pytorch

03b5a225 - Test parametrization for instantiated device-specific tests (#60233)

Test parametrization for instantiated device-specific tests (#60233) Summary: The `ops` decorator provides a way to parameterize a test across a given list of ops. This would be useful for modules as well (e.g. a `modules` decorator), but the mechanism by which this is accomplished is specific to ops. In the details, the `ops` decorator tags a test function with the metadata needed (list of ops, `dtypes`) and the actual tests are generated according to this metadata during the call to `instantiate_device_type_tests()`. This PR makes this mechanism more generic, allowing for test parameterization across arbitrary dimensions. This makes a `modules` decorator (or any similar type of decorator) straightforward to implement without changes to the device-specific test instantiation logic. One caveat is that, since this is implemented where the old `ops` decorator was (within `instantiate_device_type_tests()`), this only works for tests instantiated using the device-specific instantiation logic. Longer term, even device-specific test instantiation could be treated as an optional parameterization across device types, but this PR takes a low-risk approach for now. In practice, this just means that a `device` kwarg is required for all test signatures used with the mechanism. The `ops` decorator has been refactored to use the generic mechanism and works the same as before, with one difference: when `OpDTypes.none` is specified, the test signature no longer needs an unused `dtype` kwarg. This is a nice bonus that demonstrates the added flexibility of a generic parameterization mechanism. The refactored form also has the bonus that all op-specific test generation logic is contained within the `ops` decorator class, improving readability. Behind the scenes, the generic mechanism is a base decorator class (`_TestParameterizer`) from which `ops` derives. The core functionality is in the `_parameterize_test()` method, which takes in a test function and returns a generator that produces parameterized tests, including names and parameter kwargs to pass to them. Using the `ops` decorator results in a set of op-specific tests from a given generic test. Pull Request resolved: https://github.com/pytorch/pytorch/pull/60233 Reviewed By: iramazanli Differential Revision: D29494995 Pulled By: jbschlosser fbshipit-source-id: a14446488c106094fafcaa75ccf8e9e3faf33bfc