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  d Z ddlZddlZddlZddlZddlZddlZddlZddlZddl	Z	ddl
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 Z$dee%ej&f ddfddZ'dee%ej&f dee% fddZ(dee%ej&f dee% fddZ)dee%ej&f dee% fddZ*dee%ej&f dee% fddZ+ddde%dee%ej&f de,dej-fddZ.									d:d ee%ej&f de%d!eee%ej&f  d"e,d#ee, d$eee%e%f  d%eee,e%f  d&ee% d'e,d(ee% d)ee% de%fd*d+Z/									d:d,e%d ee%ej&f d!eee%ej&f  d"e,d#ee, d$eee%e%f  d%eee,e%f  d&ee% d'e,d(ee% d-ee% dej-fd.d/Z0d;d0ed1ee%ej&f d2ee dee% fd3d4Z1d5d6 Z2d7Z3d8d9 Z4dS )<z3Utilities to dynamically load objects from the Hub.    N)Path)
ModuleType)AnyDictListOptionalUnion)try_to_load_from_cache   )HF_MODULES_CACHE TRANSFORMERS_DYNAMIC_MODULE_NAMEcached_fileextract_commit_hashis_offline_modeloggingc                  C   sT   t tjv rdS tjt  tjt dd tt d } |  s(|   t	
  dS dS )z_
    Creates the cache directory for modules with an init, and adds it to the Python path.
    NTexist_ok__init__.py)r   syspathappendosmakedirsr   existstouch	importlibinvalidate_caches)	init_path r   c/mnt/skqttb/ctump_chatbot/chatbot/lib/python3.10/site-packages/transformers/dynamic_module_utils.pyinit_hf_modules1   s   
r    namereturnc                 C   s`   t   tt|   }|j st|j tj|dd |d }| s.|	  t
  dS dS )z
    Creates a dynamic module in the cache directory for modules.

    Args:
        name (`str` or `os.PathLike`):
            The name of the dynamic module to create.
    Tr   r   N)r    r   r   resolveparentr   create_dynamic_moduler   r   r   r   r   )r!   dynamic_module_pathr   r   r   r   r%   A   s   

r%   module_filec                 C   sj   t | ddd}| }W d   n1 sw   Y  tjd|tjd}|tjd|tjd7 }tt|S )z
    Get the list of modules that are relatively imported in a module file.

    Args:
        module_file (`str` or `os.PathLike`): The module file to inspect.

    Returns:
        `List[str]`: The list of relative imports in the module.
    rutf-8encodingNz^\s*import\s+\.(\S+)\s*$flagsz^\s*from\s+\.(\S+)\s+import)openreadrefindall	MULTILINElistset)r'   fcontentrelative_importsr   r   r   get_relative_importsW   s   

r8   c                    s   d}| g}g  |sBg }|D ]	}| t| qt| jfdd|D } fdd|D }dd |D }t|dk}  | |r	 S )a  
    Get the list of all files that are needed for a given module. Note that this function recurses through the relative
    imports (if a imports b and b imports c, it will return module files for b and c).

    Args:
        module_file (`str` or `os.PathLike`): The module file to inspect.

    Returns:
        `List[str]`: The list of all relative imports a given module needs (recursively), which will give us the list
        of module files a given module needs.
    Fc                    s   g | ]}t  | qS r   )str).0m)module_pathr   r   
<listcomp>       z-get_relative_import_files.<locals>.<listcomp>c                    s   g | ]}| vr|qS r   r   r:   r5   )all_relative_importsr   r   r=      r>   c                 S   s   g | ]}| d qS ).pyr   r?   r   r   r   r=          r   )extendr8   r   r$   len)r'   	no_changefiles_to_checknew_importsr5   new_import_filesr   )r@   r<   r   get_relative_import_filesl   s   

rI   filenamec                 C   s   t | ddd}| }W d   n1 sw   Y  tjdd|tjd}tjdd|tjd}tjd	|tjd}|tjd
|tjd7 }dd |D }tt|S )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.

