code: def gradual_training_scheduler(global_step, config):
      """Setup the gradual training schedule wrt number
      of active GPUs"""
      num_gpus = torch.cuda.device_count()
      if num_gpus == 0:
          num_gpus = 1
      new_values = None
      # we set the scheduling wrt num_gpus
      for values in config.gradual_training:
          if global_step * num_gpus >= values[0]:
              new_values = values
      return new_values[1], new_values[2]
  
file_path: TTS/TTS/utils/training.py
imports: import torch
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: gradual_training_scheduler(global_step, config) and returns: new_values,  new_values