



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 		_lowercase		(       UpperCAmelCase__,   unittest.TestCase	):
   _UpperCAmelCase     	=			BarthezTokenizer
   _UpperCAmelCase     	=			BarthezTokenizerFast
   _UpperCAmelCase     	=			True
   _UpperCAmelCase     	=			True

   def 		A							(      self			:       Optional[int]							)       ->				Tuple:


    """simple docstring"""






    super().setUp()

    a						=		BarthezTokenizerFast.from_pretrained("moussaKam/mbarthez"							)
    tokenizer.save_pretrained(self.tmpdirname							)
    tokenizer.save_pretrained(self.tmpdirname							,   legacy_format=__lowerCAmelCase							)
    a						=		tokenizer

   def 		A							(      self			:       str							)       ->				List[str]:


    """simple docstring"""






    a						=		"<pad>"
    a						=		1

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

   def 		A							(      self			:       Dict							)       ->				List[str]:


    """simple docstring"""






    a						=		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_1122							)

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


    """simple docstring"""






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

   @require_torch
   def 		A							(      self			:       str							)       ->				Optional[int]:


    """simple docstring"""






    a						=		["A long paragraph for summarization.", "Another paragraph for summarization."]
    a						=		[0, 57, 3018, 7_0307, 91, 2]

    a						=		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							)
    a						=		batch.input_ids.tolist()[0]
    self.assertListEqual(__lowerCAmelCase							,   __lowerCAmelCase							)

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


    """simple docstring"""






    if not self.test_rust_tokenizer:
     return

    a						=		self.get_tokenizer()
    a						=		self.get_rust_tokenizer()

    a						=		"I was born in 92000, and this is falsé."

    a						=		tokenizer.tokenize(__lowerCAmelCase							)
    a						=		rust_tokenizer.tokenize(__lowerCAmelCase							)
    self.assertListEqual(__lowerCAmelCase							,   __lowerCAmelCase							)

    a						=		tokenizer.encode(__lowerCAmelCase							,   add_special_tokens=__lowerCAmelCase							)
    a						=		rust_tokenizer.encode(__lowerCAmelCase							,   add_special_tokens=__lowerCAmelCase							)
    self.assertListEqual(__lowerCAmelCase							,   __lowerCAmelCase							)

    a						=		self.get_rust_tokenizer()
    a						=		tokenizer.encode(__lowerCAmelCase							)
    a						=		rust_tokenizer.encode(__lowerCAmelCase							)
    self.assertListEqual(__lowerCAmelCase							,   __lowerCAmelCase							)




   @slow
   def 		A							(      self			:       Optional[int]							)       ->				Optional[int]:


    """simple docstring"""






    a						=		{"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						=		[
        "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 	UpperCAmelCase__      (      UpperCAmelCase__ :Any					):






 '''simple docstring'''

 if not head:
  return True
 # split the list to two parts
 a		,  a						=		head.next, head
 while fast and fast.next:
  a						=		fast.next.next
  a						=		slow.next
 a						=		slow.next
 a						=		None  # Don't forget here! But forget still works!
 # reverse the second part
 a						=		None
 while second:
  a						=		second.next
  a						=		node
  a						=		second
  a						=		nxt
 # compare two parts
 # second part has the same or one less node
 while node:
  if node.val != head.val:
   return False
  a						=		node.next
  a						=		head.next
 return True


def 	UpperCAmelCase__      (      UpperCAmelCase__ :str					):






 '''simple docstring'''

 if not head or not head.next:
  return True

 # 1. Get the midpoint (slow)
 a						=		a						=		a						=		head
 while fast and fast.next:
  a		,  a						=		fast.next.next, slow.next

 # 2. Push the second half into the stack
 a						=		[slow.val]
 while slow.next:
  a						=		slow.next
  stack.append(slow.val					)

 # 3. Comparison
 while stack:
  if stack.pop() != cur.val:
   return False
  a						=		cur.next

 return True




def 	UpperCAmelCase__      (      UpperCAmelCase__ :Any					):






 '''simple docstring'''

 if not head or not head.next:
  return True
 a						=		{}
 a						=		0
 while head:
  if head.val in d:
   d[head.val].append(UpperCAmelCase__					)
  else:
   a						=		[pos]
  a						=		head.next
  pos += 1
 a						=		pos - 1
 a						=		0
 for v in d.values():
  if len(UpperCAmelCase__					) % 2 != 0:
   middle += 1
  else:
   a						=		0
   for i in range(0 ,					len(UpperCAmelCase__					)					):
    if v[i] + v[len(UpperCAmelCase__					) - 1 - step] != checksum:
     return False
    step += 1
  if middle > 1:
   return False
 return True

