code: def complete_augmenter(
      img_tf, ann_tf, seed_tf, alpha_tf, output_height, output_width
  ):
      tf = _lazy_import_tensorflow()
      img_tf, ann_tf = tf.numpy_function(
          func=numpy_augmenter,
          inp=[img_tf, ann_tf, seed_tf],
          Tout=[tf.float32, tf.float32],
      )
      img_tf, ann_tf = color_augmenter(img_tf, ann_tf, alpha_tf[0:3])
      img_tf, ann_tf = hue_augmenter(img_tf, ann_tf, alpha_tf[3:4])
      img_tf, ann_tf = resize_augmenter(
          img_tf, ann_tf, (output_height, output_width)
      )
      return img_tf, ann_tf
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import numpy
  from PIL import Image
  import turicreate.toolkits._tf_utils
  import turicreate
  from turicreate._deps.minimal_package import _minimal_package_import_check
label_desc: Use image node_id 10 for calling a global function with example usage: complete_augmenter(img_tf, ann_tf, seed_tf, alpha_tf, output_height, output_width) and returns: img_tf,  ann_tf