


from __future__ import annotations

import math
from collections.abc import Callable







def        SCREAMING_SNAKE_CASE_						(			__A :			Callable[[int | float], int | float]  ,    __A :			int | float  ,    __A :			int | float  ,    __A :			int = 1_00  ,    )	->		float:

       """simple docstring"""

       a_					:		Optional[Any]							=  x_start
       a_					:		List[str]							=  fnc(__A				)
       a_					:		str							=  0.0

       for _ in range(__A				):
              # Approximates curve as a sequence of linear lines and sums their length
              a_					:		List[str]							=  (x_end - x_start) / steps + xa
              a_					:		List[Any]							=  fnc(__A				)
              length += math.hypot(xa - xa  ,    fxa - fxa				)

              # Increment step
              a_					:		Optional[int]							=  xa
              a_					:		int							=  fxa

       return length


if __name__ == "__main__":







   def        SCREAMING_SNAKE_CASE_						(			__A :			Union[str, Any]				)	->		Any:

          """simple docstring"""

          return math.sin(10 * x				)

   print('f(x) = sin(10 * x)')
   print('The length of the curve from x = -10 to x = 10 is:')
   UpperCAmelCase_      : List[str]  					=       10
   while i <= 10_0000:
      print(F'With {i} steps: {line_length(f, -10, 10, i)}')
      i *= 10






from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments







def        SCREAMING_SNAKE_CASE_						(			)	->		Any:

       """simple docstring"""

       a_					:		Optional[Any]							=  HfArgumentParser(__A				)
       a_					:		Optional[int]							=  parser.parse_args_into_dataclasses()[0]
       a_					:		List[Any]							=  TensorFlowBenchmark(args=__A				)
       try:
              a_					:		List[str]							=  parser.parse_args_into_dataclasses()[0]
       except ValueError as e:
              a_					:		Dict							=  'Arg --no_{0} is no longer used, please use --no-{0} instead.'
              a_					:		Dict							=  ' '.join(str(__A				).split(' '				)[:-1]				)
              a_					:		int							=  ''
              a_					:		int							=  eval(str(__A				).split(' '				)[-1]				)
              a_					:		Any							=  []
              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(__A				)
              if len(__A				) > 0:
                     a_					:		str							=  full_error_msg + begin_error_msg + str(__A				)
              raise ValueError(__A				)
       benchmark.run()


if __name__ == "__main__":
   main()


