






"""simple docstring"""


from __future__ import annotations




def       snake_case  (A_				:Dict     ,      A_				:Optional[int]     ,      A_				:Optional[Any]				):







  '''simple docstring'''

  if len(__lowerCamelCase				) == 0:
    raise ValueError('find_max() arg is an empty sequence'				)
  if (
      left >= len(__lowerCamelCase				)
      or left < -len(__lowerCamelCase				)
      or right >= len(__lowerCamelCase				)
      or right < -len(__lowerCamelCase				)
  ):
    raise IndexError('list index out of range'				)
  if left == right:
    return nums[left]
  _A					:      int    =       (left + right) >> 1  # the middle
  _A					:      Union[str, Any]    =       find_max(__lowerCamelCase     ,      __lowerCamelCase     ,      __lowerCamelCase				)  # find max in range[left, mid]
  _A					:      Any    =       find_max(__lowerCamelCase     ,      mid + 1     ,      __lowerCamelCase				)  # find max in range[mid + 1, right]

  return left_max if left_max >= right_max else right_max


if __name__ == "__main__":
   import doctest

   doctest.testmod(verbose=True)












"""simple docstring"""


import os
import sys

_UpperCamelCase    :   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,
)


_UpperCamelCase    :   int   			=						[
    'torch',
    'numpy',
    'tokenizers',
    'filelock',
    'requests',
    'tqdm',
    'regex',
    'sentencepiece',
    'sacremoses',
    'importlib_metadata',
    'huggingface_hub',
]




@add_start_docstrings(AutoConfig.__doc__				)
def       snake_case  (*A_				:Optional[int]     ,      **A_				:int				):







  '''simple docstring'''

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




@add_start_docstrings(AutoTokenizer.__doc__				)
def       snake_case  (*A_				:Optional[int]     ,      **A_				:List[Any]				):







  '''simple docstring'''

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




@add_start_docstrings(AutoModel.__doc__				)
def       snake_case  (*A_				:Optional[Any]     ,      **A_				:Tuple				):







  '''simple docstring'''

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




@add_start_docstrings(AutoModelForCausalLM.__doc__				)
def       snake_case  (*A_				:str     ,      **A_				:Optional[int]				):







  '''simple docstring'''

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




@add_start_docstrings(AutoModelForMaskedLM.__doc__				)
def       snake_case  (*A_				:Optional[Any]     ,      **A_				:Dict				):







  '''simple docstring'''

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




@add_start_docstrings(AutoModelForSequenceClassification.__doc__				)
def       snake_case  (*A_				:Dict     ,      **A_				:str				):







  '''simple docstring'''

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






@add_start_docstrings(AutoModelForQuestionAnswering.__doc__				)
def       snake_case  (*A_				:Dict     ,      **A_				:List[Any]				):







  '''simple docstring'''

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