    Returns:
        `List[str]`: The list of all packages required to use the input module.
    r(   r)   r*   Nz\s*try\s*:.*?except.*?: r,   zHif is_flash_attn[a-zA-Z0-9_]+available\(\):\s*(from flash_attn\s*.*\s*)+z^\s*import\s+(\S+)\s*$z^\s*from\s+(\S+)\s+importc                 S   s$   g | ]}| d s|d d qS ).r   )
startswithsplit)r:   impr   r   r   r=      s   $ zget_imports.<locals>.<listcomp>)	r.   r/   r0   subDOTALLr2   r1   r3   r4   )rJ   r5   r6   importsr   r   r   get_imports   s   


rS   c                 C   s   t | }g }|D ]3}zt| W q ty; } ztd| d|  dt|v r0|| n W Y d}~qd}~ww t|dkrStdd	| dd		| d
t
| S )a.  
    Check if the current Python environment contains all the libraries that are imported in a file. Will raise if a
    library is missing.

    Args:
        filename (`str` or `os.PathLike`): The module file to check.

    Returns:
        `List[str]`: The list of relative imports in the file.
    z&Encountered exception while importing z: zNo module namedNr   z\This modeling file requires the following packages that were not found in your environment: z, z. Run `pip install  `)rS   r   import_moduleImportErrorloggerwarningr9   r   rD   joinr8   )rJ   rR   missing_packagesrO   	exceptionr   r   r   check_imports   s,   
r]   Fforce_reload
class_namer<   r_   c          
      C   s"  t j|}|dr|dd }|t jjd}tt| }tf |r/t	j
|d t  t	j
|}tjj||d}|gtttt| }tddd |D  }|du rhtj|}	|	t	j
|< n|}	t|	d	d
|kr{|j|	 ||	_t|	| W  d   S 1 sw   Y  dS )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.
    rA   NrL   )location    c                 s   s     | ]}t ||  V  qd S N)bytes
read_bytesr?   r   r   r   	<genexpr>   s    z&get_class_in_module.<locals>.<genexpr>__transformers_module_hash__rK   )r   r   normpathendswithreplacesepr   r   _HF_REMOTE_CODE_LOCKr   modulespopr   r   getutilspec_from_file_locationsortedmaprI   hashlibsha256rZ   	hexdigestmodule_from_specgetattrloaderexec_modulerh   )
r`   r<   r_   r!   r'   cached_modulemodule_specmodule_filesmodule_hashmoduler   r   r   get_class_in_module   s,   
$r   pretrained_model_name_or_path	cache_dirforce_downloadresume_downloadproxiestokenrevisionlocal_files_only	repo_type_commit_hashc                 K   s  | dd}|durtdt |durtd|}t r&|s&td d}t| } t	j
| }|r9t	j
| }n| dt	j
j}t| |||
|	d}g }zt| |||||||||	|
d	}|sg||krg|| W n ty|   td
| d|  d  w t|}tt	j
j | }t| tt| }|t	j
| kr||  rt|t|| st|||  t  |D ]*}| d}t	j
 | |}||  rt|t|| st|||  t  qnQt!||
}|| }|t	j
j | }t| ||  st|||  t  |D ]&}|| d  s4t"| | d||||||||d
 || d qt#|dkrk|du rkd dd |D }|	du rSdn|	 d}d| |  }t$d| d| d t	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).

    <Tip>

    Passing `token=True` is required when you want to use a private model.

