





'''simple docstring'''







from cva import destroyAllWindows, imread, imshow, waitKey





def     lowerCamelCase_ (					SCREAMING_SNAKE_CASE__ :     Union[str, Any],     SCREAMING_SNAKE_CASE__ :     int				)	->		int:
						UpperCAmelCase_  ,    UpperCAmelCase_     : List[str]         =					img.shape[0], img.shape[1]

						def to_grayscale(SCREAMING_SNAKE_CASE__ :     str,     SCREAMING_SNAKE_CASE__ :     Dict,     SCREAMING_SNAKE_CASE__ :     Any				):
												return 0.21_26 * red + 0.5_87 * green + 0.1_14 * blue

						def normalize(SCREAMING_SNAKE_CASE__ :     str				):
												return min(SCREAMING_SNAKE_CASE__,     255				)

						for i in range(SCREAMING_SNAKE_CASE__				):
												for j in range(SCREAMING_SNAKE_CASE__				):
																		UpperCAmelCase_     : List[str]         =					int(to_grayscale(*img[i][j]				)				)
																		UpperCAmelCase_     : Tuple         =					[
																		    normalize(SCREAMING_SNAKE_CASE__				),
																		    normalize(greyscale + factor				),
																		    normalize(greyscale + 2 * factor				),
																		]

						return img


if __name__ == "__main__":
					# read original image
					snake_case_       :    Union[str, Any]          =					{
					    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()












'''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       ):
							__a   :				Any       =    SqueezeBertTokenizer
							__a   :				Dict       =    SqueezeBertTokenizerFast
							__a   :				Any       =    True

							def       UpperCAmelCase__		(							self							:       Union[str, Any]    ,       **__magic_name__							:       Dict				)   ->    int:







													"""simple docstring"""
													return SqueezeBertTokenizerFast.from_pretrained(self.tmpdirname    ,       **__magic_name__				)



							@slow
							def       UpperCAmelCase__		(							self							:       Union[str, Any]				)   ->    int:







													"""simple docstring"""
													UpperCAmelCase_     : List[str]         =					SqueezeBertTokenizer.from_pretrained('''squeezebert/squeezebert-mnli-headless'''				)

													UpperCAmelCase_     : Any         =					tokenizer.encode('''sequence builders'''    ,       add_special_tokens=__magic_name__				)
													UpperCAmelCase_     : Optional[Any]         =					tokenizer.encode('''multi-sequence build'''    ,       add_special_tokens=__magic_name__				)

													UpperCAmelCase_     : List[Any]         =					tokenizer.build_inputs_with_special_tokens(__magic_name__				)
													UpperCAmelCase_     : Any         =					tokenizer.build_inputs_with_special_tokens(__magic_name__    ,       __magic_name__				)

													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
													]





