code: def _multiple_images(input_image, which_styles, output_dir):
      """Stylizes an image into a set of styles and writes them to disk."""
      with tf.Graph().as_default(), tf.Session() as sess:
          stylized_images = model.transform(
              tf.concat(
                  [input_image for _ in range(len(which_styles))], 0
              ),
              alpha=FLAGS.alpha,
              normalizer_params={
                  "labels": tf.constant(which_styles),
                  "num_categories": FLAGS.num_styles,
                  "center": True,
                  "scale": True,
              },
          )
          _load_checkpoint(sess, FLAGS.checkpoint)
  
          stylized_images = stylized_images.eval()
          for which, stylized_image in zip(
              which_styles, stylized_images
          ):
              image_utils.save_np_image(
                  stylized_image[None, ...],
                  "{}/{}_{}.png".format(
                      output_dir, FLAGS.output_basename, which
                  ),
              )
  
file_path: magenta/magenta/models/image_stylization/image_stylization_transform.py
imports: import ast
  import os
  from magenta.models.image_stylization import image_utils
  from magenta.models.image_stylization import model
  from magenta.models.image_stylization import ops
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 4 for calling a global function with example usage: _multiple_images(input_image, which_styles, output_dir) without return types