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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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35
tests/test_analyzer/test_fx/test_mod_dir.py
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@@ -10,7 +10,6 @@ except:
class LinearModel(torch.nn.Module):
def __init__(self, in_features, out_features, bias):
super().__init__()
self.linear = torch.nn.Linear(in_features, out_features, bias=bias)
@@ -21,25 +20,14 @@ class LinearModel(torch.nn.Module):
class ConvModel(torch.nn.Module):
def __init__(self, in_channel, out_channels, kernel_size, bias) -> None:
super().__init__()
self.conv = torch.nn.Conv2d(in_channel,
out_channels,
kernel_size,
bias=bias,
padding=1,
stride=2,
dilation=2,
groups=3)
self.conv_transpose = torch.nn.ConvTranspose2d(out_channels,
out_channels,
kernel_size,
bias=bias,
padding=1,
stride=2,
dilation=2,
groups=3)
self.conv = torch.nn.Conv2d(
in_channel, out_channels, kernel_size, bias=bias, padding=1, stride=2, dilation=2, groups=3
)
self.conv_transpose = torch.nn.ConvTranspose2d(
out_channels, out_channels, kernel_size, bias=bias, padding=1, stride=2, dilation=2, groups=3
)
def forward(self, x):
x = self.conv(x)
@@ -48,7 +36,6 @@ class ConvModel(torch.nn.Module):
class AModel(torch.nn.Module):
def __init__(self, bias) -> None:
super().__init__()
self.linear_1 = LinearModel(3, 3, bias)
@@ -63,7 +50,7 @@ class AModel(torch.nn.Module):
return x
@pytest.mark.skipif(torch.__version__ < '1.12.0', reason='torch version < 12')
@pytest.mark.skipif(torch.__version__ < "1.12.0", reason="torch version < 12")
@clear_cache_before_run()
@parameterize("bias", [True, False])
@parameterize("bias_addition_split", [True, False])
@@ -71,11 +58,11 @@ class AModel(torch.nn.Module):
def test_mod_dir(bias, bias_addition_split, shape):
model = AModel(bias=bias)
x = torch.rand(shape)
gm = symbolic_trace(model, meta_args={'x': x}, bias_addition_split=bias_addition_split)
gm = symbolic_trace(model, meta_args={"x": x}, bias_addition_split=bias_addition_split)
for node in gm.graph.nodes:
assert len(node.meta['info'].mod_dir), f"{node} should have non-trivial ``mod_dir``."
print(node, node.meta['info'].mod_dir)
assert len(node.meta["info"].mod_dir), f"{node} should have non-trivial ``mod_dir``."
print(node, node.meta["info"].mod_dir)
if __name__ == '__main__':
if __name__ == "__main__":
test_mod_dir(bias=True, bias_addition_split=True, shape=(3, 3, 3))