Fix floating point precision issue in step_size validation #4604
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…4604) Summary: Python's modulo operation with floating point numbers produces inaccurate results due to binary representation limitations (e.g., 1.0 % 0.1 returns ~0.1 instead of 0). This caused valid fractional step sizes to incorrectly fail validation. The fix uses np.isclose() for tolerance-based comparison when checking if a range is evenly divisible by the step size. see facebook#4599 Reviewed By: saitcakmak Differential Revision: D88077995
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Summary:
Python's modulo operation with floating point numbers produces inaccurate results due to binary representation limitations (e.g., 1.0 % 0.1 returns ~0.1 instead of 0). This caused valid fractional step sizes to incorrectly fail validation.
The fix uses np.isclose() for tolerance-based comparison when checking if a range is evenly divisible by the step size.
see #4599
Reviewed By: saitcakmak
Differential Revision: D88077995