

from transformers.models.cpm.tokenization_cpm import CpmTokenizer
from transformers.testing_utils import custom_tokenizers

from ..xlnet.test_modeling_xlnet import XLNetModelTest







@custom_tokenizers
class lowerCamelCase      (						__lowerCAmelCase							):

				def 				_lowerCamelCase						(					self,	lowercase_,	lowercase_,	lowercase_,	lowercase_,	lowercase_   )						->       str:
					return True






				def 				_lowerCamelCase						(					self   )						->       str:
					snake_case							 =				CpmTokenizer.from_pretrained('TsinghuaAI/CPM-Generate'   )
					snake_case							 =				'Hugging Face大法好，谁用谁知道。'
					snake_case							 =				'Hugging Face大法好,谁用谁知道。<unk>'
					snake_case							 =				'▁Hu gg ing ▁ ▂ ▁F ace ▁大法 ▁好 ▁ , ▁谁 ▁用 ▁谁 ▁知 道 ▁ 。'.split()

					snake_case							 =				tokenizer.tokenize(lowercase_   )
					self.assertListEqual(lowercase_,	lowercase_   )

					snake_case							 =				tokens + [tokenizer.unk_token]

					snake_case							 =				[13789, 13283, 1421, 8, 10, 1164, 13608, 16528, 63, 8, 9, 440, 108, 440, 121, 90, 8, 12, 0]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_   ),	lowercase_   )

					snake_case							 =				tokenizer.decode(lowercase_   )
					self.assertEqual(lowercase_,	lowercase_   )








'''simple docstring'''

from cva import destroyAllWindows, imread, imshow, waitKey

def     __magic_name__       ( A					,   A							)			->		Union[str, Any]:
	snake_case , snake_case							 =				img.shape[0], img.shape[1]

	def to_grayscale(A					,   A					,   A							):
		return 0.2_126 * red + 0.587 * green + 0.114 * blue

	def normalize(A							):
		return min(A					,   2_5_5							)

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

	return img


if __name__ == "__main__":
						# read original image
						lowerCAmelCase_						   =			{
						    percentage: imread("image_data/lena.jpg", 1) for percentage in (1_0, 2_0, 3_0, 4_0)
						}

						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()





