




'''simple docstring'''


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


__lowercase							:   Any					=     logging.get_logger(__name__)

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

class 	__lowercase				(  _lowercase    ):
			lowerCamelCase			:		List[str]	      =			"roc_bert"

			def __init__(self			,   A=3_0_5_2_2			,   A=7_6_8			,   A=1_2			,   A=1_2			,   A=3_0_7_2			,   A="gelu"			,   A=0.1			,   A=0.1			,   A=5_1_2			,   A=2			,   A=0.02			,   A=1E-12			,   A=True			,   A=0			,   A="absolute"			,   A=None			,   A=True			,   A=True			,   A=7_6_8			,   A=9_1_0			,   A=5_1_2			,   A=2_4_8_5_8			,   A=True			,   **A			,   ):
								lowerCamelCase_					:      Tuple     =		vocab_size
								lowerCamelCase_					:      int     =		max_position_embeddings
								lowerCamelCase_					:      List[Any]     =		hidden_size
								lowerCamelCase_					:      List[str]     =		num_hidden_layers
								lowerCamelCase_					:      Dict     =		num_attention_heads
								lowerCamelCase_					:      Dict     =		intermediate_size
								lowerCamelCase_					:      List[str]     =		hidden_act
								lowerCamelCase_					:      Union[str, Any]     =		hidden_dropout_prob
								lowerCamelCase_					:      str     =		attention_probs_dropout_prob
								lowerCamelCase_					:      Union[str, Any]     =		initializer_range
								lowerCamelCase_					:      Any     =		type_vocab_size
								lowerCamelCase_					:      List[Any]     =		layer_norm_eps
								lowerCamelCase_					:      Optional[Any]     =		use_cache
								lowerCamelCase_					:      Tuple     =		enable_pronunciation
								lowerCamelCase_					:      Tuple     =		enable_shape
								lowerCamelCase_					:      List[Any]     =		pronunciation_embed_dim
								lowerCamelCase_					:      List[Any]     =		pronunciation_vocab_size
								lowerCamelCase_					:      List[str]     =		shape_embed_dim
								lowerCamelCase_					:      List[Any]     =		shape_vocab_size
								lowerCamelCase_					:      str     =		concat_input
								lowerCamelCase_					:      Optional[Any]     =		position_embedding_type
								lowerCamelCase_					:      List[str]     =		classifier_dropout
								super().__init__(pad_token_id=A			,   **A      )




'''simple docstring'''


import itertools
import math




def lowercase_	(   _lowercase				)     ->							bool:
					'''simple docstring'''

					if 1 < number < 4:
										# 2 and 3 are primes
										return True
					elif number < 2 or number % 2 == 0 or number % 3 == 0:
										# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
										return False

					# All primes number are in format of 6k +/- 1
					for i in range(5			,       int(math.sqrt(_lowercase				) + 1				)			,       6				):
										if number % i == 0 or number % (i + 2) == 0:
															return False
					return True




def lowercase_	(   )     ->							Optional[int]:
					'''simple docstring'''

					lowerCamelCase_					:      Union[str, Any]     =		2
					while True:
										if is_prime(_lowercase				):
															yield num
										num += 1




def lowercase_	(   _lowercase = 10_001				)     ->							int:
					'''simple docstring'''

					return next(itertools.islice(prime_generator()			,       nth - 1			,       _lowercase				)				)


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


