&Vf;$ddlZddlZddlmZddlmZddlmZddlmZddlmZ ddlm Z ddlm Z dd lm Z dd l mZdd lmZejad Zdd ZddZddZdZdZdZdZdZdZdS)N)logging)backend)layers)losses)metrics)models) optimizers)tree) serialization)object_registration)module function_typeoutput_shape_typeoutput_shape_modulecPt|trtd|dttdszt jt_t jtjd<tj tjd<tj tjd<tj tjd<|d d d }|#|d dkr ||dd <n ||dd <|d dd }|Ft|tr1t|dkrt|d|dd<|d dkrt D]}|d |d }|dd}t|trCdid}|d|dd<|d|dd<|d|dd<||dd<t#|dd}t%j|tj|dS)aInstantiates a Keras model from its config. Args: config: Configuration dictionary. custom_objects: Optional dictionary mapping names (strings) to custom classes or functions to be considered during deserialization. Returns: A Keras model instance (uncompiled). Raises: TypeError: if `config` is not a dictionary. zG`model_from_config` expects a dictionary, not a list. Received: config=z8. Did you meant to use `Sequential.from_config(config)`? ALL_OBJECTS InputLayer FunctionalModel Sequentialconfigbatch_input_shapeN class_name batch_shape input_shapeaxisrLambdafunction __lambda__rrcodedefaultsclosurezkeras.layer)module_objectscustom_objectsprintable_module_name) isinstancelist TypeErrorhasattrMODULE_OBJECTSr__dict__rrrrrrpoplenintLAMBDA_DEP_ARGS_find_replace_nested_dictr deserialize_keras_object)rr(rrdep_arg_function_config function_dicts a/var/www/html/software/conda/lib/python3.11/site-packages/keras/src/legacy/saving/saving_utils.pymodel_from_configr;s8&$  0 & 0 0 0    >= 1 1E%+_"393D"<0393D"<0.4l"7+393D"<0x(,,-@$GG$ , < / /.?F8 ] + +.?F8 ] + (    - -D JtT22s4yyA~~#&tAw<<x lx''& 4 4Gx $$Wd33AA *:6 ot , , 9+72FFM.=a.@M( #F +2A!2DM( #J /1@1CM( #I .+8F8 Z ('vx B BF  1%1%%    Tcddlm}d|jji} ||d<n#t $r}|r|Yd}~nd}~wwxYwt t|tj|}t|ddr|r~|j rw|j j }| ddt||d <tj|jj|jd }||d d <|S) z3Returns a dictionary containing the model metadata.r) __version__rrN) keras_versionr model_config optimizerFtraining_configr!optimizer_config) keras.srcr> __class____name__ get_configNotImplementedErrordictstrrgetattrcompiled_compile_configrr0_serialize_nested_configr get_registered_namerA) modelinclude_optimizerrequire_configr?r@emetadatarBrCs r:model_metadatarU]sl666666 %/":;L!&!1!1!3!3 X   G     -((!!!H uk5)) O.? O > O#3:O    T 2 2 2*B++H& '2EO- /4466     ?OH& '(: ; Os. AAAcz|i}tj|5|d}tj|}t ||t}d}|dd}|0t tj|}t ||t}d}|dd}|+t t|}t ||t}d}|dd} | t t| }|d} dddn #1swxYwYt||||| S)z4Return model.compile arguments from training config.NrClossrweighted_metrics loss_weights)rArWrrXrY) r CustomObjectScoper deserialize!_resolve_compile_arguments_compatget_deserialize_nested_configr_deserialize_metricmetrics_modulerI) rBr(rCrArW loss_configrmetrics_configrXweighted_metrics_configrYs r:!compile_args_from_training_configrd~s  .~ > >$7$7*+=>*+;<< 5 '  %))&$77  "-f.@+NND4T;OOD(,,Y==  %0#^G8G  "1"5"56H$"O"O " .9#%<   '~6 I$7$7$7$7$7$7$7$7$7$7$7$7$7$7$7L  )!    sC9DD"%D"c2d}tj||S)z/Serialized a nested structure of Keras objects.cLt|rtj|S|SN)callabler serialize_keras_objectobjs r: _serialize_fnz/_serialize_nested_config.._serialize_fns& C== = 7<< < r<)r map_structure)rrls r:rNrNs&  mV 4 44r<c"d}|dS||r |St|tr fd|DSt|ttfrfd|DSt d|d)z=Deserializes arbitrary Keras `config` using `deserialize_fn`.cjt|trd|vrdSt|trdSdS)NrTF)r*rIrJrjs r:_is_single_objectz5_deserialize_nested_config.._is_single_objects? c4  \S%8%84 c3   4ur<Nc8i|]\}}|t|Sr^).0kvdeserialize_fns r: z._deserialize_nested_config..s:   1 ).!<<   r<c0g|]}t|Srrrs)rtrkrws r: z._deserialize_nested_config..s1   @C &~s ; ;   r<zrSaved configuration not understood. Configuration should be a dictionary, string, tuple or list. Received: config=.)r*rIitemstupler+ ValueError)rwrrps` r:r^r^s~t   ~f%%% FD ! !           FUDM * *     GM      I?E I I I  r<c6|dvr|Stj|S)z7Deserialize metrics, leaving special strings untouched.)accuracyacc crossentropyce)r`r[) metric_configs r:r_r_s'AAA  %m 4 44r<ctj|}|||}tj|}|Srg)jsondumpsreplaceloads)rfindrdict_strs r:r4r4s:z&!!Hg..H Z ! !F Mr<ct|tr*||jvr!||dd}|S)aCResolves backwards compatibility issues with training config arguments. This helper function accepts built-in Keras modules such as optimizers, losses, and metrics to ensure an object being deserialized is compatible with Keras 3 built-ins. For legacy H5 files saved within Keras 3, this does nothing. rname)r*rJALL_OBJECTS_DICTr])rk obj_configr s r:r\r\sC#s76+B B BjjH-f566 Jr<c |jjs|j|j|jjs'|j|j|jdSdS#t jdYdSxYw)NzCompiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.) compiled_lossbuiltbuildoutputscompiled_metricsrwarning)rPs r:try_build_compiled_argumentsrs  "( 5   % %em 4 4 4%+ G  " ( ( F F F F F G G  5      s AA""A;rg)TT)r threadingabslrrDrrrrr`rr r keras.src.legacy.savingr keras.src.savingr localr.r3r;rUrdrNr^r_r4r\rrrr<r:rs ////// 111111000000 ""????DB1111h555<555         r<