o i e@sfdZddlZddlmZddlmZeaeddddZeddd d Z ed dd d Z dS)z>Functions that save the model's config into different formats.N) keras_export) serializationzkeras.models.model_from_configcCsZt|tr td|dddlm}ttds#|j|jj j t_ tj |tj |ddS)aOInstantiates 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. zG`model_from_config` expects a dictionary, not a list. Received: config=z8. Did you meant to use `Sequential.from_config(config)`?r)layers ALL_OBJECTSlayer)module_objectscustom_objectsprintable_module_name) isinstancelist TypeError keras.srcrhasattrMODULE_OBJECTSrpopulate_deserializable_objectsLOCALrdeserialize_keras_object)configrrrS/var/www/myenv/lib/python3.10/site-packages/keras/src/saving/legacy/model_config.pymodel_from_configs     rzkeras.models.model_from_yamlcCstd)a3Parses 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_stringrrrrmodel_from_yamlJsrzkeras.models.model_from_jsoncCsddlm}|||dS)aiParses 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). r)deserialize_from_json)r)keras.src.layersr) json_stringrrrrrmodel_from_jsonds  r)N) __doc__ threading tensorflow.python.util.tf_exportrkeras.src.saving.legacyrlocalrrrrrrrrs   .