

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  __lowerCAmelCase     (					__snake_case			,			unittest.TestCase							):
  _a									=  BarthezTokenizer
  _a									=  BarthezTokenizerFast
  _a									=  True
  _a									=  True




  def   A__     (				self					)  -> Tuple:
        '''simple docstring'''






        super().setUp()

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




  def   A__     (				self					)  -> Any:
        '''simple docstring'''






        _lowercase	       ='<pad>'
        _lowercase	       =1

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




  def   A__     (				self					)  -> Optional[Any]:
        '''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(__SCREAMING_SNAKE_CASE					)							,   101_122					)




  def   A__     (				self					)  -> List[str]:
        '''simple docstring'''






        self.assertEqual(self.get_tokenizer().vocab_size							,   101_122					)




  @require_torch
  def   A__     (				self					)  -> int:
        '''simple docstring'''






        _lowercase	       =['A long paragraph for summarization.', 'Another paragraph for summarization.']
        _lowercase	       =[0, 57, 3_018, 70_307, 91, 2]

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

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




  def   A__     (				self					)  -> List[Any]:
        '''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(__SCREAMING_SNAKE_CASE					)
        _lowercase	       =rust_tokenizer.tokenize(__SCREAMING_SNAKE_CASE					)
        self.assertListEqual(__SCREAMING_SNAKE_CASE							,   __SCREAMING_SNAKE_CASE					)

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

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




  @slow
  def   A__     (				self					)  -> Union[str, Any]:
        '''simple docstring'''






        _lowercase	       ={'input_ids': [[0, 490, 14_328, 4_507, 354, 47, 43_669, 95, 25, 78_117, 20_215, 19_779, 190, 22, 400, 4, 35_343, 80_310, 603, 86, 24_937, 105, 33_438, 94_762, 196, 39_642, 7, 15, 15_933, 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, 10_534, 87, 25, 66, 3_358, 196, 55_289, 8, 82_961, 81, 2_204, 75_203, 7, 15, 763, 12_956, 216, 178, 14_328, 9_595, 1_377, 69_693, 7, 448, 71_021, 196, 18_106, 1_437, 13_974, 108, 9_083, 4, 49_315, 7, 39, 86, 1_326, 2_793, 46_333, 4, 448, 196, 74_588, 7, 49_315, 7, 39, 21, 822, 38_470, 74, 21, 66_723, 62_480, 8, 22_050, 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=__SCREAMING_SNAKE_CASE							,   model_name='moussaKam/mbarthez'							,   revision='c2e4ecbca5e3cd2c37fe1ac285ca4fbdf1366fb6'							,   sequences=__SCREAMING_SNAKE_CASE							,   )










"""simple docstring"""





from typing import Any






class      a						:






    def __init__(       self     :							Tuple       ,						__SCREAMING_SNAKE_CASE     :							Any					)     ->		List[Any]:
      lowerCamelCase_         =						data
      lowerCamelCase_         =						None






class      a						:






    def __init__(       self     :							Union[str, Any]					)     ->		List[Any]:
      lowerCamelCase_         =						None






    def    UpperCamelCase       (       self     :							Dict					)     ->		Optional[int]:
      lowerCamelCase_         =						self.head
      while temp is not None:
        print(temp.data       ,						end=' '					)
        lowerCamelCase_         =						temp.next
      print()






    def    UpperCamelCase       (       self     :							List[Any]       ,						__SCREAMING_SNAKE_CASE     :							Any					)     ->		Union[str, Any]:
      lowerCamelCase_         =						Node(__SCREAMING_SNAKE_CASE					)
      lowerCamelCase_         =						self.head
      lowerCamelCase_         =						new_node






    def    UpperCamelCase       (       self     :							Dict       ,						__SCREAMING_SNAKE_CASE     :							List[str]       ,						__SCREAMING_SNAKE_CASE     :							int					)     ->		Union[str, Any]:
      if node_data_a == node_data_a:
        return
      else:
        lowerCamelCase_         =						self.head
        while node_a is not None and node_a.data != node_data_a:
          lowerCamelCase_         =						node_a.next

        lowerCamelCase_         =						self.head
        while node_a is not None and node_a.data != node_data_a:
          lowerCamelCase_         =						node_a.next

        if node_a is None or node_a is None:
          return

        lowerCamelCase_     ,	lowerCamelCase_         =						node_a.data, node_a.data


if __name__ == "__main__":
  _SCREAMING_SNAKE_CASE					:				Optional[int]					    =						LinkedList()
  for i in range(5, 0, -1):
    ll.push(i)

  ll.print_list()

  ll.swap_nodes(1, 4)
  print('''After swapping''')
  ll.print_list()




