o  hv@sdZddlZddlZddlZddlZddlZddlZddlZddlZddl Z ddl Z ddl Z ddl Z ddl mZddlmZddlmZmZmZddlmZddlmZmZmZmZmZmZeeZ e !Z"d d Z#d ee$ej%fd dfd dZ&dee$ej%fd e'e$fddZ(dee$ej%fd e'e$fddZ)dee$ej%fd e'e$fddZ*dee$ej%fd e'e$fddZ+ddde$dee$ej%fde,d e-fddZ.         d:d ee$ej%fde$d!eee$ej%fd"e,d#ee,d$ee/e$e$fd%eee,e$fd&ee$d'e,d(ee$d)ee$d e$fd*d+Z0         d:d,e$d ee$ej%fd!eee$ej%fd"e,d#ee,d$ee/e$e$fd%eee,e$fd&ee$d'e,d(ee$d-ee$d e-fd.d/Z1d;d0ed1ee$ej%fd2ee/d e'e$fd3d4Z2d5d6Z3d7Z4d8d9Z5dS)z-get_relative_import_files..csg|]}|vr|qSrrr6r1)all_relative_importsrrr9r:cSsg|]}|dqS).pyrr;rrrr9r)extendr4rr"len)r% no_changefiles_to_check new_importsr1new_import_filesr)r<r8rget_relative_import_filesks     rEfilenamecsbt|dd }|}Wdn1swYtfddt|}|tS)a Extracts all the libraries (not relative imports this time) that are imported in a file. Args: filename (`str` or `os.PathLike`): The module file to inspect. 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Returns: `list[str]`: The list of relative imports in the file. z&Encountered exception while importing z: zNo module namedNrz\This modeling file requires the following packages that were not found in your environment: z, z. Run `pip install  `) rhr import_module ImportErrorloggerwarningr5rr@joinr4)rFimportsmissing_packagesimp exceptionrrr check_importss,     rtF force_reload class_namer8rvc Cs"tj|}|dr|dd}|tjjd}tt|}tf|r/t j |dt t j |}t jj||d}|gtttt|}tddd|D}|durht j|} | t j |<n|} t| d d |kr{|j| || _t| |WdS1swYdS) a Import a module on the cache directory for modules and extract a class from it. Args: class_name (`str`): The name of the class to import. module_path (`str` or `os.PathLike`): The path to the module to import. force_reload (`bool`, *optional*, defaults to `False`): Whether to reload the dynamic module from file if it already exists in `sys.modules`. Otherwise, the module is only reloaded if the file has changed. Returns: `typing.Type`: The class looked for. r=NrJ)locationcss |] }t||VqdSN)bytes read_bytesr;rrr sz&get_class_in_module..__transformers_module_hash__rH)rrnormpathendswithreplaceseprr _HF_REMOTE_CODE_LOCKrmodulespoprrgetutilspec_from_file_locationrfmaprEhashlibsha256ro hexdigestmodule_from_specrRloader exec_moduler) rwr8rvrr% cached_module module_spec module_files module_hashr[rrrget_class_in_modules,        $rpretrained_model_name_or_path cache_dirforce_downloadresume_downloadproxiestokenrevisionlocal_files_only repo_type _commit_hashc  Ks| dd} | durtdt|durtd| }tr&|s&tdd}t|}t j |} | r9t j |}n| dt j j}t|||| | d}g}zt|||||||||| | d }| sg||krg||Wnty|td |d |d wt|}tt j j|}t|tt|}|t j |kr||rt|t||st|||t|D]*}|d }t j ||}||rt|t||st|||tqnQt!|| }||}|t j j|}t|||s t|||t|D]&}||d s4t"||d ||||||||d ||d qt#|dkrk|durkd dd|D}| durSdn| d}d||}t$d|d|dt j ||S)a Prepares Downloads a module from a local folder or a distant repo and returns its path inside the cached Transformers module. Args: pretrained_model_name_or_path (`str` or `os.PathLike`): This can be either: - a string, the *model id* of a pretrained model configuration hosted inside a model repo on huggingface.co. - a path to a *directory* containing a configuration file saved using the [`~PreTrainedTokenizer.save_pretrained`] method, e.g., `./my_model_directory/`. module_file (`str`): The name of the module file containing the class to look for. cache_dir (`str` or `os.PathLike`, *optional*): Path to a directory in which a downloaded pretrained model configuration should be cached if the standard cache should not be used. force_download (`bool`, *optional*, defaults to `False`): Whether or not to force to (re-)download the configuration files and override the cached versions if they exist. resume_download: Deprecated and ignored. All downloads are now resumed by default when possible. Will be removed in v5 of Transformers. proxies (`Dict[str, str]`, *optional*): A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}.` The proxies are used on each request. token (`str` or *bool*, *optional*): The token to use as HTTP bearer authorization for remote files. If `True`, will use the token generated when running `huggingface-cli login` (stored in `~/.huggingface`). revision (`str`, *optional*, defaults to `"main"`): The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any identifier allowed by git. local_files_only (`bool`, *optional*, defaults to `False`): If `True`, will only try to load the tokenizer configuration from local files. repo_type (`str`, *optional*): Specify the repo type (useful when downloading from a space for instance). Passing `token=True` is required when you want to use a private model. Returns: `str`: The path to the module inside the cache. use_auth_tokenNrThe `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.V`token` and `use_auth_token` are both specified. Please set only the argument `token`.z+Offline mode: forcing local_files_only=TrueT/)rrr) rrrrrrrrrzCould not locate the z inside rJr=)rrrrrrrrr cSsg|]}d|qS)z- rr;rrrr9r>z*get_cached_module_file..rHzs/zhttps://huggingface.co/z9A new version of the following files was downloaded from z: z . Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.)