BVh ,dZddlmZddZddZddZy)z>Functions that save the model's config into different formats.) json_utilsNcXt|tr tdddlm}|||S)a-Instantiates a Keras model from its config. Usage: ``` # for a Functional API model tf.keras.Model().from_config(model.get_config()) # for a Sequential model tf.keras.Sequential().from_config(model.get_config()) ``` Args: config: Configuration dictionary. custom_objects: Optional dictionary mapping names (strings) to custom classes or functions to be considered during deserialization. Returns: A Keras model instance (uncompiled). Raises: TypeError: if `config` is not a dictionary. zn`model_from_config` expects a dictionary, not a list. Maybe you meant to use `Sequential.from_config(config)`?r deserializecustom_objects) isinstancelist TypeErrortensorflow.python.keras.layersr)configrrs [/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/keras/saving/model_config.pymodel_from_configrs20 8 999 VN ;;ctd)aParses a yaml model configuration file and returns a model instance. Note: Since TF 2.6, this method is no longer supported and will raise a RuntimeError. Args: yaml_string: YAML string or open file 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). Raises: RuntimeError: announces that the method poses a security risk zMethod `model_from_yaml()` has been removed due to security risk of arbitrary code execution. Please use `Model.to_json()` and `model_from_json()` instead.) RuntimeError) yaml_stringrs rmodel_from_yamlr5s$ % rcLtj|}ddlm}|||S)aMParses 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). rrr)rdecoder r) json_stringrr rs rmodel_from_jsonrNs$(   [ )&8 VN ;;r)N)__doc__*tensorflow.python.keras.saving.saved_modelrrrrrrrs EA<@2