code: def _make_feature_value_fn(dtype):
      """Return a function to extract the typed value from the feature.
  
      For performance reasons it is preferred to have the feature value fn
      constructed once (for each handler).
  
      Args:
        dtype: The type of the Tensorflow feature.
  
      Returns:
        A function to extract the value field from the feature depending on dtype.
      """
      if dtype.is_integer:
          return lambda feature: feature.int64_list.value
  
      if dtype.is_floating:
          return lambda feature: feature.float_list.value
  
      return lambda feature: feature.bytes_list.value
  
file_path: transform/tensorflow_transform/coders/example_proto_coder.py
imports: import numpy
  import tensorflow
  from tensorflow_transform.tf_metadata import schema_utils
label_desc: Use image node_id 2 for calling a global function with example usage: _make_feature_value_fn(dtype) and returns: function, function, function