&Vf|qdZddlZddlZddlZddlZddlZddlmZddlm Z ddl m Z ddl m Z ddlmZddlmZdd lmZeeeefZd ZGd d ZGd dZe ddZdZGddZdZ dZ!dZ"e ddgdZ#dZ$d$dZ%d$dZ&dZ'dZ(e dd g d%d"Z) d$d#Z*dS)&z6Object config serialization and deserialization logic.N) api_export)backend) keras_export) global_state)object_registration) python_utils) tensorflow) activations constraints initializerslossesmetrics optimizers regularizersceZdZdZdZdS)SerializableDictc ||_dSNconfig)selfrs _/var/www/html/software/conda/lib/python3.11/site-packages/keras/src/saving/serialization_lib.py__init__zSerializableDict.__init__!s  c*t|jSr)serialize_keras_objectrrs r serializezSerializableDict.serialize$s%dk222rN)__name__ __module__ __qualname__rrrrrr s233333rrc&eZdZdZddZdZdZdS) SafeModeScopezBScope to propagate safe mode flag to nested deserialization calls.Tc||_dSr) safe_mode)rr&s rrzSafeModeScope.__init__+s "rc`t|_tjd|jdSNsafe_mode_saving) in_safe_modeoriginal_valuerset_global_attributer&rs r __enter__zSafeModeScope.__enter__.s**nn)*s  ,-? @ @@rceZdZdZdZdZdS)ObjectSharingScopez?Scope to enable detection and reuse of previously seen objects.cZtjditjdidSNshared_objects/id_to_obj_mapshared_objects/id_to_config_mapr5rs rr-zObjectSharingScope.__enter__Es0)*H"MMM)*KRPPPPPrcZtjddtjdddSr=r5r/s rr2zObjectSharingScope.__exit__Is:)*H$OOO) -t     rN)rr r!r3r-r2r"rrr;r;Bs;IIQQQ     rr;c^tjd}|||dSdS)z:Retrieve an object previously seen during deserialization.r>N)rr9get)obj_id id_to_obj_maps rget_shared_objectrEPs= 5&M   ...! rc|ddkrd|d<tjd}|dStt|}||vr|||<dS||d<||}||d<dS)z>Call after serializing an object, to keep track of its config.module__main__Nr?shared_object_id)rr9intid)objrid_to_config_maprC prev_configs r!record_object_after_serializationrOYs h:%%x#8) C\\F %%%#)   %+!"&v. *0 &'''rc@tjd}|dS|||<dS)zFCall after deserializing an object, to keep track of it in the future.r>Nr8)rLrCrDs r#record_object_after_deserializationrQks4 5&MM&rz#keras.saving.serialize_keras_objectz"keras.utils.serialize_keras_objectc ||St|tr|St|ttfr2d|D}t|trt|n|St|trt |St|t rdd|didSt|tr?dt|j t|j t|j ddSt|ttrd idSt|tjrEt#|d d}|rt|}|d j|d <d |j|j|d dSt*jr7t|t*jr|j|ndStj|rCdtj|tj|jddSt|jt>j krjt|t>j!r<|j"d kr1d|tj|jddS|#St*jr!t|t*j$r|jSt|tJj&rO|j dkrDtOj(dtSj*|dddtWj,|idSt*jrht|t*j-rN|.}tt_d|}d|j0j |j0j|ddStc|}te|j0|}|"tg||ti|||St|tJj&r|j}n |j0j}|j0j }|dkrd}nHt|tJj&rtkj6|}ntkj6|j0}||||d} tg|| ti|| | S)a Retrieve the config dict by serializing the Keras object. `serialize_keras_object()` serializes a Keras object to a python dictionary that represents the object, and is a reciprocal function of `deserialize_keras_object()`. See `deserialize_keras_object()` for more information about the config format. Args: obj: the Keras object to serialize. Returns: A python dict that represents the object. The python dict can be deserialized via `deserialize_keras_object()`. Nc,g|]}t|Sr"r).0xs r z*serialize_keras_object..s!===A,Q//===r __bytes__valueutf-8) class_namer __slice__)startstopstep __ellipsis___keras_historyr__keras_tensor__)shapedtype keras_history __tensor__)rYrd __numpy__zaThe object being serialized includes a `lambda`. This is unsafe. In order to reload the object, you will have to pass `safe_mode=False` to the loading function. Please avoid using `lambda` in the future, and use named Python functions instead. This is the `lambda` being serialized: ) stacklevel __lambda__ct|tjr|n"t|tjr|jn|Sr) isinstancetf TensorShapeas_listDTypenamerVs rz(serialize_keras_object..sB!!R^44DAIIKKK$.q"($;$;B!