code: 
  
  
  
  
  
  
  # this script builds a small sample spm file tests/fixtures/test_sentencepiece_no_bos.model, with features needed by pegasus
  
  # 1. pip install sentencepiece
  #
  # 2. wget https://raw.githubusercontent.com/google/sentencepiece/master/data/botchan.txt
  
  # 3. build
  import sentencepiece as spm
  
  # pegasus:
  # 1. no bos
  # 2. eos_id is 1
  # 3. unk_id is 2
  # build a sample spm file accordingly
  spm.SentencePieceTrainer.train(
      """--input=botchan.txt --model_prefix=test_sentencepiece_no_bos --bos_id=-1 --unk_id=2  --eos_id=1  --vocab_size=1000"""
  )
  
  # 4. now update the fixture
  # mv test_sentencepiece_no_bos.model ../../tests/fixtures/
  
  
  
  
  
  
  
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()
  
  
  
  
  
  
  