    </Tip>

    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/)r   r   r   )	r   r   r   r   r   r   r   r   r   zCould not locate the z inside rL   rA   )r   r   r   r   r   r   r   r   r   
c                 S   s   g | ]}d | qS )z- r   r?   r   r   r   r=     rB   z*get_cached_module_file.<locals>.<listcomp>rK   zs/zhttps://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.)%ro   warningswarnFutureWarning
ValueErrorr   rX   infor9   r   r   isdirbasenamerk   rl   r	   r   r   EnvironmentErrorerrorr]   r   r%   r   r   r   filecmpcmpshutilcopyr   r   rZ   r   get_cached_module_filerD   rY   )r   r'   r   r   r   r   r   r   r   r   r   deprecated_kwargsr   is_local	submoduler|   	new_filesresolved_module_filemodules_neededfull_submodulesubmodule_pathmodule_neededmodule_needed_filecommit_hashrepo_type_strurlr   r   r   r      s   >






r   class_referencecode_revisionc                 K   s   | dd}|durtdt |durtd|}d| v r&| d\}} n|}| d\}}|
du r9||kr9|}
t||d ||||||
||	d
}t|||d	S )
a>  
    Extracts a class from a module file, present in the local folder or repository of a model.

    <Tip warning={true}>

    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.

    </Tip>



    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.

    <Tip>

    Passing `token=True` is required when you want to use a private model.

    </Tip>

    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")
    ```r   Nr   r   z--rL   rA   )r   r   r   r   r   r   r   r   r^   )ro   r   r   r   r   rN   r   r   )r   r   r   r   r   r   r   r   r   r   r   kwargsr   repo_idr'   r`   final_moduler   r   r   get_class_from_dynamic_module  s8   Zr   objfolderconfigc           	         s    j dkrtd  d| d dS  fdd}t|ttfr*|D ]}|| q"n|dur2|| g }tj j  j}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__. You should put this code in a separate module so we can include it in the saved folder and make it easier to share via the Hub.Nc           
         s   j j}|dd }| d j j }d|v rYd }d } j jdrL| d j j }t dd d urKt d}|j}|dd }| d|j }n	| d j j }||f}t| tro| di }	||	 j	< |	| d< d S t| dd d ur|| j
 j	< d S  j	|i| _
d S )NrL   	TokenizerFastslow_tokenizer_classauto_map)	__class__
__module__rN   __name__rj   ry   
isinstancedictrp   _auto_classr   )
_configmodule_namelast_module	full_namer   fast_tokenizer_classslow_tokenizerslow_tok_module_namelast_slow_tok_moduler   r   r   r   _set_auto_map_in_configB  s.   


z3custom_object_save.<locals>._set_auto_map_in_config)r   rX   rY   r   r3   tupler   rn   __file__r   r!   r   r   r   rI   )	r   r   r   r   cfgresultobject_file	dest_fileneeded_filer   r   r   custom_object_save,  s,   
 

r   c                 C   s   t d)NzLoading this model requires you to execute custom code contained in the model repository on your local machine. Please set the option `trust_remote_code=True` to permit loading of this model.)r   )signumframer   r   r   _raise_timeout_errorx  s   r      c              
   C   s.  | d u r|r	d} n~|rt dkrd }z\z7ttjt}tt  | d u rCtd| d| d}| dv r7d} n| dv r?d} | d u s#td W n ty[   td| d| d	w W |d urmttj| td n|d urttj| td w w |rtd d  |r|s| std
| d| S )NFr   zThe 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] )yesy1T)non0rK   zS.
Please pass the argument `trust_remote_code=True` to allow custom code to be run.zLoading 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_CODEsignalSIGALRMr   alarminputlower	Exceptionr   )trust_remote_code
model_namehas_local_codehas_remote_codeprev_sig_handleranswerr   r   r   resolve_trust_remote_code  sV   
	


r   )	NFNNNNFNNrd   )5__doc__r   ru   r   importlib.utilr   r0   r   r   r   	threadingtypingr   pathlibr   typesr   r   r   r   r   r   huggingface_hubr	   utilsr   r   r   r   r   r   
get_loggerr   rX   Lockrm   r    r9   PathLiker%   r8   rI   rS   r]   boolTyper   r   r   r   r   r   r   r   r   r   r   <module>   s    

   ! '
4	

 4	

.}L