"""simple docstring"""







import unittest

from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
@require_sentencepiece
@slow  # see https://github.com/huggingface/transformers/issues/11457
class        UpperCamelCase		(			lowerCAmelCase_						,      unittest.TestCase  ):
   lowercase							=  BarthezTokenizer
   lowercase							=  BarthezTokenizerFast
   lowercase							=  True
   lowercase							=  True
   def 			_UpperCAmelCase   (			self			)	->      Any:


        '''simple docstring'''


        super().setUp()

        lowercase_	:				Tuple													=	BarthezTokenizerFast.from_pretrained('moussaKam/mbarthez'			)
        tokenizer.save_pretrained(self.tmpdirname			)
        tokenizer.save_pretrained(self.tmpdirname     ,legacy_format=snake_case_			)
        lowercase_	:				str													=	tokenizer
   def 			_UpperCAmelCase   (			self			)	->      Tuple:


        '''simple docstring'''


        lowercase_	:				Optional[Any]													=	'<pad>'
        lowercase_	:				Any													=	1

        self.assertEqual(self.get_tokenizer()._convert_token_to_id(snake_case_			)     ,snake_case_			)
        self.assertEqual(self.get_tokenizer()._convert_id_to_token(snake_case_			)     ,snake_case_			)
   def 			_UpperCAmelCase   (			self			)	->      Optional[int]:


        '''simple docstring'''


        lowercase_	:				Optional[int]													=	list(self.get_tokenizer().get_vocab().keys()			)

        self.assertEqual(vocab_keys[0]     ,'<s>'			)
        self.assertEqual(vocab_keys[1]     ,'<pad>'			)
        self.assertEqual(vocab_keys[-1]     ,'<mask>'			)
        self.assertEqual(len(snake_case_			)     ,10_1122			)
   def 			_UpperCAmelCase   (			self			)	->      int:


        '''simple docstring'''


        self.assertEqual(self.get_tokenizer().vocab_size     ,10_1122			)
   @require_torch
   def 			_UpperCAmelCase   (			self			)	->      int:


        '''simple docstring'''


        lowercase_	:				Optional[Any]													=	['A long paragraph for summarization.', 'Another paragraph for summarization.']
        lowercase_	:				List[str]													=	[0, 57, 3018, 7_0307, 91, 2]

        lowercase_	:				List[str]													=	self.tokenizer(
            snake_case_     ,max_length=len(snake_case_			)     ,padding=snake_case_     ,truncation=snake_case_     ,return_tensors='pt'			)
        self.assertIsInstance(snake_case_     ,snake_case_			)

        self.assertEqual((2, 6)     ,batch.input_ids.shape			)
        self.assertEqual((2, 6)     ,batch.attention_mask.shape			)
        lowercase_	:				Tuple													=	batch.input_ids.tolist()[0]
        self.assertListEqual(snake_case_     ,snake_case_			)
   def 			_UpperCAmelCase   (			self			)	->      Dict:


        '''simple docstring'''


        if not self.test_rust_tokenizer:
             return

        lowercase_	:				str													=	self.get_tokenizer()
        lowercase_	:				Any													=	self.get_rust_tokenizer()

        lowercase_	:				Optional[Any]													=	'I was born in 92000, and this is falsé.'

        lowercase_	:				Optional[int]													=	tokenizer.tokenize(snake_case_			)
        lowercase_	:				List[Any]													=	rust_tokenizer.tokenize(snake_case_			)
        self.assertListEqual(snake_case_     ,snake_case_			)

        lowercase_	:				Any													=	tokenizer.encode(snake_case_     ,add_special_tokens=snake_case_			)
        lowercase_	:				Tuple													=	rust_tokenizer.encode(snake_case_     ,add_special_tokens=snake_case_			)
        self.assertListEqual(snake_case_     ,snake_case_			)

        lowercase_	:				Any													=	self.get_rust_tokenizer()
        lowercase_	:				str													=	tokenizer.encode(snake_case_			)
        lowercase_	:				str													=	rust_tokenizer.encode(snake_case_			)
        self.assertListEqual(snake_case_     ,snake_case_			)







   @slow
   def 			_UpperCAmelCase   (			self			)	->      int:


        '''simple docstring'''


        lowercase_	:				Optional[int]													=	{'input_ids': [[0, 490, 1_4328, 4507, 354, 47, 4_3669, 95, 25, 7_8117, 2_0215, 1_9779, 190, 22, 400, 4, 3_5343, 8_0310, 603, 86, 2_4937, 105, 3_3438, 9_4762, 196, 3_9642, 7, 15, 1_5933, 173, 2, 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, 1_0534, 87, 25, 66, 3358, 196, 5_5289, 8, 8_2961, 81, 2204, 7_5203, 7, 15, 763, 1_2956, 216, 178, 1_4328, 9595, 1377, 6_9693, 7, 448, 7_1021, 196, 1_8106, 1437, 1_3974, 108, 9083, 4, 4_9315, 7, 39, 86, 1326, 2793, 4_6333, 4, 448, 196, 7_4588, 7, 4_9315, 7, 39, 21, 822, 3_8470, 74, 21, 6_6723, 6_2480, 8, 2_2050, 5, 2]], '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, 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, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
        # fmt: on

        # moussaKam/mbarthez is a french model. So we also use french texts.
        lowercase_	:				str													=	[
            '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=snake_case_     ,model_name='moussaKam/mbarthez'     ,revision='c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'     ,sequences=snake_case_     ,)








'''simple docstring'''




def 	UpperCAmelCase_							(					__lowercase							:      int       )		->       int:


     '''simple docstring'''



     if not isinstance(__lowercase			,     __lowercase       ) or number < 0:
          raise ValueError("Input must be a non-negative integer"       )

     _UpperCAmelCase     							=   0
     while number:
          # This way we arrive at next set bit (next 1) instead of looping
          # through each bit and checking for 1s hence the
          # loop won't run 32 times it will only run the number of `1` times
          number &= number - 1
          count += 1
     return count


if __name__ == "__main__":
  import doctest

  doctest.testmod()




