code: def get_activation(identifier):
      """Maps a identifier to a Python function, e.g., "relu" => `tf.nn.relu`.
  
      It checks string first and if it is one of customized activation not in TF,
      the corresponding activation will be returned. For non-customized activation
      names and callable identifiers, always fallback to tf.keras.activations.get.
  
      Args:
        identifier: String name of the activation function or callable.
  
      Returns:
        A Python function corresponding to the activation function.
      """
      if isinstance(identifier, six.string_types):
          name_to_fn = {
              "gelu": activations.gelu,
              "simple_swish": activations.simple_swish,
              "hard_swish": activations.hard_swish,
              "identity": activations.identity,
          }
          identifier = str(identifier).lower()
          if identifier in name_to_fn:
              return tf.keras.activations.get(name_to_fn[identifier])
      return tf.keras.activations.get(identifier)
  
file_path: autodist/examples/benchmark/utils/tf_utils.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import six
  import tensorflow
  from utils import activations
label_desc: Use image node_id 4 for calling a global function with example usage: get_activation(identifier) and returns: tf, tf