



'''simple docstring'''


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

from ..bert.test_tokenization_bert import BertTokenizationTest




@require_tokenizers
class      __UpperCamelCase       (_UpperCAmelCase			):
 __A			  =					DistilBertTokenizer
 __A			  =					DistilBertTokenizerFast
 __A			  =					True







 @slow
 def   _a   (    self						)    ->    Optional[int]:
       '''simple docstring'''






       lowercase        =							DistilBertTokenizer.from_pretrained("""distilbert-base-uncased"""						)

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

       lowercase        =							tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase						)
       lowercase        =							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
       ]







'''simple docstring'''


import os







def      SCREAMING_SNAKE_CASE				(				):
						lowercase        =							os.path.join(os.path.dirname(lowercase_						) ,  """num.txt"""						)
						with open(lowercase_						) as file_hand:
												return str(sum(int(lowercase_						) for line in file_hand						)						)[:10]


if __name__ == "__main__":
						print(solution())


