pytorch

9cfc10d5 - Updates assertEqual to use torch.isclose-like logic (#37294)

Updates assertEqual to use torch.isclose-like logic (#37294) Summary: Edit: this has been updated to reflect the PR's current status, which has changed after review. This PR updates the behavior of the assertEqual, assertNotEqual, and assert_allclose to be consistent with each other and torch.isclose. It corrects several additional bugs in the current implementations and adds extensive testing and comments, too. These updates follow from changes to assertEqual like https://github.com/pytorch/pytorch/pull/34258 and https://github.com/pytorch/pytorch/pull/37069, and from our discussion of torch.isclose for complex tensors (see https://github.com/pytorch/pytorch/issues/36462), where we decided to implement a NumPy-compatible mathematical notion of "closeness" for complex tensors that is not a great fit for our testing framework. The detailed changelist is: - New test framework functions for comparing tensors and scalars - Tensors are compared using isclose; the real and imaginary parts of complex tensors are compared independently - Scalars are compared using the same algorithm - assertEqual and assert_allclose now use this common comparison function, instead of each implementing their own with divergent behavior - assertEqual-like debug messages are now available for all tensor and scalar comparisons, with additional context when comparing the components of sparse, quantized, and complex tensors - Extensive testing of the comparison behavior and debug messages - Small Updates - assertEqual now takes an "exact_device" argument, analogous to "exact_dtype", which should be useful in multidevice tests - assertEqual now takes an "equal_nan" argument for argument consistency with torch.isclose - assertEqual no longer takes the "allow_inf" keyword, which misleadingly only applied to scalar comparisons, was only ever set (rarely) to true, and is not supported by torch.isclose - Bug fixes: - the exact_dtype attribute has been removed (no longer needed after https://github.com/pytorch/pytorch/pull/38103) - message arguments passed to assertEqual are now handled correctly - bool x other dtype comparisons are now supported - uint8 and int8 tensor comparisons now function properly - rtol for integer comparisons is now supported (default is zero) - rtol and atol for scalar comparisons are now supported - complex scalar comparisons are now supported, analogous to complex tensor comparisons - assertNotEqual is now equivalent to the logical negation of assertEqual Pull Request resolved: https://github.com/pytorch/pytorch/pull/37294 Differential Revision: D21596830 Pulled By: mruberry fbshipit-source-id: f2576669f7113a06f82581fc71883e6b772de19b