





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        __SCREAMING_SNAKE_CASE      (			_lowerCAmelCase					,unittest.TestCase ):
       _UpperCAmelCase				:  Tuple			   =   BarthezTokenizer
       _UpperCAmelCase				:  Tuple			   =   BarthezTokenizerFast
       _UpperCAmelCase				:  Union[str, Any]			   =   True
       _UpperCAmelCase				:  Dict			   =   True







       def 						__lowerCamelCase   (				self					:     Dict      )       ->Optional[int]:
          super().setUp()

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







       def 						__lowerCamelCase   (				self					:     List[Any]      )       ->Any:
          lowerCamelCase__        =							'''<pad>'''
          lowerCamelCase__        =							1

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







       def 						__lowerCamelCase   (				self					:     Optional[Any]      )       ->Optional[int]:
          lowerCamelCase__        =							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(_lowercase      )		, 1_0_1_1_2_2      )







       def 						__lowerCamelCase   (				self					:     Dict      )       ->Optional[int]:
          self.assertEqual(self.get_tokenizer().vocab_size		, 1_0_1_1_2_2      )







       @require_torch
       def 						__lowerCamelCase   (				self					:     Tuple      )       ->Dict:
          lowerCamelCase__        =							['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
          lowerCamelCase__        =							[0, 5_7, 3_0_1_8, 7_0_3_0_7, 9_1, 2]

          lowerCamelCase__        =							self.tokenizer(
              _lowercase		, max_length=len(_lowercase      )		, padding=_lowercase		, truncation=_lowercase		, return_tensors='''pt'''      )
          self.assertIsInstance(_lowercase		, _lowercase      )

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







       def 						__lowerCamelCase   (				self					:     str      )       ->List[str]:
          if not self.test_rust_tokenizer:
             return

          lowerCamelCase__        =							self.get_tokenizer()
          lowerCamelCase__        =							self.get_rust_tokenizer()

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

          lowerCamelCase__        =							tokenizer.tokenize(_lowercase      )
          lowerCamelCase__        =							rust_tokenizer.tokenize(_lowercase      )
          self.assertListEqual(_lowercase		, _lowercase      )

          lowerCamelCase__        =							tokenizer.encode(_lowercase		, add_special_tokens=_lowercase      )
          lowerCamelCase__        =							rust_tokenizer.encode(_lowercase		, add_special_tokens=_lowercase      )
          self.assertListEqual(_lowercase		, _lowercase      )

          lowerCamelCase__        =							self.get_rust_tokenizer()
          lowerCamelCase__        =							tokenizer.encode(_lowercase      )
          lowerCamelCase__        =							rust_tokenizer.encode(_lowercase      )
          self.assertListEqual(_lowercase		, _lowercase      )







       @slow
       def 						__lowerCamelCase   (				self					:     str      )       ->Dict:
          # fmt: off
          lowerCamelCase__        =							{'''input_ids''': [[0, 4_9_0, 1_4_3_2_8, 4_5_0_7, 3_5_4, 4_7, 4_3_6_6_9, 9_5, 2_5, 7_8_1_1_7, 2_0_2_1_5, 1_9_7_7_9, 1_9_0, 2_2, 4_0_0, 4, 3_5_3_4_3, 8_0_3_1_0, 6_0_3, 8_6, 2_4_9_3_7, 1_0_5, 3_3_4_3_8, 9_4_7_6_2, 1_9_6, 3_9_6_4_2, 7, 1_5, 1_5_9_3_3, 1_7_3, 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_0_5_3_4, 8_7, 2_5, 6_6, 3_3_5_8, 1_9_6, 5_5_2_8_9, 8, 8_2_9_6_1, 8_1, 2_2_0_4, 7_5_2_0_3, 7, 1_5, 7_6_3, 1_2_9_5_6, 2_1_6, 1_7_8, 1_4_3_2_8, 9_5_9_5, 1_3_7_7, 6_9_6_9_3, 7, 4_4_8, 7_1_0_2_1, 1_9_6, 1_8_1_0_6, 1_4_3_7, 1_3_9_7_4, 1_0_8, 9_0_8_3, 4, 4_9_3_1_5, 7, 3_9, 8_6, 1_3_2_6, 2_7_9_3, 4_6_3_3_3, 4, 4_4_8, 1_9_6, 7_4_5_8_8, 7, 4_9_3_1_5, 7, 3_9, 2_1, 8_2_2, 3_8_4_7_0, 7_4, 2_1, 6_6_7_2_3, 6_2_4_8_0, 8, 2_2_0_5_0, 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.
          lowerCamelCase__        =							[
              '''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=_lowercase		, model_name='''moussaKam/mbarthez'''		, revision='''c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'''		, sequences=_lowercase		, )










def 	_a						(   UpperCAmelCase      ,  UpperCAmelCase					)    ->    Dict:







   """simple docstring"""
   if b == 0:
      return 1
   if (b % 2) == 0:
      return actual_power(UpperCAmelCase      ,  int(b / 2					)					) * actual_power(UpperCAmelCase      ,  int(b / 2					)					)
   else:
      return a * actual_power(UpperCAmelCase      ,  int(b / 2					)					) * actual_power(UpperCAmelCase      ,  int(b / 2					)					)



def 	_a						(   UpperCAmelCase      ,  UpperCAmelCase					)    ->    float:







   """simple docstring"""
   if b < 0:
      return 1 / actual_power(UpperCAmelCase      ,  UpperCAmelCase					)
   return actual_power(UpperCAmelCase      ,  UpperCAmelCase					)


if __name__ == "__main__":
       print(power(-2, -3))



