





'''simple docstring'''






import os
import sys

__UpperCamelCase					    =	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,
)


__UpperCamelCase					    =	[
    "torch",
    "numpy",
    "tokenizers",
    "filelock",
    "requests",
    "tqdm",
    "regex",
    "sentencepiece",
    "sacremoses",
    "importlib_metadata",
    "huggingface_hub",
]







@add_start_docstrings(AutoConfig.__doc__ )
def 					_a						(       *_lowerCamelCase    ,	**_lowerCamelCase ) ->				Tuple:



			"""simple docstring"""


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







@add_start_docstrings(AutoTokenizer.__doc__ )
def 					_a						(       *_lowerCamelCase    ,	**_lowerCamelCase ) ->				List[Any]:



			"""simple docstring"""


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







@add_start_docstrings(AutoModel.__doc__ )
def 					_a						(       *_lowerCamelCase    ,	**_lowerCamelCase ) ->				Union[str, Any]:



			"""simple docstring"""


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







@add_start_docstrings(AutoModelForCausalLM.__doc__ )
def 					_a						(       *_lowerCamelCase    ,	**_lowerCamelCase ) ->				Dict:



			"""simple docstring"""


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







@add_start_docstrings(AutoModelForMaskedLM.__doc__ )
def 					_a						(       *_lowerCamelCase    ,	**_lowerCamelCase ) ->				Dict:



			"""simple docstring"""


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







@add_start_docstrings(AutoModelForSequenceClassification.__doc__ )
def 					_a						(       *_lowerCamelCase    ,	**_lowerCamelCase ) ->				Union[str, Any]:



			"""simple docstring"""


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







@add_start_docstrings(AutoModelForQuestionAnswering.__doc__ )
def 					_a						(       *_lowerCamelCase    ,	**_lowerCamelCase ) ->				Optional[int]:



			"""simple docstring"""


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









'''simple docstring'''






def 					_a						(       _lowerCamelCase ) ->				int:



			"""simple docstring"""


			if not isinstance(_lowerCamelCase    ,	_lowerCamelCase ):
						raise TypeError("""only integers accepted as input""" )
			else:
						__snake_case					:      List[Any]							      =     str(abs(_lowerCamelCase ) )
						__snake_case					:      Union[str, Any]							      =     [list(_lowerCamelCase ) for char in range(len(_lowerCamelCase ) )]
						for index in range(len(_lowerCamelCase ) ):
									num_transpositions[index].pop(_lowerCamelCase )
						return max(
						    int("""""".join(list(_lowerCamelCase ) ) ) for transposition in num_transpositions )


if __name__ == "__main__":
	__import__("doctest").testmod()


