





"""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    lowercase_ :
       snake_case__ :							str



class    lowercase_ (   unittest.TestCase							):

       def 						_SCREAMING_SNAKE_CASE(	self   ):






        '''simple docstring'''

        snake_case__										= get_tests_dir("fixtures/test_sentencepiece.model"   )
        snake_case__										= get_tests_dir("fixtures/test_sentencepiece_with_bytefallback.model"   )

        snake_case__										= FakeOriginalTokenizer(vocab_file=__snake_case   )

        with warnings.catch_warnings(record=__snake_case   ) as w:
         snake_case__										= SpmConverter(__snake_case   )
        self.assertEqual(len(__snake_case   )      ,    0   )

        snake_case__										= FakeOriginalTokenizer(vocab_file=__snake_case   )

        with warnings.catch_warnings(record=__snake_case   ) as w:
         snake_case__										= 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   )      ,    )







def 					SCREAMING_SNAKE_CASE	(       __UpperCamelCase			:						float       ,     __UpperCamelCase			:						float      )  ->							float:
    return a + b


if __name__ == "__main__":
 _lowerCamelCase			 =						5
 _lowerCamelCase			 =						6
 print(F"The sum of {a} + {b} is {add(a, b)}")





