o NiB@sddlmZddlZddlZddlZddlZddlZddlm Z m Z m Z ddl m Z mZddlZddlmZddlmZmZddlmZdd lmZmZmZd hZd d ZdddZdddZe GdddeZ e Gddde Z!e Gddde!Z"dS)) annotationsN)asdict dataclassfield)OptionalUnion)hf_hub_download)PushToHubMixinhttp_user_agent) __version__) CONFIG_NAMEPeftTypeTaskType peft_typecCs>t|jj}t|t|}|D]}||=q||fS)aMake 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_kwargskeyr?/home/ubuntu/.local/lib/python3.10/site-packages/peft/config.py_check_and_remove_unused_kwargs%s rversionstrreturnboolcCstj|jduSN) packagingrVersiondev)rrrr_is_dev_version4sr'pkg_name str | NonecCs~ztj|}Wn tjjyYdSw|jpgD]"}|jdkr config that is trying to be loaded is missing required keys: rCzUnexpected keyword arguments z for class a,, these are ignored. This probably means that you're loading a configuration file that was saved using a higher version of the library and additional parameters have been introduced since. It is highly recommended to upgrade the PEFT version before continuing (e.g. by running `pip install -U peft`).Nr) peft.mappingrk TypeErrorr rMIN_EXPECTED_CONFIG_KEYSissubsetrr__name__rOrPsortedfrom_peft_type) rrrkr config_clsconfigexcfiltered_kwargsrrrrrrs2    zPeftConfigMixin.from_peft_typepretrained_model_name_or_path subfolderc Ks|dur tj||n|}||\}}}d|vrt|d<tjtj|tr1tj|t}n&z t|tfd|i|}WntyV} z t dtd|d| d} ~ ww| |} i|| }|j di|}|j di|S)a This method loads the configuration of your adapter model from a directory. Args: pretrained_model_name_or_path (`str`): The directory or the Hub repository id where the configuration is saved. kwargs (additional keyword arguments, *optional*): Additional keyword arguments passed along to the child class initialization. N user_agentrx Can't find '' at ''r) r\r8rF _split_kwargsr r]r rrNrEfrom_json_file check_kwargsrr) rrwrxrr8hf_hub_download_kwargs class_kwargs_ config_fileruloaded_attributesrrrfrom_pretraineds2     zPeftConfigMixin.from_pretrainedpath_json_filecKsNt| }t|}Wdn1swYd|vr%td|d=|S)z 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.)rcr2loadrOrP)rrrfile json_objectrrrr~ s zPeftConfigMixin.from_json_filecCsbi}i}i}|D]!\}}|ttjvr|||<q |t|jvr'|||<q |||<q |||fSr#)rarrrrrD__annotations__)rrrr other_kwargsrrgrrrr}s    zPeftConfigMixin._split_kwargsmodel_idc Ks|dd}|durtj||n|}tjtj|tr&tj|t}nz t|tfi|}WntyCtdtd|dw| |}|dS)Nrxrzr{r|r) r6r\r8rFr]r rrNrEr~)rrrrxr8rrrrr_get_peft_type/s   zPeftConfigMixin._get_peft_typecKs|S)zCheck kwargs before initializing the config instance. Subclasses can override this method to add specific checks. r)rrrrrrHszPeftConfigMixin.check_kwargsr"cCdS)V Utility method to check if the configuration is for prompt learning. FrrHrrris_prompt_learningQz"PeftConfigMixin.is_prompt_learningcCr)z1Return True if this is an adaption prompt config.FrrHrrris_adaption_promptXsz"PeftConfigMixin.is_adaption_prompt)r!r )r!rR)rTr r!rUr#)rwr rxrA)rr )rr r!r")rp __module__ __qualname____doc__rr?rrr@rBrJ staticmethodrGrSrj classmethodrrrr~r}rrpropertyrrrrrrr;Ls:     ! @#     r;c@seZdZUdZedddidZded<edddidZded <eddd idZd ed <eddd idZ ded<edddidZ ded<dS) PeftConfiga 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=rAbase_model_name_or_pathz'The specific base model version to use.revisionz Peft typezOptional[Union[str, PeftType]]rz Task typezOptional[Union[str, TaskType]]r?FzWhether to use inference moder"inference_mode) rprrrrrrrrr?rrrrrr^s  rc@seZdZUdZedddidZded<edddidZded <eddd idZd ed <eddd idZ d ed<edddidZ d ed<edddidZ ded<e dddZ dS)PromptLearningConfigaY 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