o 2hE#@sddlZddlmZddlmZddlmZddlmZddlmZddl m Z ddl m Z e ad Zdd d Zdd dZdddZddZddZddZddZddZdS)N)logging)backend)losses)metrics)tree) serialization)object_registration)module function_typeoutput_shape_typeoutput_shape_modulec Cst|tr td|dttds:ddlm}ddlm}|jt_ |j tj d<|j tj d<|j tj d <|j tj d <|d d d }|d urY|ddkrS||d d<n||d d<|d dd }|d urt|tr{t|dkr{t|d|d d<nt|ttfrt||d d<|ddkrtD] }|d |d }q|d d}t|trdid} |d| d d<|d| d d<|d| d d<| |d d<tj|tj |ddS)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_OBJECTSr)layers)models InputLayer FunctionalModel Sequentialconfigbatch_input_shapeN class_name batch_shape input_shapeaxisLambdafunction __lambda__rrcodedefaultsclosurelayer)module_objectscustom_objectsprintable_module_name) isinstancelist TypeErrorhasattrMODULE_OBJECTS keras.srcrr__dict__r rrrrpoplenintfloatLAMBDA_DEP_ARGSrdeserialize_keras_object) rr%rrrrdep_arg_function_config function_dictr8_/var/www/html/chatgem/venv/lib/python3.10/site-packages/keras/src/legacy/saving/saving_utils.pymodel_from_configsR               r:Tc Csddlm}d|jji}z||d<Wnty*}z |r |WYd}~nd}~wwtt|t|d}t |ddrd|rd|j rd|j j }| ddt||d <t|jj|jd }||d d <|S) z3Returns a dictionary containing the model metadata.r) __version__rrN) keras_versionr model_config optimizerFtraining_configroptimizer_config)r,r; __class____name__ get_configNotImplementedErrordictstrrgetattrcompiled_compile_configrr._serialize_nested_configrget_registered_namer>) modelinclude_optimizerrequire_configr<r=emetadatar?r@r8r8r9model_metadata[s:     rQc Cs|duri}t|addlm}|d}||}t|||}d}|dd}|dur9ttj|}t||t}d}|dd}|durPtt |}t||t }d} |dd} | duratt | } |d} Wdn1sowYt |||| | d S) z4Return model.compile arguments from training config.Nr) optimizersr@lossrweighted_metrics loss_weights)r>rSrrTrU) rCustomObjectScoper,rR deserialize!_resolve_compile_arguments_compatget_deserialize_nested_configr_deserialize_metricmetrics_modulerE) r?r%rRr@r>rS loss_configrmetrics_configrTweighted_metrics_configrUr8r8r9!compile_args_from_training_config|sL         (r`cCsdd}t||S)z/Serialized a nested structure of Keras objects.cSst|r t|S|SN)callablerserialize_keras_objectobjr8r8r9 _serialize_fns z/_serialize_nested_config.._serialize_fn)r map_structure)rrfr8r8r9rJs rJcstdd}|dur dS||r|St|tr"fdd|DSt|ttfr2fdd|DStd|d ) z=Deserializes arbitrary Keras `config` using `deserialize_fn`.cSs(t|tr d|vr dSt|trdSdS)NrTF)r'rErFrdr8r8r9_is_single_objects  z5_deserialize_nested_config.._is_single_objectNcsi|] \}}|t|qSr8rZ).0kvdeserialize_fnr8r9 s z._deserialize_nested_config..csg|]}t|qSr8ri)rjrermr8r9 s z._deserialize_nested_config..zrSaved configuration not understood. Configuration should be a dictionary, string, tuple or list. Received: config=.)r'rEitemstupler( ValueError)rnrrhr8rmr9rZs$   rZcCs|dvr|St|S)z7Deserialize metrics, leaving special strings untouched.)accuracyacc crossentropyce)r\rW) metric_configr8r8r9r[s r[cCs*t|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'rFALL_OBJECTS_DICTrY)re obj_configr r8r8r9rXsrXcCsTz|jjs |j|j|jjs|j|j|jWdSWdStdYdS)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)rLr8r8r9try_build_compiled_argumentss rra)TT) threadingabslrr,rrrr\rkeras.src.legacy.savingrkeras.src.savingrlocalr+r2r:rQr`rJrZr[rXrr8r8r8r9s$         D !6