





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  A__    (							__UpperCAmelCase ,  unittest.TestCase	):




   """simple docstring"""



   __A   :				List[str]         =  BarthezTokenizer
   __A   :				str         =  BarthezTokenizerFast
   __A   :				Dict         =  True
   __A   :				Union[str, Any]         =  True

   def 							__lowercase		(					self)			->						Union[str, Any]:







          '''simple docstring'''

          super().setUp()

          a__						:	Tuple =				BarthezTokenizerFast.from_pretrained('moussaKam/mbarthez')
          tokenizer.save_pretrained(self.tmpdirname)
          tokenizer.save_pretrained(self.tmpdirname					,  legacy_format=lowercase)
          a__						:	str =				tokenizer

   def 							__lowercase		(					self)			->						int:







          '''simple docstring'''

          a__						:	List[Any] =				'<pad>'
          a__						:	Optional[Any] =				1

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

   def 							__lowercase		(					self)			->						Optional[int]:







          '''simple docstring'''

          a__						:	Tuple =				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)					,  10_1122)

   def 							__lowercase		(					self)			->						Tuple:







          '''simple docstring'''

          self.assertEqual(self.get_tokenizer().vocab_size					,  10_1122)

   @require_torch
   def 							__lowercase		(					self)			->						List[str]:







          '''simple docstring'''

          a__						:	Optional[int] =				['A long paragraph for summarization.', 'Another paragraph for summarization.']
          a__						:	int =				[0, 57, 3018, 7_0307, 91, 2]

          a__						:	List[str] =				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)
          a__						:	Dict =				batch.input_ids.tolist()[0]
          self.assertListEqual(lowercase					,  lowercase)

   def 							__lowercase		(					self)			->						Tuple:







          '''simple docstring'''

          if not self.test_rust_tokenizer:
                 return

          a__						:	Optional[int] =				self.get_tokenizer()
          a__						:	Union[str, Any] =				self.get_rust_tokenizer()

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

          a__						:	List[Any] =				tokenizer.tokenize(lowercase)
          a__						:	Dict =				rust_tokenizer.tokenize(lowercase)
          self.assertListEqual(lowercase					,  lowercase)

          a__						:	int =				tokenizer.encode(lowercase					,  add_special_tokens=lowercase)
          a__						:	List[str] =				rust_tokenizer.encode(lowercase					,  add_special_tokens=lowercase)
          self.assertListEqual(lowercase					,  lowercase)

          a__						:	Optional[Any] =				self.get_rust_tokenizer()
          a__						:	Optional[Any] =				tokenizer.encode(lowercase)
          a__						:	Union[str, Any] =				rust_tokenizer.encode(lowercase)
          self.assertListEqual(lowercase					,  lowercase)

   @slow
   def 							__lowercase		(					self)			->						Union[str, Any]:







          '''simple docstring'''

          a__						:	Union[str, Any] =				{'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.
          a__						:	Optional[Any] =				[
              '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					,  )







from __future__ import annotations

from typing import Any



class 				lowerCAmelCase_		:
       def __init__(			self,			SCREAMING_SNAKE_CASE_       )     ->		None:
          UpperCamelCase    :  Any							=	num_of_nodes
          UpperCamelCase    :  list[list[int]]							=	[]
          UpperCamelCase    :  dict[int, int]							=	{}
       def 					snake_case_       (			self,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_       )     ->		None:
          self.m_edges.append([u_node, v_node, weight]       )
       def 					snake_case_       (			self,			SCREAMING_SNAKE_CASE_       )     ->		int:

          if self.m_component[u_node] == u_node:
             return u_node
          return self.find_component(self.m_component[u_node]       )
       def 					snake_case_       (			self,			SCREAMING_SNAKE_CASE_       )     ->		None:

          if self.m_component[u_node] != u_node:
             for k in self.m_component:
                UpperCamelCase    :  Dict							=	self.find_component(SCREAMING_SNAKE_CASE_       )
       def 					snake_case_       (			self,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_       )     ->		None:

          if component_size[u_node] <= component_size[v_node]:
             UpperCamelCase    :  Tuple							=	v_node
             component_size[v_node] += component_size[u_node]
             self.set_component(SCREAMING_SNAKE_CASE_       )

          elif component_size[u_node] >= component_size[v_node]:
             UpperCamelCase    :  Union[str, Any]							=	self.find_component(SCREAMING_SNAKE_CASE_       )
             component_size[u_node] += component_size[v_node]
             self.set_component(SCREAMING_SNAKE_CASE_       )






       def 					snake_case_       (			self       )     ->		None:
          UpperCamelCase    :  int							=	[]
          UpperCamelCase    :  int							=	0

          UpperCamelCase    :  list[Any]							=	[-1] * self.m_num_of_nodes

          # A list of components (initialized to all of the nodes)
          for node in range(self.m_num_of_nodes       ):
             self.m_component.update({node: node}       )
             component_size.append(1       )

          UpperCamelCase    :  List[str]							=	self.m_num_of_nodes

          while num_of_components > 1:
             for edge in self.m_edges:
                UpperCamelCase	,     UpperCamelCase	,     UpperCamelCase    :  List[Any]							=	edge

                UpperCamelCase    :  str							=	self.m_component[u]
                UpperCamelCase    :  Any							=	self.m_component[v]

                if u_component != v_component:

                   for component in (u_component, v_component):
                      if (
                          minimum_weight_edge[component] == -1
                          or minimum_weight_edge[component][2] > w
                      ):
                         UpperCamelCase    :  Any							=	[u, v, w]

             for edge in minimum_weight_edge:
                if isinstance(SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_       ):
                   UpperCamelCase	,     UpperCamelCase	,     UpperCamelCase    :  int							=	edge

                   UpperCamelCase    :  List[Any]							=	self.m_component[u]
                   UpperCamelCase    :  Tuple							=	self.m_component[v]

                   if u_component != v_component:
                      mst_weight += w
                      self.union(SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_,			SCREAMING_SNAKE_CASE_       )
                      print(F"""Added edge [{u} - {v}]\nAdded weight: {w}\n"""       )
                      num_of_components -= 1

             UpperCamelCase    :  Optional[Any]							=	[-1] * self.m_num_of_nodes
          print(F"""The total weight of the minimal spanning tree is: {mst_weight}"""       )






def 		UpperCamelCase	(   )	->     None:
   pass


if __name__ == "__main__":
    import doctest

    doctest.testmod()



