
'''simple docstring'''



from transformers import SqueezeBertTokenizer, SqueezeBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest

@require_tokenizers
class 				_a			(_lowerCamelCase):





       """simple docstring"""




       SCREAMING_SNAKE_CASE =					SqueezeBertTokenizer
       SCREAMING_SNAKE_CASE =					SqueezeBertTokenizerFast
       SCREAMING_SNAKE_CASE =					True






       def     UpperCamelCase			(							self    ,							**A__ )      ->     Union[str, Any]:
          return SqueezeBertTokenizerFast.from_pretrained(self.tmpdirname    ,							**A__ )






       @slow
       def     UpperCamelCase			(							self )      ->     Optional[Any]:
          _SCREAMING_SNAKE_CASE       	=			SqueezeBertTokenizer.from_pretrained("""squeezebert/squeezebert-mnli-headless""" )

          _SCREAMING_SNAKE_CASE       	=			tokenizer.encode("""sequence builders"""    ,							add_special_tokens=A__ )
          _SCREAMING_SNAKE_CASE       	=			tokenizer.encode("""multi-sequence build"""    ,							add_special_tokens=A__ )

          _SCREAMING_SNAKE_CASE       	=			tokenizer.build_inputs_with_special_tokens(A__ )
          _SCREAMING_SNAKE_CASE       	=			tokenizer.build_inputs_with_special_tokens(A__    ,							A__ )

          assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
          assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
              tokenizer.sep_token_id
          ]








'''simple docstring'''



from cva import destroyAllWindows, imread, imshow, waitKey
def 				lowerCAmelCase_		(			SCREAMING_SNAKE_CASE_      , SCREAMING_SNAKE_CASE_  )       ->       Dict:




   """simple docstring"""
   _SCREAMING_SNAKE_CASE	,							_SCREAMING_SNAKE_CASE       	=			img.shape[0], img.shape[1]

   def to_grayscale(SCREAMING_SNAKE_CASE_      , SCREAMING_SNAKE_CASE_      , SCREAMING_SNAKE_CASE_  ):
      return 0.2126 * red + 0.587 * green + 0.114 * blue

   def normalize(SCREAMING_SNAKE_CASE_  ):
      return min(SCREAMING_SNAKE_CASE_      , 2_55  )

   for i in range(SCREAMING_SNAKE_CASE_  ):
      for j in range(SCREAMING_SNAKE_CASE_  ):
         _SCREAMING_SNAKE_CASE       	=			int(to_grayscale(*img[i][j]  )  )
         _SCREAMING_SNAKE_CASE       	=			[
             normalize(SCREAMING_SNAKE_CASE_  ),
             normalize(greyscale + factor  ),
             normalize(greyscale + 2 * factor  ),
         ]

   return img


if __name__ == "__main__":
     # read original image
     UpperCamelCase__ :						Optional[int]    							=					{
         percentage: imread("image_data/lena.jpg", 1) for percentage in (10, 20, 30, 40)
     }

     for percentage, img in images.items():
          make_sepia(img, percentage)

     for percentage, img in images.items():
          imshow(f"""Original image with sepia (factor: {percentage})""", img)

     waitKey(0)
     destroyAllWindows()






