o i ej'@shdZddlZddlmmZddlmZddlmZddlm Z ddl m Z ddl m Z ddl m Z dd l mZdd l mZdd l mZdd l mZdd l mZddl mZddl mZddlmZddlmZddlmZddlmZddlmZddlmZddlmZddlmZddlmZddlm Z ddlm!Z!ddlm"Z#ddlm$Z$ddlm%Z%ddl&m'Z'ddl&m(Z(dd l&m)Z)dd!l*m+Z+dd"l,m-Z-dd#l.m/Z0dd$l1m2Z2dd%l3m4Z4dd&l3m5Z6dd'l7m8Z8eee e e eeeeeeeee eeeeeeee!e#e$e%fZ9eee'e(e)fZ:e;ae8d.d6d/d0Z?d1d2Z@d7d3d4ZAdS)8z.Layer serialization/deserialization functions.N) base_layer) input_layer) input_spec) activation) attention) convolutional)core)locally_connected)merging)pooling)regularization) reshaping)rnn)batch_normalization)batch_normalization_v1)group_normalization)layer_normalization)unit_normalization)category_encoding)discretization)hashed_crossing)hashing)image_preprocessing)integer_lookup) normalization) string_lookup)text_vectorization) cell_wrappers)gru)lstm) base_metric)serialization_lib) serialization) json_utils) generic_utils) tf_inspect) keras_exportcsttds it_dt_tjrtjtjjkrdSit_tjjt_tj t j tjt fdddtjjrFt j tjt fdddtjtjd<tjtjd<d d lm}d d lm}d d lm}d d lm}tjtjd<tjtjd<|jtjd<|jtjd<|tjd<|jtjd<|tjd<|tjd<tjjrd dl m!}|tjd<n d dl"m!}|tjd<t#j$tjd<t#j%tjd<t#j&tjd<t#j'tjd<t#j(tjd<t#j)tjd<t#j*tjd<t#j+tjd<dS) z5Populates dict ALL_OBJECTS with every built-in layer. ALL_OBJECTSNct|o t|SNinspectisclass issubclassxbase_clsM/var/www/myenv/lib/python3.10/site-packages/keras/src/layers/serialization.py|z1populate_deserializable_objects..) obj_filtercr(r)r*r.r0r2r3r4r5BatchNormalizationV1BatchNormalizationV2r)models)SequenceFeatures) LinearModel) WideDeepModelInput InputSpec FunctionalModelr: Sequentialr;r<) DenseFeaturesrBaddsubtractmultiplyaveragemaximumminimum concatenatedot),hasattrLOCALr'GENERATED_WITH_V2tf __internal__tf2enabledrLayerr$!populate_dict_with_module_objects ALL_MODULESALL_V2_MODULESrBatchNormalizationr keras.srcr90keras.src.feature_column.sequence_feature_columnr:keras.src.premade_models.linearr;"keras.src.premade_models.wide_deepr<rr=rr>r?r@rA*keras.src.feature_column.dense_features_v2rB'keras.src.feature_column.dense_featuresr rCrDrErFrGrHrIrJ)r9r:r;r<rBr2r0r3populate_deserializable_objectsfsl                             r]zkeras.layers.serializeFcCs4t|tjrtd|d|rt|St|S)aSerializes a `Layer` object into a JSON-compatible representation. Args: layer: The `Layer` object to serialize. Returns: A JSON-serializable dict representing the object's config. Example: ```python from pprint import pprint model = tf.keras.models.Sequential() model.add(tf.keras.Input(shape=(16,))) model.add(tf.keras.layers.Dense(32, activation='relu')) pprint(tf.keras.layers.serialize(model)) # prints the configuration of the model, as a dict. zCannot serialize z since it is a metric. Please use the `keras.metrics.serialize()` and `keras.metrics.deserialize()` APIs to serialize and deserialize metrics.) isinstancer Metric ValueErrorlegacy_serializationserialize_keras_objectr!)layeruse_legacy_formatr2r2r3 serializes    rezkeras.layers.deserializecCsDt|s td||rtj|tj|ddStj|tj|ddS)a8Instantiates a layer from a config dictionary. Args: config: dict of the form {'class_name': str, 'config': dict} custom_objects: dict mapping class names (or function names) of custom (non-Keras) objects to class/functions Returns: Layer instance (may be Model, Sequential, Network, Layer...) Example: ```python # Configuration of Dense(32, activation='relu') config = { 'class_name': 'Dense', 'config': { 'activation': 'relu', 'activity_regularizer': None, 'bias_constraint': None, 'bias_initializer': {'class_name': 'Zeros', 'config': {}}, 'bias_regularizer': None, 'dtype': 'float32', 'kernel_constraint': None, 'kernel_initializer': {'class_name': 'GlorotUniform', 'config': {'seed': None}}, 'kernel_regularizer': None, 'name': 'dense', 'trainable': True, 'units': 32, 'use_bias': True } } dense_layer = tf.keras.layers.deserialize(config) ``` z2Cannot deserialize empty config. Received: config=rc)module_objectscustom_objectsprintable_module_name)r]r`radeserialize_keras_objectrLr'r!)configrgrdr2r2r3 deserializes$&rkcCsttdsttj|S)z?Returns class if `class_name` is registered, else returns None.r')rKrLr]r'get) class_namer2r2r3get_builtin_layers  rncCs"ttj|tj|d}t||S)z(Instantiates a layer from a JSON string.)rfrg)r]r#decode_and_deserializerLr'rk) json_stringrgrjr2r2r3deserialize_from_json#s rq)F)NFr))B__doc__ threadingtensorflow.compat.v2compatv2rNkeras.src.enginerrrkeras.src.layersrrrrr r r r r rkeras.src.layers.normalizationrrrrrkeras.src.layers.preprocessingrrrrrrrpreprocessing_normalizationrrkeras.src.layers.rnnrrrkeras.src.metricsr keras.src.savingr!keras.src.saving.legacyr"ra#keras.src.saving.legacy.saved_modelr#keras.src.utilsr$r%r+ tensorflow.python.util.tf_exportr&rTrUlocalrLr]rerkrnrqr2r2r2r3s                                      Y ! :