




"""simple docstring"""

from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowerCamelCase  :			Optional[Any]        =       logging.get_logger(__name__)

_lowerCamelCase  :			Union[str, Any]        =       {
    'andreasmadsen/efficient_mlm_m0.40': (
        'https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'
    ),
}

class        lowercase      (    __UpperCAmelCase):
				__lowerCAmelCase    :    Any         =   """roberta-prelayernorm"""







				def __init__(							self   :					str      ,     _lowerCamelCase   :					Union[str, Any]=5_02_65      ,     _lowerCamelCase   :					str=7_68      ,     _lowerCamelCase   :					str=12      ,     _lowerCamelCase   :					Optional[int]=12      ,     _lowerCamelCase   :					Optional[int]=30_72      ,     _lowerCamelCase   :					List[str]="gelu"      ,     _lowerCamelCase   :					Optional[Any]=0.1      ,     _lowerCamelCase   :					Tuple=0.1      ,     _lowerCamelCase   :					Optional[int]=5_12      ,     _lowerCamelCase   :					Optional[int]=2      ,     _lowerCamelCase   :					Union[str, Any]=0.02      ,     _lowerCamelCase   :					List[Any]=1E-12      ,     _lowerCamelCase   :					Optional[Any]=1      ,     _lowerCamelCase   :					Any=0      ,     _lowerCamelCase   :					str=2      ,     _lowerCamelCase   :					Tuple="absolute"      ,     _lowerCamelCase   :					Union[str, Any]=True      ,     _lowerCamelCase   :					Union[str, Any]=None      ,     **_lowerCamelCase   :					Union[str, Any]      ,     ):



					"""simple docstring"""

					super().__init__(pad_token_id=_lowerCamelCase      ,     bos_token_id=_lowerCamelCase      ,     eos_token_id=_lowerCamelCase      ,     **_lowerCamelCase       )

					A_  :				Optional[int]	   =		vocab_size
					A_  :				Dict	   =		hidden_size
					A_  :				Tuple	   =		num_hidden_layers
					A_  :				Union[str, Any]	   =		num_attention_heads
					A_  :				int	   =		hidden_act
					A_  :				List[Any]	   =		intermediate_size
					A_  :				List[str]	   =		hidden_dropout_prob
					A_  :				str	   =		attention_probs_dropout_prob
					A_  :				Dict	   =		max_position_embeddings
					A_  :				int	   =		type_vocab_size
					A_  :				Tuple	   =		initializer_range
					A_  :				Optional[int]	   =		layer_norm_eps
					A_  :				Dict	   =		position_embedding_type
					A_  :				List[str]	   =		use_cache
					A_  :				List[str]	   =		classifier_dropout

class        lowercase      (    __UpperCAmelCase):







				@property
				def 					a_  (							self   :					str       ):



					"""simple docstring"""

					if self.task == "multiple-choice":
						A_  :				Optional[Any]	   =		{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
					else:
						A_  :				Any	   =		{0: '''batch''', 1: '''sequence'''}
					return OrderedDict(
					    [
					        ('''input_ids''', dynamic_axis),
					        ('''attention_mask''', dynamic_axis),
					    ]       )











"""simple docstring"""

import random

from .binary_exp_mod import bin_exp_mod

def 		lowercase_      (		_UpperCAmelCase  ,      _UpperCAmelCase=1000	):




	"""simple docstring"""






	if n < 2:
		return False

	if n % 2 == 0:
		return n == 2

	# this means n is odd
	A_  :				List[Any]	   =		n - 1
	A_  :				Dict	   =		0
	while d % 2 == 0:
		d /= 2
		exp += 1

	# n - 1=d*(2**exp)
	A_  :				Optional[Any]	   =		0
	while count < prec:
		A_  :				Optional[int]	   =		random.randint(2  ,      n - 1	)
		A_  :				Any	   =		bin_exp_mod(_UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase	)
		if b != 1:
			A_  :				Dict	   =		True
			for _ in range(_UpperCAmelCase	):
				if b == n - 1:
					A_  :				Optional[int]	   =		False
					break
				A_  :				Any	   =		b * b
				b %= n
			if flag:
				return False
			count += 1
	return True


if __name__ == "__main__":
		_lowerCamelCase  :			List[str]        =       abs(int(input('Enter bound : ').strip()))
		print('Here\'s the list of primes:')
		print(', '.join(str(i) for i in range(n + 1) if is_prime_big(i)))





