






'''simple docstring'''







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


__lowerCAmelCase									=   logging.get_logger(__name__)

__lowerCAmelCase									=   {
    'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/config.json',
    'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/config.json'
    # See all FNet models at https://huggingface.co/models?filter=fnet
}





class 						SCREAMING_SNAKE_CASE       (       SCREAMING_SNAKE_CASE_							):
			snake_case__	=					"fnet"






			def __init__(			self   :      List[Any]	,    __SCREAMING_SNAKE_CASE   :      Tuple=3_2000	,    __SCREAMING_SNAKE_CASE   :      Optional[int]=768	,    __SCREAMING_SNAKE_CASE   :      Tuple=12	,    __SCREAMING_SNAKE_CASE   :      Union[str, Any]=3072	,    __SCREAMING_SNAKE_CASE   :      List[Any]="gelu_new"	,    __SCREAMING_SNAKE_CASE   :      int=0.1	,    __SCREAMING_SNAKE_CASE   :      str=512	,    __SCREAMING_SNAKE_CASE   :      List[str]=4	,    __SCREAMING_SNAKE_CASE   :      Optional[int]=0.02	,    __SCREAMING_SNAKE_CASE   :      Dict=1e-12	,    __SCREAMING_SNAKE_CASE   :      int=False	,    __SCREAMING_SNAKE_CASE   :      Any=512	,    __SCREAMING_SNAKE_CASE   :      Optional[Any]=3	,    __SCREAMING_SNAKE_CASE   :      Dict=1	,    __SCREAMING_SNAKE_CASE   :      Union[str, Any]=2	,    **__SCREAMING_SNAKE_CASE   :      List[Any]	,    )      ->      List[str]:
							super().__init__(pad_token_id=__SCREAMING_SNAKE_CASE	,    bos_token_id=__SCREAMING_SNAKE_CASE	,    eos_token_id=__SCREAMING_SNAKE_CASE	,    **__SCREAMING_SNAKE_CASE       )

							a_		:	int									=   vocab_size
							a_		:	Optional[int]									=   max_position_embeddings
							a_		:	str									=   hidden_size
							a_		:	Optional[int]									=   num_hidden_layers
							a_		:	Any									=   intermediate_size
							a_		:	List[Any]									=   hidden_act
							a_		:	Tuple									=   hidden_dropout_prob
							a_		:	Optional[int]									=   initializer_range
							a_		:	Union[str, Any]									=   type_vocab_size
							a_		:	Optional[Any]									=   layer_norm_eps
							a_		:	str									=   use_tpu_fourier_optimizations
							a_		:	List[str]									=   tpu_short_seq_length












'''simple docstring'''







import math





def 		_UpperCAmelCase (				__A				: int   ):
				a_		:	str									=   []
				a_		:	Tuple									=   2
				a_		:	Optional[Any]									=   int(math.sqrt(__A   )   )  # Size of every segment
				a_		:	Optional[Any]									=   [True] * (end + 1)
				a_		:	Union[str, Any]									=   []

				while start <= end:
								if temp[start] is True:
												in_prime.append(__A   )
												for i in range(start * start    ,		end + 1    ,		__A   ):
																a_		:	List[Any]									=   False
								start += 1
				prime += in_prime

				a_		:	Any									=   end + 1
				a_		:	Optional[Any]									=   min(2 * end    ,		__A   )

				while low <= n:
								a_		:	Optional[Any]									=   [True] * (high - low + 1)
								for each in in_prime:
												a_		:	Any									=   math.floor(low / each   ) * each
												if t < low:
																t += each

												for j in range(__A    ,		high + 1    ,		__A   ):
																a_		:	Union[str, Any]									=   False

								for j in range(len(__A   )   ):
												if temp[j] is True:
																prime.append(j + low   )

								a_		:	Tuple									=   high + 1
								a_		:	str									=   min(high + end    ,		__A   )

				return prime




print(sieve(10**6))




