6biVSrSSKrSSKrSSKJs Jr SSKJr SSKJ r SSK J r Sq Sr Sr\R"5r\R"5q\R"5qS rS rS r"S S 5r"SS5r"SS5r"SS\5r"SS5rSSjr\R:S5r\ "S5S5rS Sjr \ "S5S Sj5r!Sr"Sr#g)!z/Legacy serialization logic for TF-Keras models.N) tf_contextlib) tf_inspect) keras_exportFzlayer was saved without configshared_object_idc$[[SS5$)zFGet whether shared object handling is disabled in a threadsafe manner.disabledF)getattrSHARED_OBJECT_DISABLEDb/home/james-whalen/.local/lib/python3.13/site-packages/tf_keras/src/saving/legacy/serialization.py_shared_object_disabledr4s ):u ==r c4[[S[55$)BGet the current shared object saving scope in a threadsafe manner.scope)r SHARED_OBJECT_LOADINGNoopLoadingScoper r r _shared_object_loading_scoper9s ('3C3E FFr c$[[SS5$)rrN)r SHARED_OBJECT_SAVINGr r r _shared_object_saving_scoper>s '$ 77r c$\rSrSrSrSrSrSrg)DisableSharedObjectScopeCzA context manager for disabling handling of shared objects. Disables shared object handling for both saving and loading. 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N)r@r4)r r8s r r4SharedObjectLoadingScope.getws$   ##'' 22r c(UcgX RU'g)zSUlX l[TU] "U40UD6 gN) ref_countr8super__init__)r base_configr8r& __class__s r rQSharedObjectConfig.__init__s!" //r ctURS:XaURU['U=RS- slgrM)rOr8SHARED_OBJECT_KEYrs r increment_ref_count&SharedObjectConfig.increment_ref_counts- >>Q &*nnD" # !r )r8rO) r)r*r+r,r-rQrWr. __classcell__)rSs@r rJrJs 0 r rJc0\rSrSrSrSrSrSrSrSr g) SharedObjectSavingScopez6Keeps track of shared object configs when serializing.c[5(ag[5bSUl[5$SUlU[l[ R "5UlSUlU$)NTFr) rr _passthroughrrweakrefWeakKeyDictionary_shared_objects_config_next_idrs r r!!SharedObjectSavingScope.__enter__sX " $ $ ' ( 4 $D .0 0 %D %)"&-&?&?&A#  r crURUnUR5 U$![[4a gf=f)zGets a `SharedObjectConfig` if one has already been seen for `obj`. Args: obj: The object for which to retrieve the `SharedObjectConfig`. Returns: The SharedObjectConfig for a given object, if already seen. Else, `None`. N)ra TypeErrorKeyErrorrW)r r9shared_object_configs r get_config"SharedObjectSavingScope.get_configsG #'#>#>s#C  002##8$    s #66c[XR5nU=RS- slX0RU'U$![a U$f=f)z3Create a new SharedObjectConfig for a given object.rN)rJrbrare)r rRr9rgs r create_config%SharedObjectSavingScope.create_configsV1+}}M   /C ' ' ,$#   ##  s< A  A c@[USS5(d S[lgg)Nr^F)r rrr$s r r' SharedObjectSavingScope.__exit__st^U33)- &4r )rbr^raN) r)r*r+r,r-r!rhrkr'r.r r r r[r[s@,$* $.r r[cXS.nUbX4['[5b:Ub7[5RU5nUc[5RXB5$U$U$)z=Returns the serialization of the class with the given config.) class_nameconfig)rVrrhrk)cls_name cls_configr9rrRrgs r serialize_keras_class_and_configrtsf"*@K #)9%& #$0S_:<GGL  '.0>>{P P## r c#8# [nSqSv Uqg!Uqf=f7fr)_SKIP_FAILED_SERIALIZATION)prevs r skip_failed_serializationrx s& &D*%)" %)"T"sz)keras.utils.legacy.serialize_keras_objectcSSKJn [RRR U5up Ucg[ US5(aURUR5nUR5n0nUR5H_upx[U[ 5(aXU'M [#U5n [U [$5(a[U[$5(dSU S'XU'Ma URUR5n[X6U5$[ US5(aURU5$['SUS 35e![a)n[(a[U[S05sSnA$UeSnAff=f![&a XU'GMf=f) aSerialize a TF-Keras object into a JSON-compatible representation. Calls to `serialize_keras_object` while underneath the `SharedObjectSavingScope` context manager will cause any objects re-used across multiple layers to be saved with a special shared object ID. This allows the network to be re-created properly during deserialization. Args: instance: The object to serialize. Returns: A dict-like, JSON-compatible representation of the object's config. robject_registrationNrhT__passive_serialization__r)zCannot serialize z- because it doesn't implement `get_config()`.)tf_keras.src.savingr{tf __internal__ decoratorunwraphasattrget_registered_namerSrhNotImplementedErrorrvrt_LAYER_UNDEFINED_CONFIG_KEYitems isinstancestrserialize_keras_objectdict ValueError) instancer{_namerqeserialization_configkeyitemserialized_items r rrs8//++228ot44Z$>>DHO$?