class_docstr: ### Model definition
code: def forward(self, x: torch.Tensor):
      x = F.relu(self.bn1(self.conv1(x)))
      x = F.max_pool2d(x, 2, 2)
      x = F.relu(self.bn2(self.conv2(x)))
      x = F.max_pool2d(x, 2, 2)
      x = x.view(-1, 4 * 4 * 50)
      x = F.relu(self.bn3(self.fc1(x)))
      return self.fc2(x)
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/normalization/batch_norm/mnist.py
imports: import torch.nn
  import torch.nn.functional
  import torch.utils.data
  from labml import experiment
  from labml.configs import option
  from labml_helpers.module import Module
  from labml_nn.experiments.mnist import MNISTConfigs
  from labml_nn.normalization.batch_norm import BatchNorm
label_desc: Use image node_id 2 for calling the Model obj's underlying member method code with example usage: obj.forward(x) and returns: self