



'''simple docstring'''





import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


_lowerCAmelCase										=     get_tests_dir('''fixtures/test_sentencepiece_bpe.model''')






class 	lowerCAmelCase_(    SCREAMING_SNAKE_CASE_						,			unittest.TestCase					):
  '''simple docstring'''




  __lowercase							:				Dict           =				BartphoTokenizer
  __lowercase							:				Tuple           =				False
  __lowercase							:				List[str]           =				True




  def 							UpperCAmelCase_     (   self				)   ->		Union[str, Any]:
      super().setUp()

      lowerCAmelCase__			:  Tuple											= ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]
      lowerCAmelCase__			:  Optional[int]											= dict(zip(__UpperCAmelCase  ,range(len(__UpperCAmelCase				)				)				)				)
      lowerCAmelCase__			:  Optional[Any]											= {"""unk_token""": """<unk>"""}

      lowerCAmelCase__			:  int											= os.path.join(self.tmpdirname  ,VOCAB_FILES_NAMES["""monolingual_vocab_file"""]				)
      with open(self.monolingual_vocab_file  ,"""w"""  ,encoding="""utf-8"""				) as fp:
          for token in vocab_tokens:
              fp.write(F"""{token} {vocab_tokens[token]}\n"""				)

      lowerCAmelCase__			:  Union[str, Any]											= BartphoTokenizer(__UpperCAmelCase  ,self.monolingual_vocab_file  ,**self.special_tokens_map				)
      tokenizer.save_pretrained(self.tmpdirname				)




  def 							UpperCAmelCase_     (   self  ,**__UpperCAmelCase				)   ->		List[str]:
      kwargs.update(self.special_tokens_map				)
      return BartphoTokenizer.from_pretrained(self.tmpdirname  ,**__UpperCAmelCase				)




  def 							UpperCAmelCase_     (   self  ,__UpperCAmelCase				)   ->		int:
      lowerCAmelCase__			:  Optional[int]											= """This is a là test"""
      lowerCAmelCase__			:  Any											= """This is a<unk><unk> test"""
      return input_text, output_text






  def 							UpperCAmelCase_     (   self				)   ->		Tuple:
      lowerCAmelCase__			:  Optional[Any]											= BartphoTokenizer(__UpperCAmelCase  ,self.monolingual_vocab_file  ,**self.special_tokens_map				)
      lowerCAmelCase__			:  str											= """This is a là test"""
      lowerCAmelCase__			:  int											= """▁This ▁is ▁a ▁l à ▁t est""".split()
      lowerCAmelCase__			:  List[str]											= tokenizer.tokenize(__UpperCAmelCase				)
      self.assertListEqual(__UpperCAmelCase  ,__UpperCAmelCase				)

      lowerCAmelCase__			:  str											= tokens + [tokenizer.unk_token]
      lowerCAmelCase__			:  Any											= [4, 5, 6, 3, 3, 7, 8, 3]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase				)  ,__UpperCAmelCase				)







'''simple docstring'''





def        _SCREAMING_SNAKE_CASE  (	UpperCamelCase      ):



    """simple docstring"""





    if any(not isinstance(UpperCamelCase							,   UpperCamelCase      ) or x < 0 for x in sequence      ):
        raise TypeError("""Sequence must be list of non-negative integers"""      )
    for _ in range(len(UpperCamelCase      )      ):
        for i, (rod_upper, rod_lower) in enumerate(zip(UpperCamelCase							,   sequence[1:]      )      ):
            if rod_upper > rod_lower:
                sequence[i] -= rod_upper - rod_lower
                sequence[i + 1] += rod_upper - rod_lower
    return sequence


if __name__ == "__main__":
 assert bead_sort([5, 4, 3, 2, 1]) == [1, 2, 3, 4, 5]
 assert bead_sort([7, 9, 4, 3, 5]) == [3, 4, 5, 7, 9]


