



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						):

   '''simple docstring'''




   A     :	int												=     BarthezTokenizer
   A     :	int												=     BarthezTokenizerFast
   A     :	Dict												=     True
   A     :	List[Any]												=     True


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




         """simple docstring"""

         super().setUp()

         lowercase__  =	BarthezTokenizerFast.from_pretrained('moussaKam/mbarthez')
         tokenizer.save_pretrained(self.tmpdirname)
         tokenizer.save_pretrained(self.tmpdirname      ,					legacy_format=lowerCAmelCase)
         lowercase__  =	tokenizer


   def       UpperCAmelCase		(    self	:      Optional[Any])						->					Tuple:




         """simple docstring"""

         lowercase__  =	'<pad>'
         lowercase__  =	1

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


   def       UpperCAmelCase		(    self	:      int)						->					str:




         """simple docstring"""

         lowercase__  =	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(lowerCAmelCase)      ,					10_11_22)


   def       UpperCAmelCase		(    self	:      int)						->					str:




         """simple docstring"""

         self.assertEqual(self.get_tokenizer().vocab_size      ,					10_11_22)


   @require_torch
   def       UpperCAmelCase		(    self	:      Dict)						->					Tuple:




         """simple docstring"""

         lowercase__  =	['A long paragraph for summarization.', 'Another paragraph for summarization.']
         lowercase__  =	[0, 57, 30_18, 7_03_07, 91, 2]

         lowercase__  =	self.tokenizer(
             lowerCAmelCase      ,					max_length=len(lowerCAmelCase)      ,					padding=lowerCAmelCase      ,					truncation=lowerCAmelCase      ,					return_tensors='pt')
         self.assertIsInstance(lowerCAmelCase      ,					lowerCAmelCase)

         self.assertEqual((2, 6)      ,					batch.input_ids.shape)
         self.assertEqual((2, 6)      ,					batch.attention_mask.shape)
         lowercase__  =	batch.input_ids.tolist()[0]
         self.assertListEqual(lowerCAmelCase      ,					lowerCAmelCase)


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




         """simple docstring"""

         if not self.test_rust_tokenizer:
               return

         lowercase__  =	self.get_tokenizer()
         lowercase__  =	self.get_rust_tokenizer()

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

         lowercase__  =	tokenizer.tokenize(lowerCAmelCase)
         lowercase__  =	rust_tokenizer.tokenize(lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase      ,					lowerCAmelCase)

         lowercase__  =	tokenizer.encode(lowerCAmelCase      ,					add_special_tokens=lowerCAmelCase)
         lowercase__  =	rust_tokenizer.encode(lowerCAmelCase      ,					add_special_tokens=lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase      ,					lowerCAmelCase)

         lowercase__  =	self.get_rust_tokenizer()
         lowercase__  =	tokenizer.encode(lowerCAmelCase)
         lowercase__  =	rust_tokenizer.encode(lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase      ,					lowerCAmelCase)



   @slow
   def       UpperCAmelCase		(    self	:      Any)						->					List[str]:




         """simple docstring"""

         lowercase__  =	{'input_ids': [[0, 4_90, 1_43_28, 45_07, 3_54, 47, 4_36_69, 95, 25, 7_81_17, 2_02_15, 1_97_79, 1_90, 22, 4_00, 4, 3_53_43, 8_03_10, 6_03, 86, 2_49_37, 1_05, 3_34_38, 9_47_62, 1_96, 3_96_42, 7, 15, 1_59_33, 1_73, 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_05_34, 87, 25, 66, 33_58, 1_96, 5_52_89, 8, 8_29_61, 81, 22_04, 7_52_03, 7, 15, 7_63, 1_29_56, 2_16, 1_78, 1_43_28, 95_95, 13_77, 6_96_93, 7, 4_48, 7_10_21, 1_96, 1_81_06, 14_37, 1_39_74, 1_08, 90_83, 4, 4_93_15, 7, 39, 86, 13_26, 27_93, 4_63_33, 4, 4_48, 1_96, 7_45_88, 7, 4_93_15, 7, 39, 21, 8_22, 3_84_70, 74, 21, 6_67_23, 6_24_80, 8, 2_20_50, 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__  =	[
             '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='moussaKam/mbarthez'      ,					revision='c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'      ,					sequences=lowerCAmelCase      ,					)





def 	_lowerCAmelCase (    A__ = 600_851_475_143						):

      try:
            lowercase__  =	int(A__						)
      except (TypeError, ValueError):
            raise TypeError('Parameter n must be int or castable to int.'						)
      if n <= 0:
            raise ValueError('Parameter n must be greater than or equal to one.'						)
      lowercase__  =	2
      lowercase__  =	0
      if n == 2:
            return 2
      while n > 2:
            while n % i != 0:
                  i += 1
            lowercase__  =	i
            while n % i == 0:
                  lowercase__  =	n // i
            i += 1
      return int(A__						)


if __name__ == "__main__":
       print(F'''{solution() = }''')
