(self, inputs: List[Tensor])
| 45 | self.memory_efficient = memory_efficient |
| 46 | |
| 47 | def bn_function(self, inputs: List[Tensor]) -> Tensor: |
| 48 | concated_features = torch.cat(inputs, 1) |
| 49 | bottleneck_output = self.conv1(self.relu1(self.norm1(concated_features))) # noqa: T484 |
| 50 | return bottleneck_output |
| 51 | |
| 52 | # todo: rewrite when torchscript supports any |
| 53 | def any_requires_grad(self, input: List[Tensor]) -> bool: |