pytorch

4bafca1a - Adds list of operator-related information for testing (#41662)

Adds list of operator-related information for testing (#41662) Summary: This PR adds: - an "OpInfo" class in common_method_invocations that can contain useful information about an operator, like what dtypes it supports - a more specialized "UnaryUfuncInfo" class designed to help test the unary ufuncs - the `ops` decorator, which can generate test variants from lists of OpInfos - test_unary_ufuncs.py, a new test suite stub that shows how the `ops` decorator and operator information can be used to improve the thoroughness of our testing The single test in test_unary_ufuncs.py simply ensures that the dtypes associated with a unary ufunc operator in its OpInfo entry are correct. Writing a test like this previously, however, would have required manually constructing test-specific operator information and writing a custom test generator. The `ops` decorator and a common place to put operator information make writing tests like this easier and allows what would have been test-specific information to be reused. The `ops` decorator extends and composes with the existing device generic test framework, allowing its decorators to be reused. For example, the `onlyOnCPUAndCUDA` decorator works with the new `ops` decorator. This should keep the tests readable and consistent. Future PRs will likely: - continue refactoring the too large test_torch.py into more verticals (unary ufuncs, binary ufuncs, reductions...) - add more operator information to common_method_invocations.py - refactor tests for unary ufuncs into test_unary_ufunc Examples of possible future extensions are [here](https://github.com/pytorch/pytorch/pull/41662/commits/616747e50dbb5a3338deedf41ff44957b162ab51), where an example unary ufunc test is added, and [here](https://github.com/pytorch/pytorch/pull/41662/commits/d0b624f110d470b9a37ad02b389d2f4258c3d632), where example autograd tests are added. Both tests leverage the operator info in common_method_invocations to simplify testing. Pull Request resolved: https://github.com/pytorch/pytorch/pull/41662 Reviewed By: ngimel Differential Revision: D23048416 Pulled By: mruberry fbshipit-source-id: ecce279ac8767f742150d45854404921a6855f2c