code: 
  
  
  
  
  
  
  def    _lowerCamelCase	(	)   -> str:
  
       '''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    _lowerCamelCase	(	)   -> Any:
  
       '''simple docstring'''
  
       for a in range(300					):
            for b in range(400					):
                 UpperCAmelCase__			:     Optional[int]										= 1000 - a - b
                 if a < b < c and (a**2) + (b**2) == (c**2):
                      return a * b * c
  
       return -1
  
  
  
  
  
  def    _lowerCamelCase	(	)   -> str:
  
       '''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() = }''')
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  
  
  import math
  import os
  
  import cva
  import numpy as np
  
  SCREAMING_SNAKE_CASE__		:       Optional[Any]   							=							255.0
  
  
  
  
  
  def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase					)   -> float:
  
       '''simple docstring'''
       UpperCAmelCase__			:     List[Any]										= np.mean((original - contrast) ** 2					)
       if mse == 0:
            return 100
  
       return 20 * math.logaa(PIXEL_MAX / math.sqrt(__lowerCamelCase					)					)
  
  
  
  
  
  def    _lowerCamelCase	(	)   -> None:
  
       '''simple docstring'''
       UpperCAmelCase__			:     Union[str, Any]										= os.path.dirname(os.path.realpath(__lowerCamelCase					)					)
       # Loading images (original image and compressed image)
       UpperCAmelCase__			:     List[Any]										= cva.imread(os.path.join(__lowerCamelCase   ,       """image_data/original_image.png"""					)					)
       UpperCAmelCase__			:     Dict										= cva.imread(os.path.join(__lowerCamelCase   ,       """image_data/compressed_image.png"""					)   ,       1					)
  
       UpperCAmelCase__			:     Tuple										= cva.imread(os.path.join(__lowerCamelCase   ,       """image_data/PSNR-example-base.png"""					)					)
       UpperCAmelCase__			:     int										= cva.imread(
           os.path.join(__lowerCamelCase   ,       """image_data/PSNR-example-comp-10.jpg"""					)   ,       1					)
  
       # Value expected: 29.73dB
       print("""-- First Test --"""					)
       print(F"PSNR value is {peak_signal_to_noise_ratio(__lowerCamelCase   ,       __lowerCamelCase					)} dB"					)
  
       # # Value expected: 31.53dB (Wikipedia Example)
       print("""\n-- Second Test --"""					)
       print(F"PSNR value is {peak_signal_to_noise_ratio(__lowerCamelCase   ,       __lowerCamelCase					)} dB"					)
  
  
  if __name__ == "__main__":
        main()
  
  
  
  
  
  
  