code: def __init__(self):
      super().__init__()
      self.conv1 = nn.Conv2d(1, 20, 5, 1)
      self.conv2 = nn.Conv2d(20, 50, 5, 1)
      self.fc1 = nn.Linear(4 * 4 * 50, 500)
      self.fc2 = nn.Linear(500, 10)
  
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 1 to create a new Net object from inherited base classes: Module with example: obj = Net()