[ONNX] Auto test based on OpInfo (#86182)
This change introduces a mechanism to test onnx export based on sample inputs registered in OpInfo, similar to how MPS and other components of pytorch are tested. It provides test coverage on ops and dtypes previously unattainable with manually created test models. This is the best way for us to discover gaps in the exporter support, especially for ops with partial existing support.
This test is adapted from https://github.com/pytorch/pytorch/blob/master/test/test_mps.py
This PR also
- Update sqrt to support integer inputs to match pytorch behavior
- Add pytest-subtests for unittest subtests support in the new test file
I only enabled very few ops: `t`, `ceil` and `sqrt` because otherwise too many things will fail due to (1) unsupported dtypes in the exporter (2) unimplemented dtype support in onnxruntime (3) unexpected input to verification.verify.
Subsequent PRs should improve `verification.verify` first for it to accept any legal input to a pytorch model, then incrementally fix the symbolic functions to enable more test cases.
Fixes #85363
Design #88118
Pull Request resolved: https://github.com/pytorch/pytorch/pull/86182
Approved by: https://github.com/BowenBao
