(self, features, context = None, scale = None)
| 11 | self.super_resolution = super_resolution |
| 12 | self.num_prototypes = num_prototypes |
| 13 | def forward(self, features, context = None, scale = None): |
| 14 | if context is not None: |
| 15 | features = torch.cat((features, context), dim = 1) |
| 16 | stuff = self.layers[scale](features) |
| 17 | logits, context = stuff[:,:self.num_prototypes], stuff[:,self.num_prototypes:] |
| 18 | return logits, context |
| 19 | |
| 20 | class ConvRefiner(nn.Module): |
| 21 | def __init__( |
nothing calls this directly
no outgoing calls
no test coverage detected