Apply adaptation layers. # here is list of three levels of features
(self, features: List[torch.tensor])
| 50 | self.add_module("adapt_layer_{}".format(i), layer) # ex: adapt_layer_0 |
| 51 | |
| 52 | def forward(self, features: List[torch.tensor]): |
| 53 | """Apply adaptation layers. # here is list of three levels of features |
| 54 | """ |
| 55 | |
| 56 | for i, _ in enumerate(features): |
| 57 | features[i] = getattr(self, "adapt_layer_{}".format(i))(features[i]) |
| 58 | return features |
| 59 | |
| 60 | class EfficientNetB3(nn.Module): |
| 61 | ''' DFNet with EB3 backbone ''' |
nothing calls this directly
no outgoing calls
no test coverage detected