






'''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


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






class     a_						(      lowerCamelCase     ,	unittest.TestCase    ):
  lowercase							=				BartphoTokenizer
  lowercase							=				False
  lowercase							=				True

  def   A__						(				self				)  ->				str:



        """simple docstring"""






        super().setUp()

        UpperCamelCase      = ["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]
        UpperCamelCase      = dict(zip(_SCREAMING_SNAKE_CASE      ,		range(len(_SCREAMING_SNAKE_CASE				)				)				)				)
        UpperCamelCase      = {"""unk_token""": """<unk>"""}

        UpperCamelCase      = 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"				)

        UpperCamelCase      = BartphoTokenizer(_SCREAMING_SNAKE_CASE      ,		self.monolingual_vocab_file      ,		**self.special_tokens_map				)
        tokenizer.save_pretrained(self.tmpdirname				)

  def   A__						(				self      ,		**_SCREAMING_SNAKE_CASE				)  ->				int:



        """simple docstring"""






        kwargs.update(self.special_tokens_map				)
        return BartphoTokenizer.from_pretrained(self.tmpdirname      ,		**_SCREAMING_SNAKE_CASE				)

  def   A__						(				self      ,		_SCREAMING_SNAKE_CASE				)  ->				Optional[Any]:



        """simple docstring"""






        UpperCamelCase      = """This is a là test"""
        UpperCamelCase      = """This is a<unk><unk> test"""
        return input_text, output_text


  def   A__						(				self				)  ->				Dict:



        """simple docstring"""






        UpperCamelCase      = BartphoTokenizer(_SCREAMING_SNAKE_CASE      ,		self.monolingual_vocab_file      ,		**self.special_tokens_map				)
        UpperCamelCase      = """This is a là test"""
        UpperCamelCase      = """▁This ▁is ▁a ▁l à ▁t est""".split()
        UpperCamelCase      = tokenizer.tokenize(_SCREAMING_SNAKE_CASE				)
        self.assertListEqual(_SCREAMING_SNAKE_CASE      ,		_SCREAMING_SNAKE_CASE				)

        UpperCamelCase      = tokens + [tokenizer.unk_token]
        UpperCamelCase      = [4, 5, 6, 3, 3, 7, 8, 3]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE				)      ,		_SCREAMING_SNAKE_CASE				)








'''simple docstring'''

def    lowercase__			(				__UpperCamelCase		,						__UpperCamelCase   )->			list:
      UpperCamelCase      = word.split()

      def justify(__UpperCamelCase		,						__UpperCamelCase		,						__UpperCamelCase   ) -> str:
            UpperCamelCase      = max_width - width
            UpperCamelCase      = len(__UpperCamelCase   )
            if len(__UpperCamelCase   ) == 1:
                  # if there is only word in line
                  # just insert overall_spaces_count for the remainder of line
                  return line[0] + " " * overall_spaces_count
            else:
                  UpperCamelCase      = words_count - 1
                  # num_spaces_between_words_list[i] : tells you to insert
                  # num_spaces_between_words_list[i] spaces
                  # after word on line[i]
                  UpperCamelCase      = spaces_to_insert_between_words * [
                      overall_spaces_count // spaces_to_insert_between_words
                  ]
                  UpperCamelCase      = (
                      overall_spaces_count % spaces_to_insert_between_words
                  )
                  # distribute spaces via round robin to the left words
                  for i in range(__UpperCamelCase   ):
                        num_spaces_between_words_list[i] += 1
                  UpperCamelCase      = []
                  for i in range(__UpperCamelCase   ):
                        # add the word
                        aligned_words_list.append(line[i]   )
                        # add the spaces to insert
                        aligned_words_list.append(num_spaces_between_words_list[i] * """ """   )
                  # just add the last word to the sentence
                  aligned_words_list.append(line[-1]   )
                  # join the aligned words list to form a justified line
                  return "".join(__UpperCamelCase   )

      UpperCamelCase      = []
      UpperCamelCase      = []
      UpperCamelCase      = 0
      for word in words:
            if width + len(__UpperCamelCase   ) + len(__UpperCamelCase   ) <= max_width:
                  # keep adding words until we can fill out max_width
                  # width = sum of length of all words (without overall_spaces_count)
                  # len(word) = length of current word
                  # len(line) = number of overall_spaces_count to insert between words
                  line.append(__UpperCamelCase   )
                  width += len(__UpperCamelCase   )
            else:
                  # justify the line and add it to result
                  answer.append(justify(__UpperCamelCase		,						__UpperCamelCase		,						__UpperCamelCase   )   )
                  # reset new line and new width
                  UpperCamelCase  ,UpperCamelCase      = [word], len(__UpperCamelCase   )
      UpperCamelCase      = max_width - width - len(__UpperCamelCase   )
      answer.append(""" """.join(__UpperCamelCase   ) + (remaining_spaces + 1) * """ """   )
      return answer


if __name__ == "__main__":
     from doctest import testmod

     testmod()
