




from ...configuration_utils import PretrainedConfig
from ...utils import logging


SCREAMING_SNAKE_CASE:    Union[str, Any]											=   logging.get_logger(__name__)

SCREAMING_SNAKE_CASE:    str											=   {
    'microsoft/mpnet-base': 'https://huggingface.co/microsoft/mpnet-base/resolve/main/config.json',
}



class       lowercase_		(lowercase_   ):
						lowerCAmelCase__ 			="""mpnet"""



						def __init__( self  :      Dict				,       snake_case__  :      Tuple=3_05_27				,       snake_case__  :      Tuple=7_68				,       snake_case__  :      Union[str, Any]=12				,       snake_case__  :      Optional[Any]=12				,       snake_case__  :      str=30_72				,       snake_case__  :      Dict="gelu"				,       snake_case__  :      Tuple=0.1				,       snake_case__  :      Dict=0.1				,       snake_case__  :      Optional[int]=5_12				,       snake_case__  :      Tuple=0.02				,       snake_case__  :      Optional[int]=1e-12				,       snake_case__  :      Union[str, Any]=32				,       snake_case__  :      Optional[Any]=1				,       snake_case__  :      List[Any]=0				,       snake_case__  :      Any=2				,       **snake_case__  :      List[str]				,       ):

								"""simple docstring"""

								super().__init__(pad_token_id=snake_case__				,       bos_token_id=snake_case__				,       eos_token_id=snake_case__				,       **snake_case__     )

								SCREAMING_SNAKE_CASE_							=       vocab_size
								SCREAMING_SNAKE_CASE_							=       hidden_size
								SCREAMING_SNAKE_CASE_							=       num_hidden_layers
								SCREAMING_SNAKE_CASE_							=       num_attention_heads
								SCREAMING_SNAKE_CASE_							=       hidden_act
								SCREAMING_SNAKE_CASE_							=       intermediate_size
								SCREAMING_SNAKE_CASE_							=       hidden_dropout_prob
								SCREAMING_SNAKE_CASE_							=       attention_probs_dropout_prob
								SCREAMING_SNAKE_CASE_							=       max_position_embeddings
								SCREAMING_SNAKE_CASE_							=       initializer_range
								SCREAMING_SNAKE_CASE_							=       layer_norm_eps
								SCREAMING_SNAKE_CASE_							=       relative_attention_num_buckets





from __future__ import annotations

import sys


def 				_a       (				lowerCAmelCase   )->  int:
		if n < 0:
				raise ValueError('Negative arguments are not supported'   )
		return _fib(lowerCAmelCase   )[0]


def 				_a       (				lowerCAmelCase   )->  tuple[int, int]:
		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
		SCREAMING_SNAKE_CASE_			,							SCREAMING_SNAKE_CASE_							=       _fib(n // 2   )
		SCREAMING_SNAKE_CASE_							=       a * (b * 2 - a)
		SCREAMING_SNAKE_CASE_							=       a * a + b * b
		return (d, c + d) if n % 2 else (c, d)


if __name__ == "__main__":
						SCREAMING_SNAKE_CASE:    Optional[int]											=   int(sys.argv[1])
						print(f"""fibonacci({n}) is {fibonacci(n)}""")