
'''simple docstring'''




def 		lowerCAmelCase_				(   snake_case__						):




    '''simple docstring'''



    if not isinstance(snake_case__		,				snake_case__						):
        raise ValueError('''Input series is not valid, valid series - [2, 4, 6]'''						)
    if len(snake_case__						) == 0:
        raise ValueError('''Input list must be a non empty list'''						)
    if len(snake_case__						) == 1:
        return True
    A       :   Any					=						series[1] - series[0]
    for index in range(len(snake_case__						) - 1						):
        if series[index + 1] - series[index] != common_diff:
            return False
    return True







def 		lowerCAmelCase_				(   snake_case__						):




    '''simple docstring'''



    if not isinstance(snake_case__		,				snake_case__						):
        raise ValueError('''Input series is not valid, valid series - [2, 4, 6]'''						)
    if len(snake_case__						) == 0:
        raise ValueError('''Input list must be a non empty list'''						)
    A       :   Optional[Any]					=						0
    for val in series:
        answer += val
    return answer / len(snake_case__						)


if __name__ == "__main__":
      import doctest

      doctest.testmod()






'''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  A				(							__snake_case						):
     __magic_name__						=		DistilBertTokenizer
     __magic_name__						=		DistilBertTokenizerFast
     __magic_name__						=		True





     @slow
     def 				__lowerCAmelCase							(							self	) ->				Any:






         """simple docstring"""






         A       :   List[Any]					=						DistilBertTokenizer.from_pretrained('''distilbert-base-uncased'''	)

         A       :   Dict					=						tokenizer.encode('''sequence builders'''						,			add_special_tokens=SCREAMING_SNAKE_CASE	)
         A       :   List[str]					=						tokenizer.encode('''multi-sequence build'''						,			add_special_tokens=SCREAMING_SNAKE_CASE	)

         A       :   Optional[Any]					=						tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE	)
         A       :   Tuple					=						tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	)

         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
         ]




