

"""simple docstring"""
import unittest
import warnings
from dataclasses import dataclass

from transformers.convert_slow_tokenizer import SpmConverter
from transformers.testing_utils import get_tests_dir

@dataclass
class        _UpperCamelCase	:


  """simple docstring"""





  snake_case_        =    42

class        _UpperCamelCase	(						unittest.TestCase	):


  """simple docstring"""





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


         '''simple docstring'''





         __magic_name__			:		List[str]        =     get_tests_dir('''fixtures/test_sentencepiece.model'''      )
         __magic_name__			:		int        =     get_tests_dir('''fixtures/test_sentencepiece_with_bytefallback.model'''      )

         __magic_name__			:		Tuple        =     FakeOriginalTokenizer(vocab_file=snake_case      )

         with warnings.catch_warnings(record=snake_case      ) as w:
                __magic_name__			:		str        =     SpmConverter(snake_case      )
         self.assertEqual(len(snake_case      )       ,       0      )

         __magic_name__			:		Optional[Any]        =     FakeOriginalTokenizer(vocab_file=snake_case      )

         with warnings.catch_warnings(record=snake_case      ) as w:
                __magic_name__			:		str        =     SpmConverter(snake_case      )
         self.assertEqual(len(snake_case      )       ,       1      )

         self.assertIn(
             '''The sentencepiece tokenizer that you are converting to a fast tokenizer uses the byte fallback option'''
             ''' which is not implemented in the fast tokenizers.'''       ,       str(w[0].message      )       ,       )



"""simple docstring"""
def       UpperCamelCase_					(     lowerCamelCase							:					str   )						->     str:



       """simple docstring"""







       return " ".join([word[::-1] for word in input_str.split()]   )


if __name__ == "__main__":
 import doctest

 doctest.testmod()
