



"""simple docstring"""






def 			snake_case_    ( A_   :						str,							A_   :						str		):


       '''simple docstring'''





       _lowerCamelCase		:							str            =					len(lowerCAmelCase_		)
       _lowerCamelCase		:							Union[str, Any]            =					[]
       for i in range(len(lowerCAmelCase_		) - pat_len + 1		):
              _lowerCamelCase		:							List[Any]            =					True
              for j in range(lowerCAmelCase_		):
                     if s[i + j] != pattern[j]:
                            _lowerCamelCase		:							Tuple            =					False
                            break
              if match_found:
                     position.append(lowerCAmelCase_		)
       return position


if __name__ == "__main__":
   assert naive_pattern_search('''ABCDEFG''', '''DE''') == [3]
   print(naive_pattern_search('''ABAAABCDBBABCDDEBCABC''', '''ABC'''))






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
     ]




