input: Write a python function to parse command-line arguments, load the model weights if available, and train the model based on the provided arguments.
  assert parse_and_train(['--nepoch', '10', '--version', '5', '--trunc', '10', '--limit', '200', '--adv', 'mse', '--train_baseline']) == 'Training the baseline model and adversarial stack with mse loss'
  assert parse_and_train(['--nepoch', '15', '--version', '2', '--trunc', '8', '--limit', '150', '--adv', 'emd']) == 'Training the baseline model and adversarial stack with emd loss'
  assert parse_and_train(['--nepoch', '25', '--version', '3', '--trunc', '6', '--limit', '100']) == 'Training the baseline model only'
output: def parse_and_train(args):
      import argparse
  
      parser = argparse.ArgumentParser(description='Train the model based on provided arguments')
      parser.add_argument('--nepoch', type=int, required=True, help='Number of epochs')
      parser.add_argument('--version', type=int, required=True, help='Model version')
      parser.add_argument('--trunc', type=int, required=True, help='Truncation')
      parser.add_argument('--limit', type=int, required=True, help='Limit')
      parser.add_argument('--adv', type=str, choices=['mse', 'emd'], help='Adversarial loss type')
      parser.add_argument('--train_baseline', action='store_true', help='Train baseline model')
  
      parsed_args = parser.parse_args(args)
  
      if parsed_args.train_baseline:
          if parsed_args.adv:
              return f'Training the baseline model and adversarial stack with {parsed_args.adv} loss'
          else:
              return 'Training the baseline model only'
      else:
          return 'Training the baseline model only'