code: def get(identifier):
      """Retrieve a Keras initializer by the identifier.
  
      The `identifier` may be the string name of a initializers function or class (
      case-sensitively).
  
      >>> identifier = 'Ones'
      >>> tf.keras.initializers.deserialize(identifier)
      <...keras.initializers.initializers_v2.Ones...>
  
      You can also specify `config` of the initializer to this function by passing
      dict containing `class_name` and `config` as an identifier. Also note that the
      `class_name` must map to a `Initializer` class.
  
      >>> cfg = {'class_name': 'Ones', 'config': {}}
      >>> tf.keras.initializers.deserialize(cfg)
      <...keras.initializers.initializers_v2.Ones...>
  
      In the case that the `identifier` is a class, this method will return a new
      instance of the class by its constructor.
  
      Args:
        identifier: String or dict that contains the initializer name or
          configurations.
  
      Returns:
        Initializer instance base on the input identifier.
  
      Raises:
        ValueError: If the input identifier is not a supported type or in a bad
          format.
      """
  
      if identifier is None:
          return None
      if isinstance(identifier, dict):
          return deserialize(identifier)
      elif isinstance(identifier, str):
          identifier = str(identifier)
          return deserialize(identifier)
      elif callable(identifier):
          if inspect.isclass(identifier):
              identifier = identifier()
          return identifier
      else:
          raise ValueError(
              "Could not interpret initializer identifier: "
              + str(identifier)
          )
  
file_path: tensorflow-upstream/tensorflow/python/keras/initializers/__init__.py
imports: import threading
  from tensorflow.python import tf2
  from tensorflow.python.keras.initializers import initializers_v1
  from tensorflow.python.keras.initializers import initializers_v2
  from tensorflow.python.keras.utils import generic_utils
  from tensorflow.python.keras.utils import tf_inspect
  from tensorflow.python.ops import init_ops
label_desc: Use image node_id 4 for calling a global function with example usage: get(identifier) and returns: None, deserialize, deserialize, identifier