@,;S)("#66x7I7IJ/   x$$"66x@@  H:&  =# ))76=G  * 1,0S) 1s6#E&>E6 E3 E.&E3,E..E36F F cSSKJn [U[5(a SU;dSU;a[ SUS35eUSnUR XRU5nUc[ SUSUS 35eUSn[U[ 5(aXg4$0nUR5HupU S :XaXU 'M[U [5(aS U ;a[U UUS S 9X'M<[U [5(dMS[R"UR X55(dMUR X5UU 'M UR5H upXXy'M Xg4$)z@Returns the class name and config for a serialized keras object.rrzrprqzImproper config format for zB. Expecting python dict contains `class_name` and `config` as keysUnknown : ''. Please ensure you are using a `keras.utils.custom_object_scope` and that this object is included in the scope. See https://www.tensorflow.org/guide/tf_keras/save_and_serialize#registering_the_custom_object for details.rr| config_item)module_objectscustom_objectsprintable_module_name) r}r{rrrget_registered_objectlistrdeserialize_keras_objectrr isfunction) rqrrrr{rpclsrsdeserialized_objectsrrs r ,class_and_config_for_serialized_keras_objectrUs8 vt $ $ v % 6 !)&2O O   %J  3 3N C {,-S =: :  !J*d##  %%'  &= )- % d # #(Ct(K(@--&3 ) %c " "z'<'<  5 5d K( ( $99$O ! 7(<*//1 .3 2  r z+keras.utils.legacy.deserialize_keras_objectcSSKJn Ucg[U[5(Ga;Un[ XQX#5upgUR [ 5n[5R U5n U bU $[US5(a[R"UR5n U=(d 0nSU R;a7URRn URU0UREU EUES9n OYUR!U5 URU5n SSS5 O-U=(d 0nUR!U5 U"S 0UD6n SSS5 [5R#UW 5 U $[U[$5(aUn U(aX;aUR U 5nOyU URR;aURRU nOEXR;aURU nO&UR U 5nUc['SUSU S 35e[R("U5(aU"5$U$[R*"U5(aU$['S US U35e!,(df  GN+=f!,(df  GN==f) a>Turns the serialized form of a TF-Keras object back into an actual object. This function is for mid-level library implementers rather than end users. Importantly, this utility requires you to provide the dict of `module_objects` to use for looking up the object config; this is not populated by default. If you need a deserialization utility that has preexisting knowledge of built-in TF-Keras objects, use e.g. `keras.layers.deserialize(config)`, `keras.metrics.deserialize(config)`, etc. Calling `deserialize_keras_object` while underneath the `SharedObjectLoadingScope` context manager will cause any already-seen shared objects to be returned as-is rather than creating a new object. Args: identifier: the serialized form of the object. module_objects: A dictionary of built-in objects to look the name up in. Generally, `module_objects` is provided by midlevel library implementers. custom_objects: A dictionary of custom objects to look the name up in. Generally, `custom_objects` is provided by the end user. printable_module_name: A human-readable string representing the type of the object. Printed in case of exception. Returns: The deserialized object. Example: A mid-level library implementer might want to implement a utility for retrieving an object from its config, as such: ```python def deserialize(config, custom_objects=None): return deserialize_keras_object( identifier, module_objects=globals(), custom_objects=custom_objects, name="MyObjectType", ) ``` This is how e.g. `keras.layers.deserialize()` is implemented. rrzN from_configr)rrrrzCould not interpret serialized z: r )r}r{rrrr4rVrrrgetfullargspecrr%_THREAD_LOCAL_CUSTOM_OBJECTS__dict___GLOBAL_CUSTOM_OBJECTSCustomObjectScoper:rrisclassr) identifierrrrr{rqrrsr shared_objectarg_spectlcodeserialized_obj object_namer9s r rrsj8*d##H N  "::&7846::;KL  $ 3 & &!00AH+1rN8==0*GGPP#&??$-DD$$)$$3$ )::>J'*z'B$KJ ,1rN$66~F##4 G %&**+;=MN J $ $ k; $$[1C "??HH I&BBKKCFF F%<<[IC $$[1C{ 45S F##   c " "5L   z * * -$%R | 5  eKJGFs8I/ I. I+. 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