


def       _lowerCAmelCase    (				lowerCAmelCase_				:str		,    lowerCAmelCase_				:str				)->bool:
   '''simple docstring'''






   snake_case_            =       len(lowerCAmelCase_				)
   snake_case_            =       len(lowerCAmelCase_				)
   snake_case_            =       [[False for _ in range(m + 1				)] for _ in range(n + 1				)]
   snake_case_            =       True
   for i in range(lowerCAmelCase_				):
      for j in range(m + 1				):
         if dp[i][j]:
            if j < m and a[i].upper() == b[j]:
               snake_case_            =       True
            if a[i].islower():
               snake_case_            =       True
   return dp[n][m]


if __name__ == "__main__":
   import doctest

   doctest.testmod()








from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest


@require_tokenizers
class      __lowerCAmelCase  (			a       ):






  """simple docstring"""





  _SCREAMING_SNAKE_CASE		     =							DistilBertTokenizer
  _SCREAMING_SNAKE_CASE		     =							DistilBertTokenizerFast
  _SCREAMING_SNAKE_CASE		     =							True



  @slow
  def        lowerCAmelCase__	(  self							:							Tuple	) ->			Optional[Any]:




     """simple docstring"""
     snake_case_            =       DistilBertTokenizer.from_pretrained("distilbert-base-uncased"	)

     snake_case_            =       tokenizer.encode("sequence builders"     ,					add_special_tokens=_lowerCAmelCase	)
     snake_case_            =       tokenizer.encode("multi-sequence build"     ,					add_special_tokens=_lowerCAmelCase	)

     snake_case_            =       tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase	)
     snake_case_            =       tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase     ,					_lowerCAmelCase	)

     assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
     assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
         tokenizer.sep_token_id
     ]




