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| author | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2022-06-05 21:18:56 +0200 | 
|---|---|---|
| committer | Gustaf Rydholm <gustaf.rydholm@gmail.com> | 2022-06-05 21:18:56 +0200 | 
| commit | 425af1bce8362efd97682a5042e76a60bfc28060 (patch) | |
| tree | a06bba00f825c0f7cb69a8df2f4d424af8070ef7 | |
| parent | 6e1ad65edd7cbb0f8eb7a48991e9f000f554761d (diff) | |
Remove depth wise conv class
| -rw-r--r-- | text_recognizer/networks/conformer/conv.py | 13 | ||||
| -rw-r--r-- | text_recognizer/networks/conformer/depth_wise_conv.py | 17 | 
2 files changed, 9 insertions, 21 deletions
diff --git a/text_recognizer/networks/conformer/conv.py b/text_recognizer/networks/conformer/conv.py index f031dc7..ac13f5d 100644 --- a/text_recognizer/networks/conformer/conv.py +++ b/text_recognizer/networks/conformer/conv.py @@ -4,7 +4,6 @@ from einops.layers.torch import Rearrange  from torch import nn, Tensor -from text_recognizer.networks.conformer.depth_wise_conv import DepthwiseConv1D  from text_recognizer.networks.conformer.glu import GLU @@ -21,12 +20,18 @@ class ConformerConv(nn.Module):          self.layers = nn.Sequential(              nn.LayerNorm(dim),              Rearrange("b n c -> b c n"), -            nn.Conv1D(dim, 2 * inner_dim, 1), +            nn.Conv1d(dim, 2 * inner_dim, 1),              GLU(dim=1), -            DepthwiseConv1D(inner_dim, inner_dim, kernel_size), +            nn.Conv1d( +                in_channels=inner_dim, +                out_channels=inner_dim, +                kernel_size=kernel_size, +                groups=inner_dim, +                padding="same", +            ),              nn.BatchNorm1d(inner_dim),              nn.Mish(inplace=True), -            nn.Conv1D(inner_dim, dim, 1), +            nn.Conv1d(inner_dim, dim, 1),              Rearrange("b c n -> b n c"),              nn.Dropout(dropout),          ) diff --git a/text_recognizer/networks/conformer/depth_wise_conv.py b/text_recognizer/networks/conformer/depth_wise_conv.py deleted file mode 100644 index 1dbd0b8..0000000 --- a/text_recognizer/networks/conformer/depth_wise_conv.py +++ /dev/null @@ -1,17 +0,0 @@ -"""Depthwise 1D convolution.""" -from torch import nn, Tensor - - -class DepthwiseConv1D(nn.Module): -    def __init__(self, in_channels: int, out_channels: int, kernel_size: int) -> None: -        super().__init__() -        self.conv = nn.Conv1d( -            in_channels=in_channels, -            out_channels=out_channels, -            kernel_size=kernel_size, -            groups=in_channels, -            padding="same", -        ) - -    def forward(self, x: Tensor) -> Tensor: -        return self.conv(x)  |