code: def format_data(data):
      # setup input data
      x_input = data[0]
      mels = data[1]
      y_coarse = data[2]
  
      # dispatch data to GPU
      if use_cuda:
          x_input = x_input.cuda(non_blocking=True)
          mels = mels.cuda(non_blocking=True)
          y_coarse = y_coarse.cuda(non_blocking=True)
  
      return x_input, mels, y_coarse
  
imports: import argparse
  import os
  import sys
  import traceback
  import time
  import glob
  import random
  import torch
  from torch.utils.data import DataLoader
  from TTS.tts.utils.visual import plot_spectrogram
  from TTS.utils.audio import AudioProcessor
  from TTS.utils.radam import RAdam
  from TTS.utils.io import copy_model_files, load_config
  from TTS.utils.training import setup_torch_training_env
  from TTS.utils.console_logger import ConsoleLogger
  from TTS.utils.tensorboard_logger import TensorboardLogger
  from TTS.utils.generic_utils import KeepAverage, count_parameters, create_experiment_folder, get_git_branch, remove_experiment_folder, set_init_dict
  from TTS.vocoder.datasets.wavernn_dataset import WaveRNNDataset
  from TTS.vocoder.datasets.preprocess import load_wav_data, load_wav_feat_data
  from TTS.vocoder.utils.distribution import discretized_mix_logistic_loss, gaussian_loss
  from TTS.vocoder.utils.generic_utils import setup_wavernn
  from TTS.vocoder.utils.io import save_best_model, save_checkpoint
label_desc: Use image node_id 2 for calling a global function with example usage: format_data(data) and returns: x_input,  mels,  y_coarse