Commit Graph

354 Commits

Author SHA1 Message Date
Elias Ellison
e0c65abd38 Revert D23568330: [pytorch][PR] Moves some of TestTorchMathOps to OpInfos
Test Plan: revert-hammer

Differential Revision:
D23568330 (a953a825cc)

Original commit changeset: 03e69fccdbfd

fbshipit-source-id: 04ec6843c5eb3c84ddf226dad0088172d9bed84d
2020-09-09 15:48:56 -07:00
Mike Ruberry
a953a825cc Moves some of TestTorchMathOps to OpInfos (#44277)
Summary:
This PR fixes three OpInfo-related bugs and moves some functions from TestTorchMathOps to be tested using the OpInfo pattern. The bugs are:

- A skip test path in test_ops.py incorrectly formatted its string argument
- Decorating the tests in common_device_type.py was incorrectly always applying decorators to the original test, not the op-specific variant of the test. This could cause the same decorator to be applied multiple times, overriding past applications.
- make_tensor was incorrectly constructing tensors in some cases

The functions moved are:

- asin
- asinh
- sinh
- acosh
- tan
- atan
- atanh
- tanh
- log
- log10
- log1p
- log2

In a follow-up PR more or all of the remaining functions in TestTorchMathOps will be refactored as OpInfo-based tests.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/44277

Reviewed By: ngimel

Differential Revision: D23568330

Pulled By: mruberry

fbshipit-source-id: 03e69fccdbfd560217c34ce4e9a5f20e10d05a5e
2020-09-09 09:41:03 -07:00
Thomas Viehmann
7c61f57bec test_ops: skipTest only takes a single argument (#44181)
Summary:
Fixes a broken skipTest from https://github.com/pytorch/pytorch/issues/43451, e.g. in the ROCm CI.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/44181

Reviewed By: ngimel

Differential Revision: D23568608

Pulled By: malfet

fbshipit-source-id: 557048bd5f0086ffac38d1c48255badb63869899
2020-09-07 18:32:59 -07:00
Mike Ruberry
665feda15b Adds opinfo-based autograd tests and (un)supported dtype tests (#43451)
Summary:
This PR adds a new test suite, test_ops.py, designed for generic tests across all operators with OpInfos. It currently has two kinds of tests:

- it validates that the OpInfo has the correct supported dtypes by verifying that unsupported dtypes throw an error and supported dtypes do not
- it runs grad and gradgrad checks on each op and its variants (method and inplace) that has an OpInfo

This is a significant expansion and simplification of the current autogenerated autograd tests, which spend considerable processing their inputs. As an alternative, this PR extends OpInfos with "SampleInputs" that are much easier to use. These sample inputs are analogous to the existing tuples in`method_tests()`.

Future PRs will extend OpInfo-based testing to other uses of `method_tests()`, like test_jit.py, to ensure that new operator tests can be implemented entirely using an OpInfo.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/43451

Reviewed By: albanD

Differential Revision: D23481723

Pulled By: mruberry

fbshipit-source-id: 0c2cdeacc1fdaaf8c69bcd060d623fa3db3d6459
2020-09-03 02:50:48 -07:00