| 52 | |
| 53 | class InvertedConvolution(nn.Module): |
| 54 | def __init__(self, in_channels, out_channels, kernel_size, padding='same', bias=True): |
| 55 | super().__init__() |
| 56 | |
| 57 | self.conv1 = nn.Conv2d(in_channels=in_channels, out_channels=out_channels, |
| 58 | kernel_size=1, padding=0, stride=1, groups=1, bias=bias) |
| 59 | |
| 60 | self.conv2 = nn.Conv2d(in_channels=out_channels, out_channels=out_channels, kernel_size=kernel_size, |
| 61 | padding=padding, stride=1, groups=out_channels, bias=bias) |
| 62 | |
| 63 | def forward(self, x): |
| 64 | x = self.conv1(x) |