code: def forward(self, x):
      x = F.relu(self.conv1(x))  # input(3, 32, 32) output(16, 28, 28)
      x = self.pool1(x)  # output(16, 14, 14)
      x = F.relu(self.conv2(x))  # output(32, 10, 10)
      x = self.pool2(x)  # output(32, 5, 5)
      x = x.view(-1, 32 * 5 * 5)  # output(32*5*5)
      x = F.relu(self.fc1(x))  # output(120)
      x = F.relu(self.fc2(x))  # output(84)
      x = self.fc3(x)  # output(10)
      return x
  
imports: import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the LeNet obj's underlying member method code with example usage: obj.forward(x) and returns: x