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Enable UFMT on test_decomp.py, test_expanded_weights.py and some files (#125117)

Browse Source 
Part of: #123062

Ran lintrunner on:

- test/test_decomp.py
- test/test_deploy.py
- test/test_determination.py
- test/test_dlpack.py
- test/test_dynamic_shapes.py
- test/test_expanded_weights.py

Detail:

```bash
$ lintrunner -a --take UFMT --all-files
ok No lint issues.
Successfully applied all patches.
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/125117
Approved by: https://github.com/jansel
This commit is contained in:
Yuanhao Ji
2024-05-07 02:36:36 +00:00
committed by PyTorch MergeBot
parent 48b6c8dbc3
commit c165a8e71d
7 changed files with 1211 additions and 511 deletions
Download Patch File Download Diff File Expand all files Collapse all files

68
test/test_dlpack.py
View File

@ -2,11 +2,16 @@
import torch
from torch.testing import make_tensor
from torch.testing._internal.common_utils import TestCase, run_tests, IS_JETSON
from torch.testing._internal.common_device_type import (
instantiate_device_type_tests, onlyCUDA, dtypes, skipMeta, skipCUDAIfRocm,
onlyNativeDeviceTypes)
dtypes,
instantiate_device_type_tests,
onlyCUDA,
onlyNativeDeviceTypes,
skipCUDAIfRocm,
skipMeta,
)
from torch.testing._internal.common_dtype import all_types_and_complex_and
from torch.testing._internal.common_utils import IS_JETSON, run_tests, TestCase
from torch.utils.dlpack import from_dlpack, to_dlpack
@ -15,7 +20,16 @@ class TestTorchDlPack(TestCase):
@skipMeta
@onlyNativeDeviceTypes
@dtypes(*all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool, torch.uint16, torch.uint32, torch.uint64))
@dtypes(
*all_types_and_complex_and(
torch.half,
torch.bfloat16,
torch.bool,
torch.uint16,
torch.uint32,
torch.uint64,
)
)
def test_dlpack_capsule_conversion(self, device, dtype):
x = make_tensor((5,), dtype=dtype, device=device)
z = from_dlpack(to_dlpack(x))
@ -23,7 +37,16 @@ class TestTorchDlPack(TestCase):
@skipMeta
@onlyNativeDeviceTypes
@dtypes(*all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool, torch.uint16, torch.uint32, torch.uint64))
@dtypes(
*all_types_and_complex_and(
torch.half,
torch.bfloat16,
torch.bool,
torch.uint16,
torch.uint32,
torch.uint64,
)
)
def test_dlpack_protocol_conversion(self, device, dtype):
x = make_tensor((5,), dtype=dtype, device=device)
z = from_dlpack(x)
@ -62,7 +85,16 @@ class TestTorchDlPack(TestCase):
@skipMeta
@onlyNativeDeviceTypes
@dtypes(*all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool, torch.uint16, torch.uint32, torch.uint64))
@dtypes(
*all_types_and_complex_and(
torch.half,
torch.bfloat16,
torch.bool,
torch.uint16,
torch.uint32,
torch.uint64,
)
)
def test_from_dlpack(self, device, dtype):
x = make_tensor((5,), dtype=dtype, device=device)
y = torch.from_dlpack(x)
@ -70,7 +102,16 @@ class TestTorchDlPack(TestCase):
@skipMeta
@onlyNativeDeviceTypes
@dtypes(*all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool, torch.uint16, torch.uint32, torch.uint64))
@dtypes(
*all_types_and_complex_and(
torch.half,
torch.bfloat16,
torch.bool,
torch.uint16,
torch.uint32,
torch.uint64,
)
)
def test_from_dlpack_noncontinguous(self, device, dtype):
x = make_tensor((25,), dtype=dtype, device=device).reshape(5, 5)
@ -113,7 +154,16 @@ class TestTorchDlPack(TestCase):
@skipMeta
@onlyNativeDeviceTypes
@dtypes(*all_types_and_complex_and(torch.half, torch.bfloat16, torch.bool, torch.uint16, torch.uint32, torch.uint64))
@dtypes(
*all_types_and_complex_and(
torch.half,
torch.bfloat16,
torch.bool,
torch.uint16,
torch.uint32,
torch.uint64,
)
)
def test_from_dlpack_dtype(self, device, dtype):
x = make_tensor((5,), dtype=dtype, device=device)
y = torch.from_dlpack(x)
@ -204,5 +254,5 @@ class TestTorchDlPack(TestCase):
instantiate_device_type_tests(TestTorchDlPack, globals())
if __name__ == '__main__':
if __name__ == "__main__":
run_tests()