Performance, Pytorch, Deep Learning, Artificial Intelligence, Tensorboard.
hidden.append(nn.ReLU()) self.hidden = nn.Sequential(*hidden) self.conv_out = nn.Conv2d(10, num_classes, 3, padding='same') def forward(self, x): x = F.relu(self.conv_in(x)) x = self.hidden(x) x = self.conv_out(x) return x To train our model we will use the standard cross-entropy loss with a few