ptrblck:

self.features3 = nn.Sequential( nn.Linear(10, 5), nn.ReLU(), ) self.classifier = nn.Linear(1281283 + 32323 + 5, 4) def forward(self, x1, x2, x3):


Hi, I have a simple question.
After I implement such a multi-input model, with 3 inputs and 1 output.
How should I do the loss.backward() operation?
Is it the same as usual if all the parameters’ requires_grad = True?