pytorch

c1cdb121 - Add dispatch mode testing for meta tensors and other stuff

Add dispatch mode testing for meta tensors and other stuff We don't have any coverage for meta tensor correctness for backwards because torch function mode can only allow us to interpose on Python torch API calls, but backwards invocations happen from C++. To make this possible, I add torch_dispatch_meta test which runs the tests with __torch_dispatch__ While doing this, I needed to generate fresh expected failure / skip lists for the new test suite, and I discovered that my original scaffolding for this purpose was woefully insufficient. So I rewrote how the test framework worked, and at the same time rewrote the __torch_function__ code to also use the new logic. Here's whats new: - Expected failure / skip is now done on a per function call basis, rather than the entire test. This means that separate OpInfo samples for a function don't affect each other. - There are now only two lists: expect failure list (where the test consistently fails on all runs) and skip list (where the test sometimes passes and fails. - We explicitly notate the dtype that failed. I considered detecting when something failed on all dtypes, but this was complicated and listing everything out seemed to be nice and simple. To keep the dtypes short, I introduce a shorthand notation for dtypes. - Conversion to meta tensors is factored into its own class MetaConverter - To regenerate the expected failure / skip lists, just run with PYTORCH_COLLECT_EXPECT and filter on a specific test type (test_meta or test_dispatch_meta) for whichever you want to update. Other misc fixes: - Fix max_pool1d to work with BFloat16 in all circumstances, by making it dispatch and then fixing a minor compile error (constexpr doesn't work with BFloat16) - Add resolve_name for turning random torch API functions into string names - Add push classmethod to the Mode classes, so that you can more easily push a mode onto the mode stack - Add some more skips for missing LAPACK - Added an API to let you query if there's already a registration for a function, added a test to check that we register_meta for all decompositions (except detach, that decomp is wrong lol), and then update all the necessary sites to make the test pass. Signed-off-by: Edward Z. Yang <ezyangfb.com> Pull Request resolved: https://github.com/pytorch/pytorch/pull/77477 Approved by: https://github.com/zou3519