




import os
import sys

snake_case_ : str    		=       os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


snake_case_ : Union[str, Any]    		=       [
    "torch",
    "numpy",
    "tokenizers",
    "filelock",
    "requests",
    "tqdm",
    "regex",
    "sentencepiece",
    "sacremoses",
    "importlib_metadata",
    "huggingface_hub",
]


@add_start_docstrings(AutoConfig.__doc__       )
def    A						(*__A   :    Union[str, Any]   ,				**__A   :    Union[str, Any]       )   ->      List[Any]:







     """simple docstring"""


     return AutoConfig.from_pretrained(*__A   ,				**__A       )


@add_start_docstrings(AutoTokenizer.__doc__       )
def    A						(*__A   :    Any   ,				**__A   :    str       )   ->      Optional[int]:







     """simple docstring"""


     return AutoTokenizer.from_pretrained(*__A   ,				**__A       )


@add_start_docstrings(AutoModel.__doc__       )
def    A						(*__A   :    Dict   ,				**__A   :    List[str]       )   ->      Optional[Any]:







     """simple docstring"""


     return AutoModel.from_pretrained(*__A   ,				**__A       )


@add_start_docstrings(AutoModelForCausalLM.__doc__       )
def    A						(*__A   :    Optional[int]   ,				**__A   :    Tuple       )   ->      List[Any]:







     """simple docstring"""


     return AutoModelForCausalLM.from_pretrained(*__A   ,				**__A       )


@add_start_docstrings(AutoModelForMaskedLM.__doc__       )
def    A						(*__A   :    Optional[int]   ,				**__A   :    Union[str, Any]       )   ->      Optional[int]:







     """simple docstring"""


     return AutoModelForMaskedLM.from_pretrained(*__A   ,				**__A       )


@add_start_docstrings(AutoModelForSequenceClassification.__doc__       )
def    A						(*__A   :    int   ,				**__A   :    int       )   ->      List[Any]:







     """simple docstring"""


     return AutoModelForSequenceClassification.from_pretrained(*__A   ,				**__A       )


@add_start_docstrings(AutoModelForQuestionAnswering.__doc__       )
def    A						(*__A   :    List[Any]   ,				**__A   :    Any       )   ->      Optional[Any]:







     """simple docstring"""


     return AutoModelForQuestionAnswering.from_pretrained(*__A   ,				**__A       )










from pathlib import PurePosixPath
from typing import Optional

import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo

from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url







class 		_snake_case  (      _snake_case							):
 SCREAMING_SNAKE_CASE__      =       ''
 SCREAMING_SNAKE_CASE__      =       'hf-legacy'  # "hf://"" is reserved for hffs




 def __init__(		self					,  _lowerCamelCase = None					,  _lowerCamelCase = None					,  **_lowerCamelCase					,  ):
       super().__init__(self					,  **_lowerCamelCase    )
       a						:Union[str, Any] 							=       repo_info
       a						:int 							=       token
       a						:int 							=       None




 def        SCREAMING_SNAKE_CASE__				(		self    ):
       if self.dir_cache is None:
             a						:Dict 							=       {}
             for hf_file in self.repo_info.siblings:
                   # TODO(QL): add sizes
                   a						:List[Any] 							=       {
                       '''name''': hf_file.rfilename,
                       '''size''': None,
                       '''type''': '''file''',
                   }
                   self.dir_cache.update(
                       {
                           str(_lowerCamelCase    ): {'''name''': str(_lowerCamelCase    ), '''size''': None, '''type''': '''directory'''}
                           for d in list(PurePosixPath(hf_file.rfilename    ).parents    )[:-1]
                       }    )




 def        SCREAMING_SNAKE_CASE__				(		self					,  _lowerCamelCase					,  _lowerCamelCase = "rb"					,  **_lowerCamelCase					,  ):
       if not isinstance(self.repo_info					,  _lowerCamelCase    ):
             raise NotImplementedError(F'''Open is only implemented for dataset repositories, but got {self.repo_info}'''    )
       a						:Optional[int] 							=       hf_hub_url(self.repo_info.id					,  _lowerCamelCase					,  revision=self.repo_info.sha    )
       return fsspec.open(
           _lowerCamelCase					,  mode=_lowerCamelCase					,  headers=get_authentication_headers_for_url(_lowerCamelCase					,  use_auth_token=self.token    )					,  client_kwargs={'''trust_env''': True}					,  ).open()




 def        SCREAMING_SNAKE_CASE__				(		self					,  _lowerCamelCase					,  **_lowerCamelCase    ):
       self._get_dirs()
       a						:Union[str, Any] 							=       self._strip_protocol(_lowerCamelCase    )
       if path in self.dir_cache:
             return self.dir_cache[path]
       else:
             raise FileNotFoundError(_lowerCamelCase    )




 def        SCREAMING_SNAKE_CASE__				(		self					,  _lowerCamelCase					,  _lowerCamelCase=False					,  **_lowerCamelCase    ):
       self._get_dirs()
       a						:str 							=       PurePosixPath(path.strip('''/'''    )    )
       a						:Tuple 							=       {}
       for p, f in self.dir_cache.items():
             a						:Optional[int] 							=       PurePosixPath(p.strip('''/'''    )    )
             a						:str 							=       p.parent
             if root == path:
                   a						:List[str] 							=       f
       a						:Any 							=       list(paths.values()    )
       if detail:
             return out
       else:
             return sorted(f['''name'''] for f in out    )





