code: def annotate_asset(asset_key: str, asset_filename: str):
      """Creates mapping between user-defined keys and SavedModel assets.
  
      This mapping is made available in `BeamDatasetMetadata` and is also used to
      resolve vocabularies in `tft.TFTransformOutput`.
  
      Note: multiple mappings for the same key will overwrite the previous one.
  
      Args:
        asset_key: The key to associate with the asset.
        asset_filename: The filename as it appears within the assets/ subdirectory.
          Must be sanitized and complete (e.g. include the tfrecord.gz for suffix
          appropriate files).
      """
      tf.compat.v1.add_to_collection(_ASSET_KEY_COLLECTION, asset_key)
      tf.compat.v1.add_to_collection(
          _ASSET_FILENAME_COLLECTION, asset_filename
      )
  
file_path: transform/tensorflow_transform/annotators.py
imports: import contextlib
  import os
  from typing import Callable, List, Optional
  import tensorflow
  from tensorflow_transform.graph_context import TFGraphContext
  from tensorflow_transform.keras_lib import tf_keras
  from tensorflow.python.trackable import base
label_desc: Use image node_id 7 for calling a global function with example usage: annotate_asset(asset_key, asset_filename) without return types