code: def clone_initializer(initializer):
      # Keras initializer is going to be stateless, which mean reusing the same
      # initializer will produce same init value when the shapes are the same.
      if isinstance(initializer, tf.keras.initializers.Initializer):
          return initializer.__class__.from_config(
              initializer.get_config()
          )
      # When the input is string/dict or other serialized configs, caller will
      # create a new keras Initializer instance based on that, and we don't need to
      # do anything
      return initializer
  
file_path: agents/tf_agents/networks/utils.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import typing
  import numpy
  import tensorflow
  from tf_agents.keras_layers import permanent_variable_rate_dropout
  from tf_agents.typing import types
  from tf_agents.utils import composite
label_desc: Use image node_id 3 for calling a global function with example usage: clone_initializer(initializer) and returns: initializer, initializer