

from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments





def    _A							(						)   -> Tuple:



   """simple docstring"""


   __SCREAMING_SNAKE_CASE       =				HfArgumentParser(__snake_case  )
   __SCREAMING_SNAKE_CASE       =				parser.parse_args_into_dataclasses()[0]
   __SCREAMING_SNAKE_CASE       =				TensorFlowBenchmark(args=__snake_case  )
   try:
      __SCREAMING_SNAKE_CASE       =				parser.parse_args_into_dataclasses()[0]
   except ValueError as e:
      __SCREAMING_SNAKE_CASE       =				"Arg --no_{0} is no longer used, please use --no-{0} instead."
      __SCREAMING_SNAKE_CASE       =				" ".join(str(__snake_case  ).split(" "  )[:-1]  )
      __SCREAMING_SNAKE_CASE       =				""
      __SCREAMING_SNAKE_CASE       =				eval(str(__snake_case  ).split(" "  )[-1]  )
      __SCREAMING_SNAKE_CASE       =				[]
      for arg in depreciated_args:
         # arg[2:] removes '--'
         if arg[2:] in TensorFlowBenchmark.deprecated_args:
            # arg[5:] removes '--no_'
            full_error_msg += arg_error_msg.format(arg[5:]  )
         else:
            wrong_args.append(__snake_case  )
      if len(__snake_case  ) > 0:
         __SCREAMING_SNAKE_CASE       =				full_error_msg + begin_error_msg + str(__snake_case  )
      raise ValueError(__snake_case  )
   benchmark.run()


if __name__ == "__main__":
     main()





'''simple docstring'''






from __future__ import annotations

from random import choice


def    _snake_case  (	A			)		->       int:
							return choice(A			)


def    _snake_case  (	A					,       A			)		->       int:
							lowerCAmelCase__			  =      random_pivot(A			)

							# partition based on pivot
							# linear time
							lowerCAmelCase__			  =      [e for e in lst if e < pivot]
							lowerCAmelCase__			  =      [e for e in lst if e > pivot]

							# if we get lucky, pivot might be the element we want.
							# we can easily see this:
							# small (elements smaller than k)
							# + pivot (kth element)
							# + big (elements larger than k)
							if len(A			) == k - 1:
														return pivot
							# pivot is in elements bigger than k
							elif len(A			) < k - 1:
														return kth_number(A					,       k - len(A			) - 1			)
							# pivot is in elements smaller than k
							else:
														return kth_number(A					,       A			)


if __name__ == "__main__":
		import doctest

		doctest.testmod()