





'''simple docstring'''

from cva import destroyAllWindows, imread, imshow, waitKey







def  a__    (    lowercase :					str				)		->		Optional[int]:





     """simple docstring"""

     _UpperCamelCase   ,    _UpperCamelCase       =	img.shape[0], img.shape[1]

     # converting each pixel's color to its negative
     for i in range(lowercase				):
          for j in range(lowercase				):
               _UpperCamelCase       =	[255, 255, 255] - img[i][j]

     return img


if __name__ == "__main__":
   # read original image
   lowercase__						:      Optional[int]	=    imread('image_data/lena.jpg', 1)

   # convert to its negative
   lowercase__						:      Union[str, Any]	=    convert_to_negative(img)

   # show result image
   imshow('negative of original image', img)
   waitKey(0)
   destroyAllWindows()










'''simple docstring'''

import unittest

from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


lowercase__						:      Optional[Any]	=    get_tests_dir('fixtures/test_sentencepiece.model')
lowercase__						:      Any	=    get_tests_dir('fixtures/test_sentencepiece_bpe.model')

lowercase__						:      Tuple	=    'pt' if is_torch_available() else 'tf'
@require_sentencepiece
@require_tokenizers
class     __lowerCAmelCase					(   __magic_name__						,						unittest.TestCase			):






       """simple docstring"""
       _snake_case     :					Union[str, Any]						    =   CamembertTokenizer
       _snake_case     :					str						    =   CamembertTokenizerFast
       _snake_case     :					int						    =   True
       _snake_case     :					List[str]						    =   True





       def snake_case__						(							self       :		Dict					)   ->					Any:

            '''simple docstring'''




            super().setUp()

            # We have a SentencePiece fixture for testing
            _UpperCamelCase       =	CamembertTokenizer(lowerCAmelCase__					)
            tokenizer.save_pretrained(self.tmpdirname					)





       def snake_case__						(							self       :		Optional[int]					)   ->					List[Any]:

            '''simple docstring'''




            _UpperCamelCase       =	'''<pad>'''
            _UpperCamelCase       =	1

            self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase__					)	,			lowerCAmelCase__					)
            self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase__					)	,			lowerCAmelCase__					)





       def snake_case__						(							self       :		Dict					)   ->					List[Any]:

            '''simple docstring'''




            _UpperCamelCase       =	list(self.get_tokenizer().get_vocab().keys()					)

            self.assertEqual(vocab_keys[0]	,			'''<s>NOTUSED'''					)
            self.assertEqual(vocab_keys[1]	,			'''<pad>'''					)
            self.assertEqual(vocab_keys[-1]	,			'''<mask>'''					)
            self.assertEqual(len(lowerCAmelCase__					)	,			1004					)





       def snake_case__						(							self       :		Optional[Any]					)   ->					List[str]:

            '''simple docstring'''




            self.assertEqual(self.get_tokenizer().vocab_size	,			1005					)





       def snake_case__						(							self       :		int					)   ->					Tuple:

            '''simple docstring'''




            _UpperCamelCase       =	CamembertTokenizer(lowerCAmelCase__					)
            tokenizer.save_pretrained(self.tmpdirname					)
            _UpperCamelCase       =	CamembertTokenizerFast.from_pretrained(self.tmpdirname					)

            _UpperCamelCase       =	'''I was born in 92000, and this is falsé.'''

            _UpperCamelCase       =	tokenizer.encode(lowerCAmelCase__					)
            _UpperCamelCase       =	rust_tokenizer.encode(lowerCAmelCase__					)
            self.assertListEqual(lowerCAmelCase__	,			lowerCAmelCase__					)

            _UpperCamelCase       =	tokenizer.encode(lowerCAmelCase__	,			add_special_tokens=lowerCAmelCase__					)
            _UpperCamelCase       =	rust_tokenizer.encode(lowerCAmelCase__	,			add_special_tokens=lowerCAmelCase__					)
            self.assertListEqual(lowerCAmelCase__	,			lowerCAmelCase__					)

            # <unk> tokens are not the same for `rust` than for `slow`.
            # Because spm gives back raw token instead of `unk` in EncodeAsPieces
            # tokens = tokenizer.tokenize(sequence)
            _UpperCamelCase       =	tokenizer.convert_ids_to_tokens(lowerCAmelCase__					)
            _UpperCamelCase       =	rust_tokenizer.tokenize(lowerCAmelCase__					)
            self.assertListEqual(lowerCAmelCase__	,			lowerCAmelCase__					)





       def snake_case__						(							self       :		Optional[int]					)   ->					List[Any]:

            '''simple docstring'''




            if not self.test_rust_tokenizer:
                 return

            _UpperCamelCase       =	self.get_tokenizer()
            _UpperCamelCase       =	self.get_rust_tokenizer()

            _UpperCamelCase       =	'''I was born in 92000, and this is falsé.'''

            _UpperCamelCase       =	tokenizer.tokenize(lowerCAmelCase__					)
            _UpperCamelCase       =	rust_tokenizer.tokenize(lowerCAmelCase__					)
            self.assertListEqual(lowerCAmelCase__	,			lowerCAmelCase__					)

            _UpperCamelCase       =	tokenizer.encode(lowerCAmelCase__	,			add_special_tokens=lowerCAmelCase__					)
            _UpperCamelCase       =	rust_tokenizer.encode(lowerCAmelCase__	,			add_special_tokens=lowerCAmelCase__					)
            self.assertListEqual(lowerCAmelCase__	,			lowerCAmelCase__					)

            _UpperCamelCase       =	self.get_rust_tokenizer()
            _UpperCamelCase       =	tokenizer.encode(lowerCAmelCase__					)
            _UpperCamelCase       =	rust_tokenizer.encode(lowerCAmelCase__					)
            self.assertListEqual(lowerCAmelCase__	,			lowerCAmelCase__					)







       @slow
       def snake_case__						(							self       :		Any					)   ->					Optional[Any]:

            '''simple docstring'''




            _UpperCamelCase       =	{'''input_ids''': [[5, 54, 7196, 297, 30, 23, 776, 18, 11, 3215, 3705, 8252, 22, 3164, 1181, 2116, 29, 16, 813, 25, 791, 3314, 20, 3446, 38, 27575, 120, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [5, 468, 17, 11, 9088, 20, 1517, 8, 22804, 18818, 10, 38, 629, 607, 607, 142, 19, 7196, 867, 56, 10326, 24, 2267, 20, 416, 5072, 15612, 233, 734, 7, 2399, 27, 16, 3015, 1649, 7, 24, 20, 4338, 2399, 27, 13, 3400, 14, 13, 6189, 8, 930, 9, 6]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
            # fmt: on

            # camembert is a french model. So we also use french texts.
            _UpperCamelCase       =	[
                '''Le transformeur est un modèle d\'apprentissage profond introduit en 2017, '''
                '''utilisé principalement dans le domaine du traitement automatique des langues (TAL).''',
                '''À l\'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus '''
                '''pour gérer des données séquentielles, telles que le langage naturel, pour des tâches '''
                '''telles que la traduction et la synthèse de texte.''',
            ]

            self.tokenizer_integration_test_util(
                expected_encoding=lowerCAmelCase__	,			model_name='''camembert-base'''	,			revision='''3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf'''	,			sequences=lowerCAmelCase__	,			)



