>:jB SSKJr SSKrSSKrSSKrSSKrSSKrSSKJ r J r J r SSK J r Jr SSKrSSKJr SSKJrJr SSKJr SS KJrJrJr S 1rS rSS jrSS jr\ "SS\55r \ "SS\ 55r!\ "SS\!55r"g)) annotationsN)asdict dataclassfield)OptionalUnion)hf_hub_download)PushToHubMixinhttp_user_agent) __version__) CONFIG_NAMEPeftTypeTaskType peft_typec[R"UR5Rn[ UR 55[ UR 55- nUHnX M X4$)zMake PEFT configs forward-compatible by removing unused kwargs that were added in later PEFT versions. This assumes that removing the unused kwargs will not affect the default behavior. Returns the filtered kwargs and the set of removed keys. )inspect signature__init__ parameterssetkeys)clskwargssignature_parametersunexpected_kwargskeys H/home/mande/repo/quber/.venv/lib/python3.13/site-packages/peft/config.py_check_and_remove_unused_kwargsr%s\#,,S\\:EEFKKM*S1E1J1J1L-MM  K!  $$cX[RRU5RSL$N) packagingversionVersiondev)r$s r_is_dev_versionr'4s$    $ $W - 1 1 ==r c[RRU5nUR=(d /HonUR S:XdM[ R"URU5R55nURS5nU(dMbSU;dMjUSs $ g![RRa gf=f)Nzdirect_url.jsonvcs_info commit_id) importlibmetadata distributionPackageNotFoundErrorfilesnamejsonloads locate_file read_textget)pkg_namedistpath direct_urlr)s r_get_commit_hashr:9s!!..x8   b  99) )T%5%5d%;$F$F$HIJ!~~j1HxK83 ,, !     2 2sB**C  C cT\rSrSr%Sr\"SSS0S9rS\S'\"SSS 0S9rS \S '\"SSS 0S9r S \S'\"SSS0S9r S\S'Sr \ SSj5r S SjrS!Sjr\S5r\S"S#Sjj5r\S$Sj5r\S5r\S%Sj5r\S5r\S&Sj5r\S&Sj5rSrg)'PeftConfigMixinLa' This is the base configuration class for PEFT adapter models. It contains all the methods that are common to all PEFT adapter models. This class inherits from [`~transformers.utils.PushToHubMixin`] which contains the methods to push your model to the Hub. The method `save_pretrained` will save the configuration of your adapter model in a directory. The method `from_pretrained` will load the configuration of your adapter model from a directory. Args: peft_type (Union[[`~peft.utils.config.PeftType`], `str`]): The type of Peft method to use. NhelpzThe type of task.defaultr,zOptional[TaskType] task_typezThe type of PEFT model.zOptional[PeftType]rzEAn auto mapping dict to help retrieve the base model class if needed.zOptional[dict] auto_mappingz'PEFT version, leave empty to auto-fill. Optional[str] peft_versioncURbLUR[[5;a/[SURSSR [5S35eUR cUR 5Ulgg)NzInvalid task type: 'z,'. Must be one of the following task types: z, .)rAlistr ValueErrorjoinrD_get_peft_versionselfs r __post_init__PeftConfigMixin.__post_init___ss NN &T^^4>-Q&t~~&66bcgclclmucvbwwxy     $ $ 6 6 8D  %r c[n[U5(dU$[S5nUcSnUSU3-nU$![a [R "S5 SnN.f=f)NpeftUNKNOWNzA dev version of PEFT is used but there was an error while trying to determine the commit hash. Please open an issue: https://github.com/huggingface/peft/issues@)r r'r: Exceptionwarningswarn)r$git_hashs rrJ!PeftConfigMixin._get_peft_versionhstw''N !'/H$azN* ! MMS !H  !s4"AAc[U5$)zC Returns the configuration for your adapter model as a dictionary. )rrKs rto_dictPeftConfigMixin.to_dict~sd|r c >[RRU5(a[SUS35e[R"USS9 UR SS5nUR 5nUR5H)upV[U[5(dM[U5XE'M+ [RRU[5nUbX4S'[US5nUR[R "US SS 95 SSS5 g!,(df  g=f) a^ This method saves the configuration of your adapter model in a directory. Args: save_directory (`str`): The directory where the configuration will be saved. kwargs (additional keyword arguments, *optional*): Additional keyword arguments passed along to the [`~transformers.utils.PushToHubMixin.push_to_hub`] method. zProvided path (z#) should be a directory, not a fileT)exist_okauto_mapping_dictNrBw)indent sort_keys)osr8isfileAssertionErrormakedirspoprYitems isinstancerrGrIropenwriter1dumps) rLsave_directoryrr] output_dictrvalue output_pathwriters rsave_pretrainedPeftConfigMixin.save_pretraineds 77>>. ) ) ?>2BBe!fg g NT2"JJ':DAlln %++-JC%%%#';  .ggll>;?   (*; '+s #v LLKTJ K$ # #s &D Dc SSKJn SU;a USnX#nOUnU"S 0UD6nU$![anS[U5;aUe[ XA5upx[ R [UR555(d [SURS[ S35e[R"S[U5S URS 35 UR"S 0UD6nS nAU$S nAff=f) ai This method loads the configuration of your adapter model from a set of kwargs. The appropriate configuration type is determined by the `peft_type` argument. If `peft_type` is not provided, the calling class type is instantiated. 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N user_agent subfolder Can't find '' at ''ru) rbr8rI _split_kwargsr rcrr rSrHfrom_json_file check_kwargsr}) rpretrained_model_name_or_pathrrr8hf_hub_download_kwargs class_kwargs_ config_filerloaded_attributess rfrom_pretrainedPeftConfigMixin.from_pretraineds-$ GGLL6 B. 362C2CF2K/a 5 53B3D "< 0 77>>"'',,t[9 : :'',,t[9K n-1;JSWm  ..{;6L6$56!!+F+!!+F++  n < }FC`Baab!cdjmm ns8D D,D''D,c [U5n[R"U5nSSS5 SW;a[R"S5 US U$!,(df  N/=f)zt Loads a configuration file from a json file. Args: path_json_file (`str`): The path to the json file. Nruntime_configzzThe configuration file contains a `runtime_config` key. This is ignored. Runtime configurations are only valid at runtime.)rir1loadrTrU)rpath_json_filerfile json_objects rrPeftConfigMixin.from_json_file sV. !T))D/K" { * MMM ,-" !s A  Ac0n0n0nUR5HVupVU[R"[5R;aXbU'M3U[ UR 5;aXcU'MRXdU'MX X#U4$r")rgrrr rrG__annotations__)rrrr other_kwargsrrns rrPeftConfigMixin._split_kwargssu!#   ,,.JCg''8CCC.3s+S0011$)S!$)S! )&\AAr c URSS5nUb[RRX5OUn[RR [RRU[ 55(a%[RRU[ 5nO[ U[ 40UD6nURU5nUS$![a [S[ SUS35ef=f)Nrrrrr) r5rbr8rIrcrr rSrHr)rmodel_idrrr8rrs r_get_peft_typePeftConfigMixin._get_peft_type/s +..{DA 4=4Irww||H0x 77>>"'',,t[9 : :'',,t[9K P--  ..{; --  P < }F8*A!NOO Ps #C !C+c U$)ztCheck kwargs before initializing the config instance. Subclasses can override this method to add specific checks. ru)rrs rrPeftConfigMixin.check_kwargsHs  r cg)F Utility method to check if the configuration is for prompt learning. FrurKs ris_prompt_learning"PeftConfigMixin.is_prompt_learningQs r cg)z1Return True if this is an adaption prompt config.FrurKs ris_adaption_prompt"PeftConfigMixin.is_adaption_promptXsr )rD)returnrx)rdict)rlrxrNoner")rrxrrC)rrx)rrxrbool)r{ __module__ __qualname____firstlineno____doc__rrArrrBrDrM staticmethodrJrYrq classmethodr}rrrrrpropertyrr__static_attributes__rur rr<r<Ls?%*$&J]A^$_I!_$)$&JcAd$eI!e#((op$L.#(Hq?r"sL-s9* LB>>@!,!,F( B B...0 r r<c\rSrSr%Sr\"SSS0S9rS\S'\"SSS 0S9rS\S '\"SSS 0S9r S \S '\"SSS0S9r S\S'\"SSS0S9r S\S'Sr g) PeftConfigi^az This is the base configuration class to store the configuration of a [`PeftModel`]. Args: peft_type (Union[[`~peft.utils.config.PeftType`], `str`]): The type of Peft method to use. task_type (Union[[`~peft.utils.config.TaskType`], `str`]): The type of task to perform. inference_mode (`bool`, defaults to `False`): Whether to use the Peft model in inference mode. Nr>z"The name of the base model to use.r?rCbase_model_name_or_pathz'The specific base model version to use.revisionz Peft typezOptional[Union[str, PeftType]]rz Task typezOptional[Union[str, TaskType]]rAFzWhether to use inference moderinference_moderu) r{rrrrrrrrrrArrrur rrr^s.3(LM.]$DFDm;noHmo05dfVaMb0cI-c05dfVaMb0cI-c &Ba9bcNDcr rc\rSrSr%Sr\"SSS0S9rS\S'\"SSS 0S9rS\S '\"SSS 0S9r S \S '\"SSS0S9r S \S'\"SSS0S9r S \S'\"SSS0S9r S\S'\ SSj5rSrg)PromptLearningConfigira5 This is the base configuration class to store the configuration of [`PrefixTuning`], [`PromptEncoder`], or [`PromptTuning`]. Args: num_virtual_tokens (`int`): The number of virtual tokens to use. token_dim (`int`): The hidden embedding dimension of the base transformer model. num_transformer_submodules (`int`): The number of transformer submodules in the base transformer model. num_attention_heads (`int`): The number of attention heads in the base transformer model. num_layers (`int`): The number of layers in the base transformer model. Nr>zNumber of virtual tokensr?intnum_virtual_tokensz