| 143 | |
| 144 | class AttnBlock(nn.Module): |
| 145 | def __init__(self, in_channels): |
| 146 | super().__init__() |
| 147 | self.in_channels = in_channels |
| 148 | |
| 149 | self.norm = Normalize(in_channels) |
| 150 | self.q = torch.nn.Conv2d(in_channels, in_channels, kernel_size=1, stride=1, padding=0) |
| 151 | self.k = torch.nn.Conv2d(in_channels, in_channels, kernel_size=1, stride=1, padding=0) |
| 152 | self.v = torch.nn.Conv2d(in_channels, in_channels, kernel_size=1, stride=1, padding=0) |
| 153 | self.proj_out = torch.nn.Conv2d(in_channels, in_channels, kernel_size=1, stride=1, padding=0) |
| 154 | |
| 155 | def attention(self, h_: torch.Tensor) -> torch.Tensor: |
| 156 | h_ = self.norm(h_) |