[Bugfix]Fix a conditional to not check zero value #28754
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Checking zero value would introduce an unnecessary and failing dynamic shape guard in some cases. In this case, checking nonness is sufficient and correct. Signed-off-by: Yanan Cao <gmagogsfm@gmail.com>
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This pull request addresses a subtle bug in the logic for reconstructing compilation inputs during the deserialization of a compiled function. The previous implementation using inp or example_inputs[i] would incorrectly discard falsy values such as 0, which can be valid inputs (e.g., for tensor dimensions). The change to inp if inp is not None else example_inputs[i] is correct, as it explicitly checks for None, which is the intended placeholder for runtime tensor inputs. This fix improves the robustness and correctness of the compilation caching mechanism.
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@zou3519 @ProExpertProg Could you take a quick look at this one-line change? Thanks |
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LGTM< cc @zhxchen17 @zou3519
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@gmagogsfm could you just elaborate what the repro for causing this issue is? |
I discovered this issue when debugging a dynamic shape bug. I think |
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in torch.compile integration
Signed-off-by: Yanan Cao <gmagogsfm@gmail.com>
Signed-off-by: Yanan Cao <gmagogsfm@gmail.com>
Signed-off-by: Yanan Cao <gmagogsfm@gmail.com> Signed-off-by: Runkai Tao <rt572@physics.rutgers.edu>
Signed-off-by: Yanan Cao <gmagogsfm@gmail.com>
Signed-off-by: Yanan Cao <gmagogsfm@gmail.com>
Signed-off-by: Yanan Cao <gmagogsfm@gmail.com>
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if inpunintentionally checks zero value in addition to none-ness. This would introduce an unnecessary and failing dynamic shape guard in some cases. Checking none-ness only is sufficient and correct.