code: def get_validation_dataset(
      batch_size=128, dataset="cifar10", split="10%"
  ):
      """Returns a tf.data.Dataset with preprocessed and batched validation data."""
      ds = tfds.load(dataset, split=f"train[-{split}:]")
      return (
          ds.map(convert_to_tuples)
          .map(normalize_image)
          .batch(batch_size)
      )
  
file_path: neural-structured-learning/research/multi_representation_adversary/multi_representation_adversary/data.py
imports: import gin
  import tensorflow.compat.v2
  import tensorflow_datasets
label_desc: Use image node_id 5 for calling a global function with example usage: get_validation_dataset(batch_size, dataset, split) and returns: ds