"""simple docstring"""




from __future__ import annotations





def 							SCREAMING_SNAKE_CASE					(      _lowerCamelCase						:	List[str]      ,_lowerCamelCase						:	Tuple      ,_lowerCamelCase						:	int     )	->				int | float:
  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]
  _lowerCAmelCase						:	str        =					(left + right) >> 1  # the middle
  _lowerCAmelCase						:	int        =					find_max(lowerCamelCase_      ,lowerCamelCase_      ,lowerCamelCase_     )  # find max in range[left, mid]
  _lowerCAmelCase						:	Dict        =					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"""




_a				:		Any	   =       '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'

_a				:		List[Any]	   =       [{'type': 'code', 'content': INSTALL_CONTENT}]
_a				:		Union[str, Any]	   =       {
    '{processor_class}': 'FakeProcessorClass',
    '{model_class}': 'FakeModelClass',
    '{object_class}': 'FakeObjectClass',
}




