code: def model_from_json(json_string, custom_objects=None):
      """Parses a JSON model configuration string and returns a model instance.
  
      Usage:
  
      >>> model = tf.keras.Sequential([
      ...     tf.keras.layers.Dense(5, input_shape=(3,)),
      ...     tf.keras.layers.Softmax()])
      >>> config = model.to_json()
      >>> loaded_model = tf.keras.models.model_from_json(config)
  
      Args:
          json_string: JSON string encoding a model configuration.
          custom_objects: Optional dictionary mapping names
              (strings) to custom classes or functions to be
              considered during deserialization.
  
      Returns:
          A Keras model instance (uncompiled).
      """
      config = json_utils.decode(json_string)
      from tensorflow.python.keras.layers import (
          deserialize,
      )  # pylint: disable=g-import-not-at-top
  
      return deserialize(config, custom_objects=custom_objects)
  
imports: from tensorflow.python.keras.saving.saved_model import json_utils
label_desc: Use image node_id 3 for calling a global function with example usage: model_from_json(json_string, custom_objects) and returns: deserialize