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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  `) rer import_module ImportErrorloggerwarningr6rrAjoinr5)rCZimportsZmissing_packagesimp exceptionrrr check_importss,     roF force_reload class_namer9rqc 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>NrG)locationcss |] }t||VqdSN)bytes read_bytesr<rrr sz&get_class_in_module..__transformers_module_hash__rE)rrnormpathrQreplaceseprr _HF_REMOTE_CODE_LOCKrmodulespoprrgetutilspec_from_file_locationrcmaprBhashlibsha256rl hexdigestmodule_from_specrOloader exec_modulerz) rrr9rqr"r' cached_moduleZ module_specZ module_filesZ module_hashr[rrr get_class_in_modules,        $rpretrained_model_name_or_path cache_dirforce_downloadresume_downloadproxiestokenrevisionlocal_files_only repo_type _commit_hashc  Ks| dd} | durtdt|durtd| }tr&|s&tdd}t|}t j |} | r9t j |}n| dt j j}t|||| | d}g}zt|||||||||| | d }| sg||krg||Wnty|td |d |d wt|}tt j j|}t|tt|}|t j |kr||rt|t||st|||t|D]*}|d }t j ||}||rt|t||st|||tqn[t || }||}|t j j|}t j ||}tt|j!||st|||t|D]&}||d s>t"||d ||||||||d ||d qt#|dkru|duruddd|D}| dur]dn| d}d||}t$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). 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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--rGr>)rrrrrrrrrp)rrrrrrWrr)rrrrrrrrrrrkwargsrZrepo_idr'rrZ final_modulerrr get_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. 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Args: path_or_repo_id (`str` or `os.PathLike`): This can be either: - a string, the *model id* of a model repo on huggingface.co. - a path to a *directory* potentially containing the file. kwargs (`Dict[str, Any]`, *optional*): Additional arguments to pass to `cached_file`. )path_or_repo_idrCrN#)NNz (installed: None)Tz (installed: )z4Missing requirements in your local environment for `z`: rr)r r, readlinesstriprRrrrmetadatarZPackageNotFoundErrorrrZ from_stringrbrrirl) rZrequirements_filerfailed requirementsr3 requirement package_name delimiterZversion_numberZlocal_package_versionZ is_satisfiedrrr check_python_requirementssN      r) NFNNNNFNNrv)r)=__doc__rIrrrimportlib.metadataimportlib.utilrr.rrr threadingrpathlibrtypesrtypingrrrZhuggingface_hubr packagingrrTr r r r rrZutils.import_utilsrrZ get_loggerrrjLockr~r!r6PathLiker&r1r5rBrerobooltyperrrrrrrrrrrrr s          ! 7'  4     5     .}L E