

def 			__snake_case	(   ):



      """simple docstring"""

      for a in range(300						):
            for b in range(a + 1							,400						):
                  for c in range(b + 1							,500						):
                        if (a + b + c) == 1000 and (a**2) + (b**2) == (c**2):
                              return a * b * c

      return -1

def 			__snake_case	(   ):



      """simple docstring"""

      for a in range(300						):
            for b in range(400						):
                  A_	     =							1000 - a - b
                  if a < b < c and (a**2) + (b**2) == (c**2):
                        return a * b * c

      return -1

def 			__snake_case	(   ):



      """simple docstring"""

      import timeit

      print(
          timeit.timeit("solution()"							,setup="from __main__ import solution"							,number=1000						)						)
      print(
          timeit.timeit(
              "solution_fast()"							,setup="from __main__ import solution_fast"							,number=1000						)						)


if __name__ == "__main__":
      print(F"{solution() = }")


import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


__a						:Optional[int]            = logging.get_logger(__name__)

class      _a				( snake_case_							):




      """simple docstring"""

      def __init__(      self       :							List[Any]	, *UpperCAmelCase       :							Any	, **UpperCAmelCase       :							int  ):
            warnings.warn(
                "The class MobileNetV2FeatureExtractor is deprecated and will be removed in version 5 of Transformers."
                " Please use MobileNetV2ImageProcessor instead."	, UpperCAmelCase	, )
            super().__init__(*UpperCAmelCase	, **UpperCAmelCase  )