code: def model_from_json(json_string, custom_objects=None):
      """Parses a JSON model configuration string and returns a model instance.
  
      Usage:
  
      >>> model = keras.Sequential([
      ...     keras.layers.Dense(5, input_shape=(3,)),
      ...     keras.layers.Softmax()])
      >>> config = model.to_json()
      >>> loaded_model = 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).
      """
      from keras.saving import serialization_lib
  
      model_config = json.loads(json_string)
      return serialization_lib.deserialize_keras_object(
          model_config, custom_objects=custom_objects
      )
  
imports: import inspect
  import json
  import os
  import warnings
  from keras import backend
  from keras import utils
  from keras.api_export import keras_export
  from keras.layers.layer import Layer
  from keras.models.variable_mapping import map_trackable_variables
  from keras.saving import saving_api
  from keras.saving import saving_lib
  from keras.trainers import trainer
  from keras.utils import io_utils
  from keras.utils import summary_utils
  from keras.utils import traceback_utils
label_desc: Use image node_id 1 for calling a global function with example usage: model_from_json(json_string, custom_objects) and returns: serialization_lib