code: def _multiple_styles(input_image, which_styles, output_dir):
      """Stylizes image into a linear combination of styles and writes to disk."""
      with tf.Graph().as_default(), tf.Session() as sess:
          mixture = _style_mixture(which_styles, FLAGS.num_styles)
          stylized_images = model.transform(
              input_image,
              alpha=FLAGS.alpha,
              normalizer_fn=ops.weighted_instance_norm,
              normalizer_params={
                  "weights": tf.constant(mixture),
                  "num_categories": FLAGS.num_styles,
                  "center": True,
                  "scale": True,
              },
          )
          _load_checkpoint(sess, FLAGS.checkpoint)
  
          stylized_image = stylized_images.eval()
          image_utils.save_np_image(
              stylized_image,
              os.path.join(
                  output_dir,
                  "%s_%s.png"
                  % (
                      FLAGS.output_basename,
                      _describe_style(which_styles),
                  ),
              ),
          )
  
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 5 for calling a global function with example usage: _multiple_styles(input_image, which_styles, output_dir) without return types