code: def main():
      """
      ### Train StyleGAN2
      """
  
      # Create an experiment
      experiment.create(name="stylegan2")
      # Create configurations object
      configs = Configs()
  
      # Set configurations and override some
      experiment.configs(
          configs,
          {
              "device.cuda_device": 0,
              "image_size": 64,
              "log_generated_interval": 200,
          },
      )
  
      # Initialize
      configs.init()
      # Set models for saving and loading
      experiment.add_pytorch_models(
          mapping_network=configs.mapping_network,
          generator=configs.generator,
          discriminator=configs.discriminator,
      )
  
      # Start the experiment
      with experiment.start():
          # Run the training loop
          configs.train()
  
imports: import math
  from pathlib import Path
  from typing import Iterator, Tuple
  import torch
  import torch.utils.data
  import torchvision
  from PIL import Image
  from labml import tracker, lab, monit, experiment
  from labml.configs import BaseConfigs
  from labml_helpers.device import DeviceConfigs
  from labml_helpers.train_valid import ModeState, hook_model_outputs
  from labml_nn.gan.stylegan import Discriminator, Generator, MappingNetwork, GradientPenalty, PathLengthPenalty
  from labml_nn.gan.wasserstein import DiscriminatorLoss, GeneratorLoss
  from labml_nn.utils import cycle_dataloader
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types