(self, input)
| 49 | nn.init.uniform_(self.encoder.weight, -0.1, 0.1) |
| 50 | |
| 51 | def forward(self, input): |
| 52 | if torch.accelerator.is_available(): |
| 53 | device = torch.accelerator.current_accelerator() |
| 54 | input = input.to(device) |
| 55 | return self.drop(self.encoder(input)).cpu() |
| 56 | |
| 57 | |
| 58 | class Decoder(nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected