





'''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


a__			:					Tuple       						=						get_tests_dir('fixtures/test_sentencepiece.model')
a__			:					int       						=						get_tests_dir('fixtures/test_sentencepiece_bpe.model')

a__			:					Union[str, Any]       						=						'pt' if is_torch_available() else 'tf'






@require_sentencepiece
@require_tokenizers
class     lowerCAmelCase__ (				UpperCAmelCase_      , unittest.TestCase    ):

       '''simple docstring'''
       _lowerCamelCase								=CamembertTokenizer
       _lowerCamelCase								=CamembertTokenizerFast
       _lowerCamelCase								=True
       _lowerCamelCase								=True

       def 			__snake_case      ( self					:				Optional[int]						):
              super().setUp()

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

       def 			__snake_case      ( self					:				Union[str, Any]						):
              UpperCAmelCase  =						'''<pad>'''
              UpperCAmelCase  =						1

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

       def 			__snake_case      ( self					:				int						):
              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(a__						)       ,     1004						)

       def 			__snake_case      ( self					:				List[str]						):
              self.assertEqual(self.get_tokenizer().vocab_size       ,     1005						)

       def 			__snake_case      ( self					:				Dict						):
              UpperCAmelCase  =						CamembertTokenizer(a__						)
              tokenizer.save_pretrained(self.tmpdirname						)
              UpperCAmelCase  =						CamembertTokenizerFast.from_pretrained(self.tmpdirname						)

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

              UpperCAmelCase  =						tokenizer.encode(a__						)
              UpperCAmelCase  =						rust_tokenizer.encode(a__						)
              self.assertListEqual(a__       ,     a__						)

              UpperCAmelCase  =						tokenizer.encode(a__       ,     add_special_tokens=a__						)
              UpperCAmelCase  =						rust_tokenizer.encode(a__       ,     add_special_tokens=a__						)
              self.assertListEqual(a__       ,     a__						)

              # <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(a__						)
              UpperCAmelCase  =						rust_tokenizer.tokenize(a__						)
              self.assertListEqual(a__       ,     a__						)

       def 			__snake_case      ( self					:				List[Any]						):
              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(a__						)
              UpperCAmelCase  =						rust_tokenizer.tokenize(a__						)
              self.assertListEqual(a__       ,     a__						)

              UpperCAmelCase  =						tokenizer.encode(a__       ,     add_special_tokens=a__						)
              UpperCAmelCase  =						rust_tokenizer.encode(a__       ,     add_special_tokens=a__						)
              self.assertListEqual(a__       ,     a__						)

              UpperCAmelCase  =						self.get_rust_tokenizer()
              UpperCAmelCase  =						tokenizer.encode(a__						)
              UpperCAmelCase  =						rust_tokenizer.encode(a__						)
              self.assertListEqual(a__       ,     a__						)



       @slow
       def 			__snake_case      ( self					:				Optional[Any]						):
              # fmt: off
              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=a__       ,     model_name='''camembert-base'''       ,     revision='''3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf'''       ,     sequences=a__       ,     )







"""simple docstring"""







def     UpperCAmelCase_					(				):




			'''simple docstring'''



			_lowerCamelCase					:					str	       =    0
			for i in range(1      ,							10_01						):
						total += i**i
			return str(__a						)[-10:]


if __name__ == "__main__":
	print(solution())





