| 94 | |
| 95 | |
| 96 | class Block(nn.Module): |
| 97 | def __init__(self, dim, dim_out, groups=32, dropout=0): |
| 98 | super().__init__() |
| 99 | self.block = nn.Sequential( |
| 100 | # nn.BatchNorm2d(dim), |
| 101 | nn.GroupNorm(groups, dim), |
| 102 | # LayerNorm2d(dim), |
| 103 | Swish(), |
| 104 | nn.Dropout(dropout) if dropout != 0 else nn.Identity(), |
| 105 | nn.Conv2d(dim, dim_out, 3, padding=1), |
| 106 | ) |
| 107 | |
| 108 | def forward(self, x): |
| 109 | return self.block(x) |
| 110 | |
| 111 | |
| 112 | class ResnetBlock(nn.Module): |