code: def format_data(data):
      if isinstance(data[0], list):
          # setup input data
          c_G, x_G = data[0]
          c_D, x_D = data[1]
  
          # dispatch data to GPU
          if use_cuda:
              c_G = c_G.cuda(non_blocking=True)
              x_G = x_G.cuda(non_blocking=True)
              c_D = c_D.cuda(non_blocking=True)
              x_D = x_D.cuda(non_blocking=True)
  
          return c_G, x_G, c_D, x_D
  
      # return a whole audio segment
      co, x = data
      if use_cuda:
          co = co.cuda(non_blocking=True)
          x = x.cuda(non_blocking=True)
      return co, x, None, None
  
imports: import argparse
  import glob
  import os
  import sys
  import time
  import traceback
  from inspect import signature
  import torch
  from torch.utils.data import DataLoader
  from TTS.utils.audio import AudioProcessor
  from TTS.utils.console_logger import ConsoleLogger
  from TTS.utils.generic_utils import KeepAverage, count_parameters, create_experiment_folder, get_git_branch, remove_experiment_folder, set_init_dict
  from TTS.utils.io import copy_model_files, load_config
  from TTS.utils.radam import RAdam
  from TTS.utils.tensorboard_logger import TensorboardLogger
  from TTS.utils.training import setup_torch_training_env
  from TTS.vocoder.datasets.gan_dataset import GANDataset
  from TTS.vocoder.datasets.preprocess import load_wav_data, load_wav_feat_data
  from TTS.vocoder.layers.losses import DiscriminatorLoss, GeneratorLoss
  from TTS.vocoder.utils.generic_utils import plot_results, setup_discriminator, setup_generator
  from TTS.vocoder.utils.io import save_best_model, save_checkpoint
  from torch.nn.parallel import DistributedDataParallel
  from torch.utils.data.distributed import DistributedSampler
  from TTS.utils.distribute import init_distributed
label_desc: Use image node_id 2 for calling a global function with example usage: format_data(data) and returns: co,  x,  None,  None, c_G,  x_G,  c_D,  x_D