(self, X: Tensor)
| 61 | self.out_layer = nn.Sequential(*out_layer) |
| 62 | |
| 63 | def forward(self, X: Tensor) -> Tensor: |
| 64 | for layer in self.hidden_layers: |
| 65 | X = layer(X) |
| 66 | |
| 67 | Y = self.out_layer(X) |
| 68 | return Y.squeeze(1) |
| 69 | |
| 70 | |
| 71 | class MLP_Block(nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected