





from __future__ import annotations

from collections import Counter


def 				SCREAMING_SNAKE_CASE__    (     __a ):
	snake_case_		:      Optional[int]           =						[True] * n
	snake_case_		:      List[str]           =						False
	snake_case_		:      Dict           =						False
	snake_case_		:      List[str]           =						True

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

	snake_case_		:      Optional[Any]           =						[2]

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

	return primes


def 				SCREAMING_SNAKE_CASE__    (     __a ):
	snake_case_		:      List[Any]           =						str(__a )
	snake_case_		:      Tuple           =						[]
	snake_case_		:      Tuple           =						['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']

	for duplicate in Counter(__a ) - Counter(set(__a ) ):
		snake_case_		:      int           =						[int(number_str.replace(__a ,			__a ) ) for digit in digits]
		replacements.append(__a )

	return replacements


def 				SCREAMING_SNAKE_CASE__    (     __a = 8 ):
	snake_case_		:      Optional[int]           =						set()

	# Filter primes with less than 3 replaceable digits
	snake_case_		:      Tuple           =						{
	    x for x in set(prime_sieve(1_00_00_00 ) ) if len(str(__a ) ) - len(set(str(__a ) ) ) >= 3
	}

	for prime in primes:
		if prime in numbers_checked:
			continue

		snake_case_		:      List[Any]           =						digit_replacements(__a )

		for family in replacements:
			numbers_checked.update(__a )
			snake_case_		:      Optional[Any]           =						primes.intersection(__a )

			if len(__a ) != family_length:
				continue

			return min(__a )

	return -1


if __name__ == "__main__":
						print(solution())








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


_SCREAMING_SNAKE_CASE   						=		logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE   						=		{
    """uw-madison/nystromformer-512""": """https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json""",
    # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
}
class SCREAMING_SNAKE_CASE_    (       snake_case_       ):
						__magic_name__:      Optional[Any]			   =							"nystromformer"






						def __init__(   self   :   List[str]		, _A   :   Optional[Any]=30000		, _A   :   str=768		, _A   :   Optional[int]=12		, _A   :   Dict=12		, _A   :   Any=3072		, _A   :   str="gelu_new"		, _A   :   Optional[Any]=0.1		, _A   :   int=0.1		, _A   :   Dict=510		, _A   :   List[Any]=2		, _A   :   Optional[Any]=64		, _A   :   Union[str, Any]=64		, _A   :   List[Any]=65		, _A   :   Dict=False		, _A   :   str=0.0_2		, _A   :   Dict=1E-5		, _A   :   List[Any]=1		, _A   :   Optional[int]=0		, _A   :   List[Any]=2		, **_A   :   int		, )				->     int:







							"""simple docstring"""


							snake_case_		:      Union[str, Any]           =						vocab_size
							snake_case_		:      str           =						max_position_embeddings
							snake_case_		:      Tuple           =						hidden_size
							snake_case_		:      Union[str, Any]           =						num_hidden_layers
							snake_case_		:      str           =						num_attention_heads
							snake_case_		:      Optional[Any]           =						intermediate_size
							snake_case_		:      str           =						hidden_act
							snake_case_		:      str           =						hidden_dropout_prob
							snake_case_		:      Optional[Any]           =						attention_probs_dropout_prob
							snake_case_		:      Union[str, Any]           =						initializer_range
							snake_case_		:      Union[str, Any]           =						type_vocab_size
							snake_case_		:      Dict           =						segment_means_seq_len
							snake_case_		:      Tuple           =						num_landmarks
							snake_case_		:      Any           =						conv_kernel_size
							snake_case_		:      List[str]           =						inv_coeff_init_option
							snake_case_		:      str           =						layer_norm_eps
							super().__init__(pad_token_id=_A		, bos_token_id=_A		, eos_token_id=_A		, **_A						)