%rwarningswarn FutureWarning ValueErrorr rminfor5rrisdirbasenamerrrr rOSErrorerrorrtr r#rr rfilecmpcmpshutilcopyrrror get_cached_module_filer@rn)rr%rrrrrrrrrdeprecated_kwargsris_local submoduler new_filesresolved_module_filemodules_neededfull_submodulesubmodule_path module_neededmodule_needed_file commit_hash repo_type_strurlrrrrs >            rclass_reference code_revisionc  Ks| dd} | durtdt|durtd| }d|vr&|d\} }n|} |d\}}| dur9|| kr9|} t| |d|||||| || d }t|||d S) a> Extracts a class from a module file, present in the local folder or repository of a model. Calling this function will execute the code in the module file found locally or downloaded from the Hub. It should therefore only be called on trusted repos. Args: class_reference (`str`): The full name of the class to load, including its module and optionally its repo. pretrained_model_name_or_path (`str` or `os.PathLike`): This can be either: - a string, the *model id* of a pretrained model configuration hosted inside a model repo on huggingface.co. - a path to a *directory* containing a configuration file saved using the [`~PreTrainedTokenizer.save_pretrained`] method, e.g., `./my_model_directory/`. This is used when `class_reference` does not specify another repo. module_file (`str`): The name of the module file containing the class to look for. class_name (`str`): The name of the class to import in the module. cache_dir (`str` or `os.PathLike`, *optional*): Path to a directory in which a downloaded pretrained model configuration should be cached if the standard cache should not be used. force_download (`bool`, *optional*, defaults to `False`): Whether or not to force to (re-)download the configuration files and override the cached versions if they exist. resume_download: Deprecated and ignored. All downloads are now resumed by default when possible. Will be removed in v5 of Transformers. proxies (`Dict[str, str]`, *optional*): A dictionary of proxy servers to use by protocol or endpoint, e.g., `{'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}.` The proxies are used on each request. token (`str` or `bool`, *optional*): The token to use as HTTP bearer authorization for remote files. If `True`, will use the token generated when running `huggingface-cli login` (stored in `~/.huggingface`). revision (`str`, *optional*, defaults to `"main"`): The specific model version to use. It can be a branch name, a tag name, or a commit id, since we use a git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any identifier allowed by git. local_files_only (`bool`, *optional*, defaults to `False`): If `True`, will only try to load the tokenizer configuration from local files. repo_type (`str`, *optional*): Specify the repo type (useful when downloading from a space for instance). code_revision (`str`, *optional*, defaults to `"main"`): The specific revision to use for the code on the Hub, if the code leaves in a different repository than the rest of the model. It can be a branch name, a tag name, or a commit id, since we use a git-based system for storing models and other artifacts on huggingface.co, so `revision` can be any identifier allowed by git. Passing `token=True` is required when you want to use a private model. Returns: `typing.Type`: The class, dynamically imported from the module. Examples: ```python # Download module `modeling.py` from huggingface.co and cache then extract the class `MyBertModel` from this # module. cls = get_class_from_dynamic_module("modeling.MyBertModel", "sgugger/my-bert-model") # Download module `modeling.py` from a given repo and cache then extract the class `MyBertModel` from this # module. cls = get_class_from_dynamic_module("sgugger/my-bert-model--modeling.MyBertModel", "sgugger/another-bert-model") ```rNrrz--rJr=)rrrrrrrrru)rrrrrrWrr)rrrrrrrrrrrkwargsrrepo_idr%rw final_modulerrrget_class_from_dynamic_modules8 Z robjfolderconfigc sjdkrtdd|ddSfdd}t|ttfr*|D]}||q"n|dur2||g}tjjj}t |t |j }t ||| |t|D]}t |t |j }t ||| |qS|S)a  Save the modeling files corresponding to a custom model/configuration/tokenizer etc. in a given folder. Optionally adds the proper fields in a config. Args: obj (`Any`): The object for which to save the module files. folder (`str` or `os.PathLike`): The folder where to save. config (`PretrainedConfig` or dictionary, `optional`): A config in which to register the auto_map corresponding to this custom object. Returns: `List[str]`: The list of files saved. __main__z We can't save the code defining z in z as it's been defined in __main__. 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Please set the option `trust_remote_code=True` to permit loading of this model.)r)signumframerrr_raise_timeout_errorsrc Cs.|dur|r d}n~|rtdkrd}z\z7ttjt}tt|durCtd|d|d}|dvr7d}n|dvr?d}|dus#tdWnty[td|d|d wW|durmttj|tdn|durttj|tdww|rtdd|r|s|std |d |S) NFrzThe repository for z contains custom code which must be executed to correctly load the model. You can inspect the repository content at https://hf.co/z. You can avoid this prompt in future by passing the argument `trust_remote_code=True`. Do you wish to run the custom code? [y/N] )yesy1T)non0rHzS. Please pass the argument `trust_remote_code=True` to allow custom code to be run.zLoading z requires you to execute the configuration file in that repo on your local machine. Make sure you have read the code there to avoid malicious use, then set the option `trust_remote_code=True` to remove this error.) TIME_OUT_REMOTE_CODEsignalSIGALRMralarminputlower Exceptionr)trust_remote_code model_namehas_local_codehas_remote_codeprev_sig_handleranswerrrrresolve_trust_remote_codesV           r) NFNNNNFNNr{)6__doc__rLrrrimportlib.utilrr,rrr threadingrpathlibrtypesrtypingrrrhuggingface_hubrutilsr r r r r r get_loggerrrmLockrrr5PathLiker#r/r4rErhrtbooltyperrrrrrrrrrrrs         ! 0'  4     4     .}L