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Ensure Conv2D and Conv3D's kernel sizes aren't trimmed (#1852)

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Before the change, this snippet:

```
print(nn.Conv1d(1, 32, 3, padding=1))
print(nn.Conv2d(1, 32, (3, 3), padding=1))
print(nn.Conv3d(1, 32, (3, 3, 3), padding=1))
```

would output:

```
Conv1d(1, 32, kernel_size=3, stride=1, padding=1, dilation=1, groups=1, bias=True)
Conv2d(1, 32, kernel_size=(3,), stride=(1, 1), padding=(1, 1), dilation=1, groups=1, bias=True)
Conv3d(1, 32, kernel_size=(3, 3), stride=(1, 1, 1), padding=(1, 1, 1), dilation=1, bias=True)
```

After the change, the output will be:

```
Conv1d(1, 32, kernel_size=3, stride=1, padding=1, dilation=1, groups=1, bias=True)
Conv2d(1, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), dilation=1, groups=1, bias=True)
Conv3d(1, 32, kernel_size=(3, 3, 3), stride=(1, 1, 1), padding=(1, 1, 1), dilation=1, bias=True)
```
This commit is contained in:
Franck Verrot 2025-02-10 06:27:01 -08:00 committed by GitHub
parent 9eb7d7362f
commit 7df3f792a2
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1 changed files with 2 additions and 2 deletions
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python/mlx/nn/layers/convolution.py
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@ -147,7 +147,7 @@ class Conv2d(Module):
def _extra_repr(self):
return (
f"{self.weight.shape[-1]}, {self.weight.shape[0]}, "
f"kernel_size={self.weight.shape[1:2]}, stride={self.stride}, "
f"kernel_size={self.weight.shape[1:3]}, stride={self.stride}, "
f"padding={self.padding}, dilation={self.dilation}, "
f"groups={self.groups}, "
f"bias={'bias' in self}"
@ -220,7 +220,7 @@ class Conv3d(Module):
def _extra_repr(self):
return (
f"{self.weight.shape[-1]}, {self.weight.shape[0]}, "
f"kernel_size={self.weight.shape[1:3]}, stride={self.stride}, "
f"kernel_size={self.weight.shape[1:4]}, stride={self.stride}, "
f"padding={self.padding}, dilation={self.dilation}, "
f"bias={'bias' in self}"
)