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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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31
tests/test_fx/test_meta/test_backward.py
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@@ -23,31 +23,40 @@ tm_models = [
]
tmm_models = [
tmm.resnest.resnest50d, tmm.beit.beit_base_patch16_224, tmm.cait.cait_s24_224, tmm.efficientnet.efficientnetv2_m,
tmm.resmlp_12_224, tmm.vision_transformer.vit_base_patch16_224, tmm.deit_base_distilled_patch16_224,
tmm.convnext.convnext_base, tmm.vgg.vgg11, tmm.dpn.dpn68, tmm.densenet.densenet121, tmm.rexnet.rexnet_100,
tmm.swin_transformer.swin_base_patch4_window7_224
tmm.resnest.resnest50d,
tmm.beit.beit_base_patch16_224,
tmm.cait.cait_s24_224,
tmm.efficientnet.efficientnetv2_m,
tmm.resmlp_12_224,
tmm.vision_transformer.vit_base_patch16_224,
tmm.deit_base_distilled_patch16_224,
tmm.convnext.convnext_base,
tmm.vgg.vgg11,
tmm.dpn.dpn68,
tmm.densenet.densenet121,
tmm.rexnet.rexnet_100,
tmm.swin_transformer.swin_base_patch4_window7_224,
]
@pytest.mark.skipif(not is_compatible_with_meta(), reason='torch version is lower than 1.12.0')
@pytest.mark.skipif(not is_compatible_with_meta(), reason="torch version is lower than 1.12.0")
@clear_cache_before_run()
def test_torchvision_models():
for m in tm_models:
model = m()
data = torch.rand(100000, 3, 224, 224, device='meta')
model(MetaTensor(data, fake_device=torch.device('cpu'))).sum().backward()
data = torch.rand(100000, 3, 224, 224, device="meta")
model(MetaTensor(data, fake_device=torch.device("cpu"))).sum().backward()
@pytest.mark.skipif(not is_compatible_with_meta(), reason='torch version is lower than 1.12.0')
@pytest.mark.skipif(not is_compatible_with_meta(), reason="torch version is lower than 1.12.0")
@clear_cache_before_run()
def test_timm_models():
for m in tmm_models:
model = m()
data = torch.rand(100000, 3, 224, 224, device='meta')
model(MetaTensor(data, fake_device=torch.device('cpu'))).sum().backward()
data = torch.rand(100000, 3, 224, 224, device="meta")
model(MetaTensor(data, fake_device=torch.device("cpu"))).sum().backward()
if __name__ == '__main__':
if __name__ == "__main__":
test_torchvision_models()
test_timm_models()