text: import argparse
  
  import tensorflow as tf
  
  from model import parse_images, TransposeCNN
  
  if __name__ == '__main__':
      parser = argparse.ArgumentParser()
      parser.add_argument("--n_files", type=int, default=10000)
      parser.add_argument("--n_epochs", type=int, default=100)
      parser.add_argument("--batch_size", type=int, default=64)
      args = parser.parse_args()
      
      # Restraint GPU usage
      config = tf.compat.v1.ConfigProto()
      config.gpu_options.per_process_gpu_memory_fraction = 0.7
      tf.compat.v1.keras.backend.set_session(tf.compat.v1.Session(config=config))
      
      # Load in datafiles
      img_names = [f"sample_{i}" for i in range(1, args.n_files + 1)]
      
      # Fetch image data (both input features as true values)
      features, values = parse_images(img_names)
      
      # Model
      model = TransposeCNN()
      
      # Train the model
      model.train(
              n_epoch=args.n_epochs,
              features=features,
              values=values,
              batch_size=args.batch_size,
      )
  