Ignores deliberate undefined float->int conversion (#35086)
Summary:
In C++, casting a floating point value to an integer dtype is undefined when the value is outside the dtype's dynamic range. For example, casting 300.5 to Int8 is undefined behavior because the maximum representable Int8 value is 127, and 300.5 > 127.
PyTorch, like NumPy, deliberately allows and makes these casts, however, and when we do this we trigger undefined behavior that causes our sanitizers to (correctly) complain. I propose skipping this sanitization on our cast function.
The history of this PR demonstrates the issue, showing a single CI failure in the ASAN build when a test is added that converts a large float value to an integral value. The current PR shows a green CI after the sanitization is skipped.
There are alternatives to skipping this sanitization:
- Clamping or otherwise converting floats to the dynamic range of integral types they're cast to
- Throwing a runtime error if a float value is outside the dynamic range of the integral type it's cast to (this would not be NumPy compatible)
- Declaring programs in error if they perform these casts (this is technically true)
- Preventing this happening in PyTorch proper so the ASAN build doesn't fail
None of these alternatives seems particularly appealing, and I think it's appropriate to skip the sanitization because our behavior is deliberate.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/35086
Differential Revision: D20591163
Pulled By: mruberry
fbshipit-source-id: fa7a90609c73c4c627bd39726a7dcbaeeffa1d1b
