'''simple docstring'''





import math
import sys





def 	lowerCAmelCase_				(					snake_case_       : int			)    ->      int:


     '''simple docstring'''




     if number != int(snake_case_			):
          raise ValueError("the value of input must be a natural number"			)
     if number < 0:
          raise ValueError("the value of input must not be a negative number"			)
     if number == 0:
          return 1
     UpperCAmelCase_           =   [-1] * (number + 1)
     UpperCAmelCase_           =   0
     for i in range(1					,    number + 1			):
          UpperCAmelCase_           =   sys.maxsize
          UpperCAmelCase_           =   int(math.sqrt(snake_case_			)			)
          for j in range(1					,    root + 1			):
               UpperCAmelCase_           =   1 + answers[i - (j**2)]
               UpperCAmelCase_           =   min(snake_case_					,    snake_case_			)
          UpperCAmelCase_           =   answer
     return answers[number]


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      ( UpperCamelCase__	):
    a__       :						Optional[Any]          =  DistilBertTokenizer
    a__       :						Any          =  DistilBertTokenizerFast
    a__       :						str          =  True



    @slow
    def 					_lowercase						(self    :    int ):
         UpperCAmelCase_           =   DistilBertTokenizer.from_pretrained("distilbert-base-uncased" )

         UpperCAmelCase_           =   tokenizer.encode("sequence builders"   ,			add_special_tokens=__a )
         UpperCAmelCase_           =   tokenizer.encode("multi-sequence build"   ,			add_special_tokens=__a )

         UpperCAmelCase_           =   tokenizer.build_inputs_with_special_tokens(__a )
         UpperCAmelCase_           =   tokenizer.build_inputs_with_special_tokens(__a   ,			__a )

         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
         ]




