


'''simple docstring'''




import os
import sys

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





@add_start_docstrings(AutoConfig.__doc__				)
def 	a_					( *lowerCamelCase	:     Union[str, Any]	, **lowerCamelCase	:     Optional[Any]				):
   return AutoConfig.from_pretrained(*__UpperCAmelCase	, **__UpperCAmelCase				)





@add_start_docstrings(AutoTokenizer.__doc__				)
def 	a_					( *lowerCamelCase	:     int	, **lowerCamelCase	:     Union[str, Any]				):
   return AutoTokenizer.from_pretrained(*__UpperCAmelCase	, **__UpperCAmelCase				)





@add_start_docstrings(AutoModel.__doc__				)
def 	a_					( *lowerCamelCase	:     Optional[int]	, **lowerCamelCase	:     Optional[Any]				):
   return AutoModel.from_pretrained(*__UpperCAmelCase	, **__UpperCAmelCase				)





@add_start_docstrings(AutoModelForCausalLM.__doc__				)
def 	a_					( *lowerCamelCase	:     str	, **lowerCamelCase	:     Optional[int]				):
   return AutoModelForCausalLM.from_pretrained(*__UpperCAmelCase	, **__UpperCAmelCase				)





@add_start_docstrings(AutoModelForMaskedLM.__doc__				)
def 	a_					( *lowerCamelCase	:     Dict	, **lowerCamelCase	:     Union[str, Any]				):
   return AutoModelForMaskedLM.from_pretrained(*__UpperCAmelCase	, **__UpperCAmelCase				)





@add_start_docstrings(AutoModelForSequenceClassification.__doc__				)
def 	a_					( *lowerCamelCase	:     int	, **lowerCamelCase	:     Optional[int]				):
   return AutoModelForSequenceClassification.from_pretrained(*__UpperCAmelCase	, **__UpperCAmelCase				)





@add_start_docstrings(AutoModelForQuestionAnswering.__doc__				)
def 	a_					( *lowerCamelCase	:     Optional[Any]	, **lowerCamelCase	:     int				):
   return AutoModelForQuestionAnswering.from_pretrained(*__UpperCAmelCase	, **__UpperCAmelCase				)












def 		lowerCAmelCase_    (  __UpperCAmelCase:			float		,   __UpperCAmelCase:			int      )      ->	float:
    if digit_amount > 0:
        return round(number - int(__UpperCAmelCase      )		,   __UpperCAmelCase      )
    return number - int(__UpperCAmelCase      )


if __name__ == "__main__":
  print(decimal_isolate(1.53, 0))
  print(decimal_isolate(35.345, 1))
  print(decimal_isolate(35.345, 2))
  print(decimal_isolate(35.345, 3))
  print(decimal_isolate(-14.789, 3))
  print(decimal_isolate(0, 2))
  print(decimal_isolate(-14.123, 1))
  print(decimal_isolate(-14.123, 2))
  print(decimal_isolate(-14.123, 3))

