



'''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


lowercase_		       =  get_tests_dir("fixtures/test_sentencepiece_bpe.model")






class __A			(  A   ,   unittest.TestCase						):



 '''simple docstring'''







 __lowerCamelCase    :       Tuple          =       BartphoTokenizer
 __lowerCamelCase    :       Optional[int]          =       False
 __lowerCamelCase    :       int          =       True



 def 					a__  (self       )    ->     Dict:


      """simple docstring"""



      super().setUp()

      _a      =  ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']
      _a      =  dict(zip(A ,   range(len(A       )       )       )       )
      _a      =  {'''unk_token''': '''<unk>'''}

      _a      =  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'''       )

      _a      =  BartphoTokenizer(A ,   self.monolingual_vocab_file ,   **self.special_tokens_map       )
      tokenizer.save_pretrained(self.tmpdirname       )



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


      """simple docstring"""



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



 def 					a__  (self ,   A       )    ->     Dict:


      """simple docstring"""



      _a      =  '''This is a là test'''
      _a      =  '''This is a<unk><unk> test'''
      return input_text, output_text



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


      """simple docstring"""



      _a      =  BartphoTokenizer(A ,   self.monolingual_vocab_file ,   **self.special_tokens_map       )
      _a      =  '''This is a là test'''
      _a      =  '''▁This ▁is ▁a ▁l à ▁t est'''.split()
      _a      =  tokenizer.tokenize(A       )
      self.assertListEqual(A ,   A       )

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








'''simple docstring'''





from __future__ import annotations

from typing import TypedDict






class __A			(  A						):



 '''simple docstring'''







 __lowerCamelCase    :       str
 __lowerCamelCase    :       int





def lowerCAmelCase  (__A):



     """simple docstring"""



     if not isinstance(__A  ,	__A):
          raise TypeError('''The parameter s type must be str.''')

     return [s[i:] + s[:i] for i in range(len(__A))]




def lowerCAmelCase  (__A):



     """simple docstring"""



     if not isinstance(__A  ,	__A):
          raise TypeError('''The parameter s type must be str.''')
     if not s:
          raise ValueError('''The parameter s must not be empty.''')

     _a      =  all_rotations(__A)
     rotations.sort()  # sort the list of rotations in alphabetically order
     # make a string composed of the last char of each rotation
     _a      =  {
         "bwt_string": "".join([word[-1] for word in rotations]),
         "idx_original_string": rotations.index(__A),
     }
     return response




def lowerCAmelCase  (__A  ,	__A):



     """simple docstring"""



     if not isinstance(__A  ,	__A):
          raise TypeError('''The parameter bwt_string type must be str.''')
     if not bwt_string:
          raise ValueError('''The parameter bwt_string must not be empty.''')
     try:
          _a      =  int(__A)
     except ValueError:
          raise TypeError(
              '''The parameter idx_original_string type must be int or passive'''
              ''' of cast to int.''')
     if idx_original_string < 0:
          raise ValueError('''The parameter idx_original_string must not be lower than 0.''')
     if idx_original_string >= len(__A):
          raise ValueError(
              '''The parameter idx_original_string must be lower than''' ''' len(bwt_string).''')

     _a      =  [''''''] * len(__A)
     for _ in range(len(__A)):
          for i in range(len(__A)):
               _a      =  bwt_string[i] + ordered_rotations[i]
          ordered_rotations.sort()
     return ordered_rotations[idx_original_string]


if __name__ == "__main__":
  lowercase_		       =  "Provide a string that I will generate its BWT transform: "
  lowercase_		       =  input(entry_msg).strip()
  lowercase_		       =  bwt_transform(s)
  print(
      F"""Burrows Wheeler transform for string '{s}' results """
      F"""in '{result['bwt_string']}'"""
  )
  lowercase_		       =  reverse_bwt(result["bwt_string"], result["idx_original_string"])
  print(
      F"""Reversing Burrows Wheeler transform for entry '{result['bwt_string']}' """
      F"""we get original string '{original_string}'"""
  )



