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[misc] update pre-commit and run all files (#4752)

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* [misc] update pre-commit

* [misc] run pre-commit

* [misc] remove useless configuration files

* [misc] ignore cuda for clang-format
This commit is contained in:
Hongxin Liu
2023-09-19 14:20:26 +08:00
committed by GitHub
parent 3c6b831c26
commit 079bf3cb26
1268 changed files with 50037 additions and 38444 deletions
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36
tests/test_fx/test_tracer/test_patched_op.py
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@@ -33,38 +33,34 @@ def test_repeat_interleave():
data = torch.tensor([1, 2, 3])
materialized_output = torch.repeat_interleave(data, repeats=2)
repeat_interleave = partial(patch_fn, repeats=2)
meta_data = data.to('meta')
_assert_output_shape(data=meta_data,
patch_fn=repeat_interleave,
expect_exception=False,
output_shape=materialized_output.shape)
meta_data = data.to("meta")
_assert_output_shape(
data=meta_data, patch_fn=repeat_interleave, expect_exception=False, output_shape=materialized_output.shape
)
data = torch.tensor([[1, 2], [3, 4]])
materialized_output = torch.repeat_interleave(data, repeats=3, dim=1)
repeat_interleave = partial(patch_fn, repeats=3, dim=1)
meta_data = data.to('meta')
_assert_output_shape(data=meta_data,
patch_fn=repeat_interleave,
expect_exception=False,
output_shape=materialized_output.shape)
meta_data = data.to("meta")
_assert_output_shape(
data=meta_data, patch_fn=repeat_interleave, expect_exception=False, output_shape=materialized_output.shape
)
data = torch.tensor([[1, 2], [3, 4]])
materialized_output = torch.repeat_interleave(data, repeats=torch.tensor([1, 2]), dim=-1)
repeat_interleave = partial(patch_fn, repeats=torch.tensor([1, 2]), dim=-1)
meta_data = data.to('meta')
_assert_output_shape(data=meta_data,
patch_fn=repeat_interleave,
expect_exception=False,
output_shape=materialized_output.shape)
meta_data = data.to("meta")
_assert_output_shape(
data=meta_data, patch_fn=repeat_interleave, expect_exception=False, output_shape=materialized_output.shape
)
data = torch.tensor([[1, 2], [3, 4]])
materialized_output = torch.repeat_interleave(data, repeats=torch.tensor([1, 2]), dim=0)
repeat_interleave = partial(patch_fn, repeats=[1, 2], dim=0)
meta_data = data.to('meta')
_assert_output_shape(data=meta_data,
patch_fn=repeat_interleave,
expect_exception=True,
output_shape=materialized_output.shape)
meta_data = data.to("meta")
_assert_output_shape(
data=meta_data, patch_fn=repeat_interleave, expect_exception=True, output_shape=materialized_output.shape
)
@clear_cache_before_run()