code: def make_identity_transform_fn(context_feature_names):
      """Returns transform fn that split the features.
  
        The make_identity_transform_fn generates a transform_fn which handles only
        non-prefixed features. The per-example features need to have shape
        [batch_size, input_size, ...] and the context features need to have shape
        [batch_size, ...].
  
      Args:
        context_feature_names: A list of strings representing the context feature
          names.
  
      Returns:
        An identity transform function that splits into context and per example
        features.
      """
  
      def _transform_fn(features, mode):
          """Splits the features into context and per-example features."""
          del mode
          context_features = {
              name: feature
              for name, feature in six.iteritems(features)
              if name in context_feature_names
          }
  
          per_example_features = {
              name: feature
              for name, feature in six.iteritems(features)
              if name not in context_feature_names
          }
  
          return context_features, per_example_features
  
      return _transform_fn
  
file_path: ranking/tensorflow_ranking/python/feature.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import six
  import tensorflow
  from tensorflow import estimator
  from tensorflow.python.feature_column import feature_column_lib
  from tensorflow_ranking.python import utils
label_desc: Use image node_id 1 for calling a global function with example usage: make_identity_transform_fn(context_feature_names) and returns: _transform_fn, context_features,  per_example_features