



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 	_snake_case							(			lowerCamelCase_      ,				unittest.TestCase      ):






   '''simple docstring'''






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


   def 	A__  (  self:			List[Any]				)     ->	Dict:
       super().setUp()

       UpperCAmelCase_			:    Optional[int]   						= BarthezTokenizerFast.from_pretrained("""moussaKam/mbarthez"""				)
       tokenizer.save_pretrained(self.tmpdirname				)
       tokenizer.save_pretrained(self.tmpdirname   ,legacy_format=lowerCAmelCase__				)
       UpperCAmelCase_			:    Optional[Any]   						= tokenizer


   def 	A__  (  self:			str				)     ->	Any:
       UpperCAmelCase_			:    int   						= """<pad>"""
       UpperCAmelCase_			:    Optional[Any]   						= 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:			int				)     ->	Dict:
       UpperCAmelCase_			:    Optional[int]   						= 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__				)   ,101122				)


   def 	A__  (  self:			Dict				)     ->	List[str]:
       self.assertEqual(self.get_tokenizer().vocab_size   ,101122				)


   @require_torch
   def 	A__  (  self:			Optional[int]				)     ->	str:
       UpperCAmelCase_			:    Union[str, Any]   						= ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
       UpperCAmelCase_			:    List[str]   						= [0, 57, 3018, 70307, 91, 2]

       UpperCAmelCase_			:    Union[str, Any]   						= 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				)
       UpperCAmelCase_			:    Optional[Any]   						= batch.input_ids.tolist()[0]
       self.assertListEqual(lowerCAmelCase__   ,lowerCAmelCase__				)


   def 	A__  (  self:			Tuple				)     ->	Union[str, Any]:
       if not self.test_rust_tokenizer:
           return

       UpperCAmelCase_			:    int   						= self.get_tokenizer()
       UpperCAmelCase_			:    Dict   						= self.get_rust_tokenizer()

       UpperCAmelCase_			:    int   						= """I was born in 92000, and this is falsé."""

       UpperCAmelCase_			:    int   						= tokenizer.tokenize(lowerCAmelCase__				)
       UpperCAmelCase_			:    Optional[int]   						= rust_tokenizer.tokenize(lowerCAmelCase__				)
       self.assertListEqual(lowerCAmelCase__   ,lowerCAmelCase__				)

       UpperCAmelCase_			:    Union[str, Any]   						= tokenizer.encode(lowerCAmelCase__   ,add_special_tokens=lowerCAmelCase__				)
       UpperCAmelCase_			:    int   						= rust_tokenizer.encode(lowerCAmelCase__   ,add_special_tokens=lowerCAmelCase__				)
       self.assertListEqual(lowerCAmelCase__   ,lowerCAmelCase__				)

       UpperCAmelCase_			:    List[Any]   						= self.get_rust_tokenizer()
       UpperCAmelCase_			:    Tuple   						= tokenizer.encode(lowerCAmelCase__				)
       UpperCAmelCase_			:    int   						= rust_tokenizer.encode(lowerCAmelCase__				)
       self.assertListEqual(lowerCAmelCase__   ,lowerCAmelCase__				)






   @slow
   def 	A__  (  self:			Optional[int]				)     ->	str:
       # fmt: off
       UpperCAmelCase_			:    str   						= {"""input_ids""": [[0, 490, 14328, 4507, 354, 47, 43669, 95, 25, 78117, 20215, 19779, 190, 22, 400, 4, 35343, 80310, 603, 86, 24937, 105, 33438, 94762, 196, 39642, 7, 15, 15933, 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, 10534, 87, 25, 66, 3358, 196, 55289, 8, 82961, 81, 2204, 75203, 7, 15, 763, 12956, 216, 178, 14328, 9595, 1377, 69693, 7, 448, 71021, 196, 18106, 1437, 13974, 108, 9083, 4, 49315, 7, 39, 86, 1326, 2793, 46333, 4, 448, 196, 74588, 7, 49315, 7, 39, 21, 822, 38470, 74, 21, 66723, 62480, 8, 22050, 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.
       UpperCAmelCase_			:    str   						= [
           """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__   ,)




"""simple docstring"""




__UpperCamelCase						=      0  # The first color of the flag.
__UpperCamelCase						=      1  # The second color of the flag.
__UpperCamelCase						=      2  # The third color of the flag.
__UpperCamelCase						=      (red, white, blue)


def     lowercase			(SCREAMING_SNAKE_CASE_		:				list  )   ->						list:
						if not sequence:
												return []
						if len(SCREAMING_SNAKE_CASE_  ) == 1:
												return list(SCREAMING_SNAKE_CASE_  )
						SCREAMING_SNAKE_CASE													=					0
						SCREAMING_SNAKE_CASE													=					len(SCREAMING_SNAKE_CASE_  ) - 1
						SCREAMING_SNAKE_CASE													=					0
						while mid <= high:
												if sequence[mid] == colors[0]:
																		SCREAMING_SNAKE_CASE							,				SCREAMING_SNAKE_CASE													=					sequence[mid], sequence[low]
																		low += 1
																		mid += 1
												elif sequence[mid] == colors[1]:
																		mid += 1
												elif sequence[mid] == colors[2]:
																		SCREAMING_SNAKE_CASE							,				SCREAMING_SNAKE_CASE													=					sequence[high], sequence[mid]
																		high -= 1
												else:
																		SCREAMING_SNAKE_CASE													=					F'The elements inside the sequence must contains only {colors} values'
																		raise ValueError(SCREAMING_SNAKE_CASE_  )
						return sequence


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	__UpperCamelCase						=      input('''Enter numbers separated by commas:\n''').strip()
	__UpperCamelCase						=      [int(item.strip()) for item in user_input.split(''',''')]
	print(f'''{dutch_national_flag_sort(unsorted)}''')


