





"""simple docstring"""






from typing import Callable, Optional, Union

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


__UpperCAmelCase						=			logging.get_logger(__name__)

__UpperCAmelCase						=			{
    '''microsoft/xprophetnet-large-wiki100-cased''': (
        '''https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/config.json'''
    ),
}



class 					__UpperCAmelCase							(						_UpperCamelCase  ):
				__lowerCamelCase				:	Optional[Any]				     =				"xlm-prophetnet"
				__lowerCamelCase				:	Any				     =				["past_key_values"]
				__lowerCamelCase				:	List[str]				     =				{
				    "num_attention_heads": "num_encoder_attention_heads",
				}
				def __init__(		self    :			Optional[int]	, a_    :			Optional[float] = 0.1	, a_    :			Optional[Union[str, Callable]] = "gelu"	, a_    :			Optional[int] = 3_05_22	, a_    :			Optional[int] = 10_24	, a_    :			Optional[int] = 40_96	, a_    :			Optional[int] = 12	, a_    :			Optional[int] = 16	, a_    :			Optional[int] = 40_96	, a_    :			Optional[int] = 12	, a_    :			Optional[int] = 16	, a_    :			Optional[float] = 0.1	, a_    :			Optional[float] = 0.1	, a_    :			Optional[int] = 5_12	, a_    :			Optional[float] = 0.02	, a_    :			Optional[bool] = True	, a_    :			Optional[bool] = True	, a_    :			Optional[int] = 0	, a_    :			Optional[int] = 2	, a_    :			Optional[int] = 32	, a_    :			Optional[int] = 1_28	, a_    :			Optional[bool] = False	, a_    :			Optional[float] = 0.0	, a_    :			Optional[bool] = True	, a_    :			Optional[int] = 0	, a_    :			Optional[int] = 1	, a_    :			Optional[int] = 2	, **a_    :			Optional[int]	, )	->	List[Any]:



							'''simple docstring'''



							a__  :	Optional[int]		 =			vocab_size
							a__  :	Union[str, Any]		 =			hidden_size
							a__  :	int		 =			encoder_ffn_dim
							a__  :	str		 =			num_encoder_layers
							a__  :	Optional[Any]		 =			num_encoder_attention_heads
							a__  :	Optional[Any]		 =			decoder_ffn_dim
							a__  :	Any		 =			num_decoder_layers
							a__  :	Optional[int]		 =			num_decoder_attention_heads
							a__  :	str		 =			max_position_embeddings
							a__  :	Dict		 =			init_std  # Normal(0, this parameter)
							a__  :	Any		 =			activation_function

							# parameters for xlmprophetnet
							a__  :	List[Any]		 =			ngram
							a__  :	Any		 =			num_buckets
							a__  :	Union[str, Any]		 =			relative_max_distance
							a__  :	List[str]		 =			disable_ngram_loss
							a__  :	str		 =			eps

							# 3 Types of Dropout
							a__  :	Union[str, Any]		 =			attention_dropout
							a__  :	Tuple		 =			activation_dropout
							a__  :	Optional[Any]		 =			dropout

							a__  :	List[str]		 =			use_cache

							super().__init__(
							    pad_token_id=a_	, bos_token_id=a_	, eos_token_id=a_	, is_encoder_decoder=a_	, add_cross_attention=a_	, decoder_start_token_id=a_	, **a_	, )
				@property
				def       UpperCAmelCase      (		self    :			Union[str, Any]    )	->	int:



							'''simple docstring'''



							return self.num_encoder_layers + self.num_decoder_layers






				@num_hidden_layers.setter
				def       UpperCAmelCase      (		self    :			Optional[Any]	, a_    :			Dict    )	->	Any:



							'''simple docstring'''



							raise NotImplementedError(
							    "This model does not support the setting of `num_hidden_layers`. Please set `num_encoder_layers` and"
							    " `num_decoder_layers`."    )






"""simple docstring"""






from __future__ import annotations






def      lowercase__ (					lowerCAmelCase__   :			int			)    ->			list[int]:



			'''simple docstring'''
			a__  :	Tuple		 =			[True] * limit
			a__  :	Tuple		 =			False
			a__  :	int		 =			False
			a__  :	Tuple		 =			True

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

			a__  :	str		 =			[2]

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

			return primes






def      lowercase__ (					lowerCAmelCase__   :			int = 1_0_0_0_0_0_0			)    ->			int:



			'''simple docstring'''
			a__  :	List[Any]		 =			prime_sieve(lowerCAmelCase__			)
			a__  :	int		 =			0
			a__  :	str		 =			0

			for i in range(len(lowerCAmelCase__			)			):
						for j in range(i + length							,			len(lowerCAmelCase__			)			):
									a__  :	List[str]		 =			sum(primes[i:j]			)
									if sol >= ceiling:
												break

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

			return largest


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