code: def forward(self, x):
      x = F.relu(self.conv1(x))
      x = F.max_pool2d(x, 2, 2)
      x = F.relu(self.conv2(x))
      x = F.max_pool2d(x, 2, 2)
      x = x.view(-1, 4 * 4 * 50)
      x = F.relu(self.fc1(x))
      return self.fc2(x)
  
file_path: labml/samples/pytorch/mnist/a_no_labml.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  import torch.utils.data
  from torchvision import datasets, transforms
  from labml import lab
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.forward(x) and returns: self