






'''simple docstring'''







from __future__ import annotations





def 				SCREAMING_SNAKE_CASE_ (UpperCamelCase   )   -> list[int]:
							lowerCamelCase__      :			List[str] 						= [True] * limit
							lowerCamelCase__      :			Union[str, Any] 						= False
							lowerCamelCase__      :			List[str] 						= False
							lowerCamelCase__      :			Any 						= True

							for i in range(3       ,    int(limit**0.5 + 1   )       ,    2   ):
														lowerCamelCase__      :			Any 						= i * 2
														while index < limit:
																					lowerCamelCase__      :			int 						= False
																					lowerCamelCase__      :			Optional[Any] 						= index + i

							lowerCamelCase__      :			List[Any] 						= [2]

							for i in range(3       ,    UpperCamelCase       ,    2   ):
														if is_prime[i]:
																					primes.append(UpperCamelCase   )

							return primes





def 				SCREAMING_SNAKE_CASE_ (UpperCamelCase = 1000000   )   -> int:
							lowerCamelCase__      :			Dict 						= prime_sieve(UpperCamelCase   )
							lowerCamelCase__      :			int 						= 0
							lowerCamelCase__      :			List[Any] 						= 0

							for i in range(len(UpperCamelCase   )   ):
														for j in range(i + length       ,    len(UpperCamelCase   )   ):
																					lowerCamelCase__      :			List[Any] 						= sum(primes[i:j]   )
																					if sol >= ceiling:
																												break

																					if sol in primes:
																												lowerCamelCase__      :			Union[str, Any] 						= j - i
																												lowerCamelCase__      :			Tuple 						= sol

							return largest


if __name__ == "__main__":
			print(F'{solution() = }')









'''simple docstring'''







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


_A			:    str					  =logging.get_logger(__name__)

_A			:    int					  ={
    '''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json''',
}

class _lowercase			(       _lowercase	):
							a          = """roc_bert"""




							def __init__(							self:       Optional[Any]    ,							UpperCamelCase__:       Any=30_522    ,							UpperCamelCase__:       Optional[Any]=768    ,							UpperCamelCase__:       Union[str, Any]=12    ,							UpperCamelCase__:       Tuple=12    ,							UpperCamelCase__:       Tuple=3_072    ,							UpperCamelCase__:       str="gelu"    ,							UpperCamelCase__:       List[Any]=0.1    ,							UpperCamelCase__:       List[str]=0.1    ,							UpperCamelCase__:       Dict=512    ,							UpperCamelCase__:       str=2    ,							UpperCamelCase__:       str=0.02    ,							UpperCamelCase__:       Tuple=1e-12    ,							UpperCamelCase__:       Any=True    ,							UpperCamelCase__:       Union[str, Any]=0    ,							UpperCamelCase__:       List[Any]="absolute"    ,							UpperCamelCase__:       Any=None    ,							UpperCamelCase__:       Any=True    ,							UpperCamelCase__:       Optional[int]=True    ,							UpperCamelCase__:       Union[str, Any]=768    ,							UpperCamelCase__:       int=910    ,							UpperCamelCase__:       Tuple=512    ,							UpperCamelCase__:       int=24_858    ,							UpperCamelCase__:       Optional[Any]=True    ,							**UpperCamelCase__:       Optional[Any]    ,							):
														lowerCamelCase__      :			Optional[Any] 						= vocab_size
														lowerCamelCase__      :			Tuple 						= max_position_embeddings
														lowerCamelCase__      :			List[Any] 						= hidden_size
														lowerCamelCase__      :			int 						= num_hidden_layers
														lowerCamelCase__      :			Tuple 						= num_attention_heads
														lowerCamelCase__      :			Any 						= intermediate_size
														lowerCamelCase__      :			List[str] 						= hidden_act
														lowerCamelCase__      :			str 						= hidden_dropout_prob
														lowerCamelCase__      :			Dict 						= attention_probs_dropout_prob
														lowerCamelCase__      :			Union[str, Any] 						= initializer_range
														lowerCamelCase__      :			Tuple 						= type_vocab_size
														lowerCamelCase__      :			Optional[Any] 						= layer_norm_eps
														lowerCamelCase__      :			List[Any] 						= use_cache
														lowerCamelCase__      :			Tuple 						= enable_pronunciation
														lowerCamelCase__      :			Union[str, Any] 						= enable_shape
														lowerCamelCase__      :			Union[str, Any] 						= pronunciation_embed_dim
														lowerCamelCase__      :			Any 						= pronunciation_vocab_size
														lowerCamelCase__      :			int 						= shape_embed_dim
														lowerCamelCase__      :			Tuple 						= shape_vocab_size
														lowerCamelCase__      :			Optional[Any] 						= concat_input
														lowerCamelCase__      :			str 						= position_embedding_type
														lowerCamelCase__      :			Dict 						= classifier_dropout
														super().__init__(pad_token_id=UpperCamelCase__    ,							**UpperCamelCase__  )

