Apply adaptation layers. # here is list of three levels of features
(self, features: List[torch.tensor])
| 64 | self.add_module("adapt_layer_{}".format(i), layer) # ex: adapt_layer_0 |
| 65 | |
| 66 | def forward(self, features: List[torch.tensor]): |
| 67 | """Apply adaptation layers. # here is list of three levels of features |
| 68 | """ |
| 69 | |
| 70 | for i, _ in enumerate(features): |
| 71 | features[i] = getattr(self, "adapt_layer_{}".format(i))(features[i]) |
| 72 | return features |
| 73 | |
| 74 | class DFNet(nn.Module): |
| 75 | ''' DFNet implementation ''' |
nothing calls this directly
no outgoing calls
no test coverage detected