&&r __typespec__)r[ spec_namerGrregistered_namebuiltinsrGr[rrv)7rl PLAIN_TYPESlisttupledictserialize_dictbytesdecodeslicerr]r^r_typeEllipsisr KerasTensorgetattrrqrcrdrm availablern_dimsro is_tensorconvert_to_numpytoliststandardize_dtyper nprndarrayndimitemrptypes FunctionTypewarningswarninspect getsourcer func_dumpTypeSpec _serializemap __class___get_class_or_fn_configserialize_with_public_classget_build_and_compile_configrOrget_registered_name) rL config_arrhistory ts_config inner_configconfig_with_public_classrGr[rvrs rrrus* { #{## #e}%%K===== $.sE$:$:JuZ   J#t#c"""#u % 7 3 34   #u %/ ::.sx88.sx88   #tH~~&&<,;;;#w*++  #/66  )7mmG GAJ,!(    |@ 377@ # 5s{{}}}4? & 1#66==?? 239==    Cyyr{** c2: & & 38a<<) ZZ\\$6syAA 88::  | 311x#u)** s|z/I/I  O 7>6G6L6L  O O     '/44    | 3 44 NN$$         )/m.#    +3//L: |   +$S*BCCC)#/GHHH''#u)***)'J  c5- . . 1EcJJOO1E O  * F !f---%c6222 Mrct|dr(|}|t||d<t|dr(|}|t||d<dS)Nget_build_config build_configget_compile_configcompile_config)hasattrrr}r)rLrrrs rrrss&''B++--  #%3L%A%AF> "s())F//11  %'5n'E'EF# $ Frctj|}|)tj|}|dS|j|j||dS|d}d|dd|d|ddS)zSerializes classes from public Keras API or object registration. Called to check and retrieve the config of any class that has a public Keras API or has been registered as serializable via `keras.saving.register_keras_serializable()`. Nrx.)rget_name_from_symbolrrr rsplitjoin)clsrkeras_api_namervpartss rrr&s 4S99N-A#FF  "4n,".       % %E((5":&&Bi   rc |r|d||dStj|}|r7|d}d|ddd||dSt j|}|s |jdksdS|jd||dS)aOSerializes functions from public Keras API or object registration. Called to check and retrieve the config of any function that has a public Keras API or has been registered as serializable via `keras.saving.register_keras_serializable()`. If function's module name is already known, returns corresponding config. functionrxrNrrw)rrrrrrr )fnrfn_module_namerrrvs rserialize_with_public_fnrIs $$%     4R88N $$S))hhuSbSz**$%    .A"EE r} 'B'B4m$.    rct|tjr|jSt |drM|}t|t std|d|t|St |drtj |Std|dt|d)z1Return the object's config depending on its type. get_configzThe `get_config()` method of z$ should return a dict. 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M M Mr)items)rLs rr}r}s M M M M MMrz%keras.saving.deserialize_keras_objectz$keras.utils.deserialize_keras_objectTc v t}||n|dd}pitjdi}tj}i|||dSt |trr||St |ttfrfd|DS|\d\}} } t |trd|vr|d}d|vrtd|r=|dvs0|d vst |tr|vrd } nl|dd kr |d } | d kr |d}nI|d }n@|d d"td|dd|dd|d}| sr||vr|St ||tjr&t!t#|||| St!t%|||St |t&r|St |tstd|d|vsd|vr!fd|DS|d} |dpi}pi| dkr1t+j|d|d} |d| _| S| dkr"t+j|d|dS| dkr"t3j|d|dS|ddkr|ddS|dd krt8S|dd!krSt;t!|d"#t!|d$#t!