code: def __call__(self, x: torch.Tensor):
      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)
  
imports: import torch.nn
  import torch.nn.functional
  import torch.utils.data
  from labml import experiment, tracker
  from labml.configs import option
  from labml.utils import pytorch
  from labml_helpers.datasets.mnist import MNISTConfigs
  from labml_helpers.device import DeviceConfigs
  from labml_helpers.metrics.accuracy import Accuracy
  from labml_helpers.module import Module
  from labml_helpers.seed import SeedConfigs
  from labml_helpers.train_valid import TrainValidConfigs, BatchIndex, hook_model_outputs
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.__call__(x) and returns: self