code: def _deserialize_nested_config(deserialize_fn, config):
      """Deserializes arbitrary Keras `config` using `deserialize_fn`."""
  
      def _is_single_object(obj):
          if isinstance(obj, dict) and "class_name" in obj:
              return True  # Serialized Keras object.
          if isinstance(obj, str):
              return True  # Serialized function or string.
          return False
  
      if config is None:
          return None
      if _is_single_object(config):
          return deserialize_fn(config)
      elif isinstance(config, dict):
          return {
              k: _deserialize_nested_config(deserialize_fn, v)
              for k, v in config.items()
          }
      elif isinstance(config, (tuple, list)):
          return [
              _deserialize_nested_config(deserialize_fn, obj)
              for obj in config
          ]
  
      raise ValueError("Saved configuration not understood.")
  
imports: import collections
  import copy
  import os
  from tensorflow.python.eager import def_function
  from tensorflow.python.keras import backend
  from tensorflow.python.keras import losses
  from tensorflow.python.keras import optimizer_v1
  from tensorflow.python.keras import optimizers
  from tensorflow.python.keras.engine import base_layer_utils
  from tensorflow.python.keras.utils import generic_utils
  from tensorflow.python.keras.utils import version_utils
  from tensorflow.python.keras.utils.io_utils import ask_to_proceed_with_overwrite
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import nest
label_desc: Use image node_id 8 for calling a global function with example usage: _deserialize_nested_config(deserialize_fn, config) and returns: False, None, deserialize_fn, True, True, unknown, unknown