code: def parse_example(serialized_example):
      """Parses feature dictionary from the `serialized_example` proto.
  
      Args:
        serialized_example: The proto of the current example.
  
      Returns:
        A parsed example as dict with several elements.
      """
      feature_description = {
          "chrm_img": tf.io.FixedLenFeature(
              [], tf.string, default_value=""
          ),
          "meta_img": tf.io.FixedLenFeature(
              [], tf.string, default_value=""
          ),
          "label": tf.io.FixedLenFeature(
              [], tf.string, default_value=""
          ),
          "chrm_path": tf.io.FixedLenFeature(
              [], tf.string, default_value=""
          ),
      }
  
      features = tf.io.parse_single_example(
          serialized_example, feature_description
      )
  
      return features
  
file_path: scenic/scenic/projects/tasseo/dataset_utils.py
imports: from absl import logging
  import jax
  import numpy
  import tensorflow
label_desc: Use image node_id 1 for calling a global function with example usage: parse_example(serialized_example) and returns: features