helper function to identify floating-point types and a sanitization method for NaN bounds. Feedback includes correcting the casing of DataTypeCode constants to avoid runtime errors, refactoring duplicated comparison logic in tests, removing redundant test parameters, and expanding test coverage to explicitly verify that input NaNs are preserved.
…k_correctness - Extend tvm.testing.assert_allclose with equal_nan (forwarded to NumPy) and document parameters. - Refactor check_correctness _check_output to normalize ndarray once and call a single assert helper. - Parametrize test_clip_v13 over input vectors (finite vs NaN); adjust Clip v13 min/max fixture where needed.
tlopex
approved these changes
May 12, 2026
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This PR fixes #19533: