(self, in_channels, with_conv)
| 88 | |
| 89 | class Upsample(nn.Module): |
| 90 | def __init__(self, in_channels, with_conv): |
| 91 | super().__init__() |
| 92 | self.with_conv = with_conv |
| 93 | if self.with_conv: |
| 94 | self.conv = nn.Conv2d(in_channels, in_channels, kernel_size=3, stride=1, padding=1) |
| 95 | |
| 96 | def forward(self, x): |
| 97 | x = nn.functional.interpolate(x, scale_factor=2.0, mode="nearest") |