|d%#S|dd&kr+rtd't=j|dSt@f|dd(krZtC|d)|d |d d*|+} tEd,|}| #t|S|d d} |d | }| d kr|}tC||| d |+Sd-|vrtI|d-} | | StC| || d*|+}t |tjr|StK|d.std/| d0|t j&}tO}|5|5 |(|}n)#t$r}t|d1|d2|d}~wwxYw|d3d}|r#|j)s|*|d |_)|d4d}|r|+|d |_,dddn #1swxYwYdddn #1swxYwYd-|vrt[||d-|S)5a:Retrieve the object by deserializing the config dict. The config dict is a Python dictionary that consists of a set of key-value pairs, and represents a Keras object, such as an `Optimizer`, `Layer`, `Metrics`, etc. The saving and loading library uses the following keys to record information of a Keras object: - `class_name`: String. This is the name of the class, as exactly defined in the source code, such as "LossesContainer". - `config`: Dict. Library-defined or user-defined key-value pairs that store the configuration of the object, as obtained by `object.get_config()`. - `module`: String. The path of the python module. Built-in Keras classes expect to have prefix `keras`. - `registered_name`: String. The key the class is registered under via `keras.saving.register_keras_serializable(package, name)` API. The key has the format of '{package}>{name}', where `package` and `name` are the arguments passed to `register_keras_serializable()`. If `name` is not provided, it uses the class name. If `registered_name` successfully resolves to a class (that was registered), the `class_name` and `config` values in the dict will not be used. `registered_name` is only used for non-built-in classes. For example, the following dictionary represents the built-in Adam optimizer with the relevant config: ```python dict_structure = { "class_name": "Adam", "config": { "amsgrad": false, "beta_1": 0.8999999761581421, "beta_2": 0.9990000128746033, "decay": 0.0, "epsilon": 1e-07, "learning_rate": 0.0010000000474974513, "name": "Adam" }, "module": "keras.optimizers", "registered_name": None } # Returns an `Adam` instance identical to the original one. deserialize_keras_object(dict_structure) ``` If the class does not have an exported Keras namespace, the library tracks it by its `module` and `class_name`. For example: ```python dict_structure = { "class_name": "MetricsList", "config": { ... }, "module": "keras.trainers.compile_utils", "registered_name": "MetricsList" } # Returns a `MetricsList` instance identical to the original one. deserialize_keras_object(dict_structure) ``` And the following dictionary represents a user-customized `MeanSquaredError` loss: ```python @keras.saving.register_keras_serializable(package='my_package') class ModifiedMeanSquaredError(keras.losses.MeanSquaredError): ... dict_structure = { "class_name": "ModifiedMeanSquaredError", "config": { "fn": "mean_squared_error", "name": "mean_squared_error", "reduction": "auto" }, "registered_name": "my_package>ModifiedMeanSquaredError" } # Returns the `ModifiedMeanSquaredError` object deserialize_keras_object(dict_structure) ``` Args: config: Python dict describing the object. custom_objects: Python dict containing a mapping between custom object names the corresponding classes or functions. safe_mode: Boolean, whether to disallow unsafe `lambda` deserialization. When `safe_mode=False`, loading an object has the potential to trigger arbitrary code execution. This argument is only applicable to the Keras v3 model format. Defaults to `True`. Returns: The object described by the `config` dictionary. Nmodule_objectscustom_objects_scope_dictc4g|]}t|Scustom_objectsr&deserialize_keras_object)rUrVrr&s rrWz,deserialize_keras_object..sA    %.I      r)NNFrr[z%Unknown `config` as a `dict`, config=rvTrrGrw_z#Cannot deserialize object of type `z`. If `zj` is a custom class, please register it using the `@keras.saving.register_keras_serializable()` decorator.r)rzCould not parse config: c<i|]\}}|t|Srr)rUrrYrr&s rrz,deserialize_keras_object..RsH   U )n    rrbrcrd)rdrerfrYrgrXrZr`r\r]rr^r_rjaRRequested the deserialization of a `lambda` object. This carries a potential risk of arbitrary code execution and thus it is disallowed by default. If you trust the source of the saved model, you can pass `safe_mode=False` to the loading function in order to allow `lambda` loading, or call `keras.config.enable_unsafe_deserialization()`.rtruclass)obj_type full_configrct|trtj|n=t tjt |rtt|n|Sr)rlrzrmrnrdtypesstrrrrs rrsz*deserialize_keras_object..sOa&&Kq!!!(/ 3q66(B(BIgb!nnnrrI from_configz&Unable to reconstruct an instance of 'zM' because the class is missing a `from_config()` method. Full object config: z could not be deserialized properly. Please ensure that components that are Python object instances (layers, models, etc.) returned by `get_config()` are explicitly deserialized in the model's `from_config()` method. config=z. Exception encountered: rr).r*poprr9rGLOBAL_CUSTOM_OBJECTSrlrrBrzr{r| ValueErrorrrrrrrryrrr _pre_serialization_keras_historyconvert_to_tensorrarrayencoderrr func_loadrm_retrieve_class_or_fnr _deserializerErCustomObjectScoper$rbuiltbuild_from_configcompile_from_configcompiledrQ)rrr&r1safe_scope_argrtlcogcorrhas_custom_objectr[rLrGrvfn_namercustom_obj_scopesafe_mode_scopeinstanceerrs `` rrrsP"^^N"0"<)IZZ 0$77N#)rN  ,-H" M MD  3C66$6#6N ~t 63& &   v & & 2f%%&4-((           !:K7 n&7 fd # #& .6!!%h/ 6)) DFDD  .|$66::/00NBB|S11C%66%)!! %33!'!1!Z//#H-FF#$56FF::h,,4#%"<0%%"<0%%% -  ^++ .0%2DEE /,&v.$2  ,+"6* .  &+&& fd # #=;6;;<<<6!!XV%;%;     %llnn      %J(#)rL#)rN'''!  !g)>   0    [  x W-\'5JKKKK l{**G$++G444 l~-- l{** $W%-#    %V$-#    %V$-#      "l|++  J %l7&;<<< ~&..@@# ;  $ % 8 )          l 3 3444ZZ$ ' 'Fjj!2J??OZ$   )     V##'9 :;; ?J %    C#u)** 3 & &  ,Z , ,#) , ,   +<^LL#I..O %%?%% |44HH   FF % FF CD FF  zz.$77  " "  & &| 4 4 4!HN$4d;;  %  ( ( 8 8 8 $H '%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%*V##+ f/0    Os[>XW=UW= U?#U::U??A2W=1 X=X XX XXXc J|dkrtj||}ntj||}||S|rQ|dks|dr |dz|z}tj|}||S|dkr|dkr}t D]%} tjd| zdz|z}||cS&fd|D} | r.tt| S tj |} n)#t$rtd|d |d |d wxYwt| |d}|%|#t| |d}||Std |d |d )Nrrkeraszkeras.rrwcRi|]#\}}|d ||$Sr)endswith)rUkvrs rrz)_retrieve_class_or_fn..sFAq::k(3441rzCould not deserialize z 'z' because its parent module z) cannot be imported. Full object config: zCould not locate zr'. Make sure custom classes are decorated with `@keras.saving.register_keras_serializable()`. Full object config: )rget_registered_object startswithrget_symbol_from_nameBUILTIN_MODULESrnextitervalues importlib import_moduleModuleNotFoundErrorrvarsrB) rqrvrGrrr custom_objapi_namerLmod filtered_dicts ` rrrsk :(>    )> N    2 W   1 1( ; ; |d*H1(;;C z ! !f &:&:&   5sNS(4/?JJJ#*0022M  :D!5!5!7!788999 )&11CC"   555T55%+55'255   3iimmD$'' ;?6s))--66C ?J  -H - - - - + - -  s D&D<r)NT)+r3rrrrnumpyr keras.srcrrkeras.src.api_exportrkeras.src.backend.commonrkeras.src.savingrkeras.src.utilsrkeras.src.utils.module_utilsr rmrrJfloatboolryrrr$r6r*r;rErOrQrrrrrr}rrr"rrrs<<  ------111111000000((((((999999C% 33333333         :;;AA<;A AAA         ///111$   -, \\  \~        F! ! ! ! H   0NNN/.,0VVV  Vt JNIIIIIIr