(self, in_channels)
| 38 | |
| 39 | class AttnBlock(nn.Module): |
| 40 | def __init__(self, in_channels): |
| 41 | super().__init__() |
| 42 | self.in_channels = in_channels |
| 43 | |
| 44 | self.norm = Normalize(in_channels) |
| 45 | self.q = torch.nn.Conv2d(in_channels, |
| 46 | in_channels, |
| 47 | kernel_size=1, |
| 48 | stride=1, |
| 49 | padding=0) |
| 50 | self.k = torch.nn.Conv2d(in_channels, |
| 51 | in_channels, |
| 52 | kernel_size=1, |
| 53 | stride=1, |
| 54 | padding=0) |
| 55 | self.v = torch.nn.Conv2d(in_channels, |
| 56 | in_channels, |
| 57 | kernel_size=1, |
| 58 | stride=1, |
| 59 | padding=0) |
| 60 | self.proj_out = torch.nn.Conv2d(in_channels, |
| 61 | in_channels, |
| 62 | kernel_size=1, |
| 63 | stride=1, |
| 64 | padding=0) |
| 65 | |
| 66 | def forward(self, x): |
| 67 | h_ = x |
nothing calls this directly
no test coverage detected