





from __future__ import annotations

import sys





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE							)       ->   Optional[Any]:




				"""simple docstring"""




				if n < 0:
								raise ValueError('Negative arguments are not supported'							)
				return _fib(_A							)[0]





def 							__lowerCAmelCase(					_SCREAMING_SNAKE_CASE							)       ->   Dict:




				"""simple docstring"""




				if n == 0:  # (F(0), F(1))
								return (0, 1)

				# F(2n) = F(n)[2F(n+1) − F(n)]
				# F(2n+1) = F(n+1)^2+F(n)^2
				_A, _A    =       _fib(n // 2							)
				_A    =       a * (b * 2 - a)
				_A    =       a * a + b * b
				return (d, c + d) if n % 2 else (c, d)


if __name__ == "__main__":
	__A       : Union[str, Any]						    = int(sys.argv[1])
	print(f"fibonacci({n}) is {fibonacci(n)}")












from transformers import SqueezeBertTokenizer, SqueezeBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow

from ..bert.test_tokenization_bert import BertTokenizationTest







@require_tokenizers
class     lowerCamelCase(	__snake_case  ):
     '''simple docstring'''


     __magic_name__        = SqueezeBertTokenizer
     __magic_name__        = SqueezeBertTokenizerFast
     __magic_name__        = True




     def 					lowerCAmelCase__		(						self							,    **snake_case_       ):
         return SqueezeBertTokenizerFast.from_pretrained(self.tmpdirname							,    **snake_case_       )




     @slow
     def 					lowerCAmelCase__		(						self       ):
         _A    =       SqueezeBertTokenizer.from_pretrained('squeezebert/squeezebert-mnli-headless'       )

         _A    =       tokenizer.encode('sequence builders'							,    add_special_tokens=snake_case_       )
         _A    =       tokenizer.encode('multi-sequence build'							,    add_special_tokens=snake_case_       )

         _A    =       tokenizer.build_inputs_with_special_tokens(snake_case_       )
         _A    =       tokenizer.build_inputs_with_special_tokens(snake_case_							,    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
         ]





