a h@sdZddlZddlZddlZddlZddlZddlZddlZddlZddl Z ddl Z ddl Z ddl Z ddl Z ddlmZddlmZddlmZmZmZddlmZddlmZdd lmZmZmZmZmZm Z dd l!m"Z"m#Z#e $e%Z&e 'Z(d d Z)ee*ej+fdd ddZ,ee*ej+fe-e*dddZ.ee*ej+fe-e*dddZ/ee*ej+fe-e*dddZ0ee*ej+fe-e*dddZ1dde*ee*ej+fe2e3dddZ4d0ee*ej+fe*eee*ej+fe2ee2ee5e*e*feee2e*fee*e2ee*ee*e*d d d!Z6d1e*ee*ej+feee*ej+fe2ee2ee5e*e*feee2e*fee*e2ee*ee*e3d" d#d$Z7d2eee*ej+fee5e-e*d%d&d'Z8d(d)Z9d*Z:d3d+d,Z;d4d.d/Zz-get_relative_import_files..csg|]}|vr|qSrrr8r3)all_relative_importsrr r;r<r)extendr5rr%len)r'Z no_changeZfiles_to_checkZ new_importsr3Znew_import_filesr)r>r:r get_relative_import_filesns    rA)filenamer#cslt|dd}|}Wdn1s*0Ytddlfddt|}|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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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 `hf auth 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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To avoid downloading new versions of the code file, you can pin a revision.)&r}warningswarn FutureWarning ValueErrorrriinfor7rrisdirbasenameryrzrr rOSErrorrnr r&rr rfilecmpcmpr%mkdirshutilcopyrrrkr get_cached_module_filer@rj)rr'rrrrrrrrrZdeprecated_kwargsris_local submodulerZ new_filesZresolved_module_fileZmodules_neededZfull_submoduleZsubmodule_pathZ module_neededZmodule_needed_fileZ commit_hashZfull_submodule_module_file_pathZ repo_type_strurlrrr rs>            r) class_referencerrrrrrrrr code_revisionr#c  Ks| dd} | dur4tdt|dur0td| }d|vrL|d\} }n|} |d\}}| durr|| krr|} t| |d|||||| || d }t|||d S) a6 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 `hf auth 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--rFr6)rrrrrrrrro)r}rrrrrVrr)rrrrrrrrrrrkwargsrZrepo_idr'rqZ final_modulerrr get_class_from_dynamic_modules8Z  r)objfolderconfigr#c sjdkr&tdd|ddSfdd}t|ttfrT|D] }||qDn|durd||g}tjjj}t |t |j }t ||| |t|D],}t |t |j }t ||| |q|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|durd|dur*d|d|d|d}n:tj|rRd|dtj|d}nd|d|d}|dur||rzd}n|rltd krld}zzfttjt}tt|durt |d |d }| d vrd }q| dvrd}qtd Wn(t yt |d |dYn0W|durjttj|td n$|durhttj|td 0n|r|tdd|r|s|st |d |d|S)a Resolves the `trust_remote_code` argument. If there is remote code to be loaded, the user must opt-in to loading it. Args: trust_remote_code (`bool` or `None`): User-defined `trust_remote_code` value. model_name (`str`): The name of the model repository in huggingface.co. has_local_code (`bool`): Whether the model has local code. has_remote_code (`bool`): Whether the model has remote code. error_message (`str`, *optional*): Custom error message to display if there is remote code to load and the user didn't opt-in. If unset, the error message will be regarding loading a model with custom code. Returns: The resolved `trust_remote_code` value. 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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_idrBrN#)NNz (installed: None)Tz (installed: )z4Missing requirements in your local environment for `z`: r)r r, readlinesstriprQrrrmetadatarPackageNotFoundErrorrrZ from_stringrarrhrk) rZrequirements_filerfailed requirementsr3 requirement package_name delimiterZversion_numberZlocal_package_versionZ is_satisfiedrrr check_python_requirementss@  &  r) NFNNNNFNN) NFNNNNFNN)N)NN)r)=__doc__rHrrrimportlib.metadataimportlib.utilrr.rrr threadingrpathlibrtypesrtypingrrrZhuggingface_hubr packagingrrSr r r r rrZutils.import_utilsrrZ get_loggerrriLockr{r!r7PathLiker&r1r5rArdrnbooltyperrrrrrrrrrrrr s       7'  4  6  }(L U