6bi,SrSSKrSSKJr SSKJr \R "5q\"S5S Sj5r\"S5S Sj5r \"S 5S S j5r g) z>Functions that save the model's config into different formats.N) keras_export) serializationzkeras.models.model_from_configcP[U[5(a[SUS35eSSKJn [ [ S5(dCURR5 URRR[ l [R"U[ RUSS9$)aInstantiates a TF-Keras model from its config. Usage: ``` # for a Functional API model tf.keras.Model().from_config(model.get_config()) # for a Sequential model tf.keras.Sequential().from_config(model.get_config()) ``` Args: config: Configuration dictionary. custom_objects: Optional dictionary mapping names (strings) to custom classes or functions to be considered during deserialization. Returns: A TF-Keras model instance (uncompiled). Raises: TypeError: if `config` is not a dictionary. zG`model_from_config` expects a dictionary, not a list. Received: config=z8. Did you meant to use `Sequential.from_config(config)`?r)layers ALL_OBJECTSlayer)module_objectscustom_objectsprintable_module_name) isinstancelist TypeError tf_keras.srcrhasattrMODULE_OBJECTSrpopulate_deserializable_objectsLOCALrdeserialize_keras_object)configr rs a/home/james-whalen/.local/lib/python3.13/site-packages/tf_keras/src/saving/legacy/model_config.pymodel_from_configrs2&$ &x(0 0  $ >= 1 1<<>%+%9%9%?%?%K%K"  1 1%11%%  zkeras.models.model_from_yamlc[S5e)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 TF-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_stringr s rmodel_from_yamlrJs&  ' rzkeras.models.model_from_jsoncSSKJn U"XS9$)a4Parses 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 TF-Keras model instance (uncompiled). r)deserialize_from_json)r )tf_keras.src.layersr) json_stringr rs rmodel_from_jsonr!ds* ! LLr)N) __doc__ threading tensorflow.python.util.tf_exportrtf_keras.src.saving.legacyrlocalrrrr!rrr(ss E94"./+0+\,-.2,-M.Mr