




'''simple docstring'''
def 			lowerCamelCase(							SCREAMING_SNAKE_CASE_       ,SCREAMING_SNAKE_CASE_ = False     )		->		bool:
			if n == 2:
						return True
			if not n % 2 or n < 2:
						return False
			if n > 5 and n % 10 not in (1, 3, 7, 9):  # can quickly check last digit
						return False
			if n > 3_3170_4406_4679_8873_8596_1981 and not allow_probable:
						raise ValueError(
						    'Warning: upper bound of deterministic test is exceeded. '
						    'Pass allow_probable=True to allow probabilistic test. '
						    'A return value of True indicates a probable prime.'     )
			# array bounds provided by analysis
			A_									= [
			    2047,
			    137_3653,
			    2532_6001,
			    32_1503_1751,
			    2_1523_0289_8747,
			    3_4747_4966_0383,
			    341_5500_7172_8321,
			    1,
			    382_5123_0565_4641_3051,
			    1,
			    1,
			    3186_6585_7834_0311_5116_7461,
			    3_3170_4406_4679_8873_8596_1981,
			]

			A_									= [2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]
			for idx, _p in enumerate(SCREAMING_SNAKE_CASE_       ,1     ):
						if n < _p:
									# then we have our last prime to check
									A_									= primes[:idx]
									break
			A_		, A_									= n - 1, 0
			# break up n -1 into a power of 2 (s) and
			# remaining odd component
			# essentially, solve for d * 2 ** s == n - 1
			while d % 2 == 0:
						d //= 2
						s += 1
			for prime in plist:
						A_									= False
						for r in range(SCREAMING_SNAKE_CASE_     ):
									A_									= pow(SCREAMING_SNAKE_CASE_       ,d * 2**r       ,SCREAMING_SNAKE_CASE_     )
									# see article for analysis explanation for m
									if (r == 0 and m == 1) or ((m + 1) % n == 0):
												A_									= True
												# this loop will not determine compositeness
												break
						if pr:
									continue
						# if pr is False, then the above loop never evaluated to true,
						# and the n MUST be composite
						return False
			return True





def 			lowerCamelCase(							)		->		None:
			assert not miller_rabin(561     )
			assert miller_rabin(563     )
			# 2047

			assert not miller_rabin(83_8201     )
			assert miller_rabin(83_8207     )
			# 1_373_653

			assert not miller_rabin(1731_6001     )
			assert miller_rabin(1731_6017     )
			# 25_326_001

			assert not miller_rabin(30_7838_6641     )
			assert miller_rabin(30_7838_6653     )
			# 3_215_031_751

			assert not miller_rabin(1_7130_4557_4801     )
			assert miller_rabin(1_7130_4557_4819     )
			# 2_152_302_898_747

			assert not miller_rabin(2_7797_9972_8307     )
			assert miller_rabin(2_7797_9972_8327     )
			# 3_474_749_660_383

			assert not miller_rabin(113_8500_2390_9441     )
			assert miller_rabin(113_8500_2390_9527     )
			# 341_550_071_728_321

			assert not miller_rabin(127_5041_0188_4880_4351     )
			assert miller_rabin(127_5041_0188_4880_4391     )
			# 3_825_123_056_546_413_051

			assert not miller_rabin(796_6646_4458_5077_8779_1867     )
			assert miller_rabin(796_6646_4458_5077_8779_1951     )
			# 318_665_857_834_031_151_167_461

			assert not miller_rabin(5528_4067_7446_6478_9766_0333     )
			assert miller_rabin(5528_4067_7446_6478_9766_0359     )
			# 3_317_044_064_679_887_385_961_981
			# upper limit for probabilistic test


if __name__ == "__main__":
							test_miller_rabin()










'''simple docstring'''
import warnings

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


_SCREAMING_SNAKE_CASE			=						logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE			=						{
    "RUCAIBox/mvp": "https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json",
}
class   __UpperCAmelCase				(     lowerCAmelCase				):



					'''simple docstring'''





					_UpperCamelCase							=		"""mvp"""
					_UpperCamelCase							=		["""past_key_values"""]
					_UpperCamelCase							=		{"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}



					def __init__(	self     :						List[str]      ,       _lowercase     :						int=50_267      ,       _lowercase     :						str=1_024      ,       _lowercase     :						int=12      ,       _lowercase     :						int=4_096      ,       _lowercase     :						Tuple=16      ,       _lowercase     :						Optional[Any]=12      ,       _lowercase     :						Union[str, Any]=4_096      ,       _lowercase     :						List[Any]=16      ,       _lowercase     :						str=0.0      ,       _lowercase     :						List[str]=0.0      ,       _lowercase     :						Dict="gelu"      ,       _lowercase     :						Union[str, Any]=1_024      ,       _lowercase     :						str=0.1      ,       _lowercase     :						List[Any]=0.0      ,       _lowercase     :						Any=0.0      ,       _lowercase     :						List[str]=0.02      ,       _lowercase     :						List[Any]=0.0      ,       _lowercase     :						List[str]=False      ,       _lowercase     :						Tuple=True      ,       _lowercase     :						Any=1      ,       _lowercase     :						Optional[Any]=0      ,       _lowercase     :						Dict=2      ,       _lowercase     :						int=True      ,       _lowercase     :						Any=2      ,       _lowercase     :						Tuple=2      ,       _lowercase     :						Optional[Any]=False      ,       _lowercase     :						List[str]=100      ,       _lowercase     :						List[str]=800      ,       **_lowercase     :						Dict      ,       )    ->							Dict:
								A_									= vocab_size
								A_									= max_position_embeddings
								A_									= d_model
								A_									= encoder_ffn_dim
								A_									= encoder_layers
								A_									= encoder_attention_heads
								A_									= decoder_ffn_dim
								A_									= decoder_layers
								A_									= decoder_attention_heads
								A_									= dropout
								A_									= attention_dropout
								A_									= activation_dropout
								A_									= activation_function
								A_									= init_std
								A_									= encoder_layerdrop
								A_									= decoder_layerdrop
								A_									= classifier_dropout
								A_									= use_cache
								A_									= encoder_layers
								A_									= scale_embedding  # scale factor will be sqrt(d_model) if True
								A_									= use_prompt
								A_									= prompt_length
								A_									= prompt_mid_dim

								super().__init__(
								    pad_token_id=_lowercase      ,       bos_token_id=_lowercase      ,       eos_token_id=_lowercase      ,       is_encoder_decoder=_lowercase      ,       decoder_start_token_id=_lowercase      ,       forced_eos_token_id=_lowercase      ,       **_lowercase      ,       )

								if self.forced_bos_token_id is None and kwargs.get('force_bos_token_to_be_generated'      ,       _lowercase):
											A_									= self.bos_token_id
											warnings.warn(
											    F'Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. '
											    'The config can simply be saved and uploaded again to be fixed.')




