from collections import OrderedDict
from typing import Mapping

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


_lowerCamelCase					:   str							=		logging.get_logger(__name__)

_lowerCamelCase					:   Dict							=		{
    '''junnyu/roformer_chinese_small''': '''https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json''',
    '''junnyu/roformer_chinese_base''': '''https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json''',
    '''junnyu/roformer_chinese_char_small''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json'''
    ),
    '''junnyu/roformer_chinese_char_base''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_discriminator''': (
        '''https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_generator''': (
        '''https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json'''
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}


class 						lowercase    (     a     ):
							lowercase__						:       Dict								=							"""roformer"""




							def __init__(						self   :					int	,							_UpperCamelCase   :					Union[str, Any]=50_000	,							_UpperCamelCase   :					int=None	,							_UpperCamelCase   :					Tuple=768	,							_UpperCamelCase   :					Optional[int]=12	,							_UpperCamelCase   :					Optional[Any]=12	,							_UpperCamelCase   :					Optional[Any]=3_072	,							_UpperCamelCase   :					List[Any]="gelu"	,							_UpperCamelCase   :					List[Any]=0.1	,							_UpperCamelCase   :					Any=0.1	,							_UpperCamelCase   :					Optional[Any]=1_536	,							_UpperCamelCase   :					Optional[Any]=2	,							_UpperCamelCase   :					Dict=0.0_2	,							_UpperCamelCase   :					Tuple=1e-12	,							_UpperCamelCase   :					Optional[Any]=0	,							_UpperCamelCase   :					int=False	,							_UpperCamelCase   :					Tuple=True	,							**_UpperCamelCase   :					List[Any]	,							)					->				List[str]:



												'''simple docstring'''

												super().__init__(pad_token_id=_UpperCamelCase	,							**_UpperCamelCase      )

												SCREAMING_SNAKE_CASE    			=       vocab_size
												SCREAMING_SNAKE_CASE    			=       hidden_size if embedding_size is None else embedding_size
												SCREAMING_SNAKE_CASE    			=       hidden_size
												SCREAMING_SNAKE_CASE    			=       num_hidden_layers
												SCREAMING_SNAKE_CASE    			=       num_attention_heads
												SCREAMING_SNAKE_CASE    			=       hidden_act
												SCREAMING_SNAKE_CASE    			=       intermediate_size
												SCREAMING_SNAKE_CASE    			=       hidden_dropout_prob
												SCREAMING_SNAKE_CASE    			=       attention_probs_dropout_prob
												SCREAMING_SNAKE_CASE    			=       max_position_embeddings
												SCREAMING_SNAKE_CASE    			=       type_vocab_size
												SCREAMING_SNAKE_CASE    			=       initializer_range
												SCREAMING_SNAKE_CASE    			=       layer_norm_eps
												SCREAMING_SNAKE_CASE    			=       rotary_value
												SCREAMING_SNAKE_CASE    			=       use_cache



class 						lowercase    (     a     ):




							@property
							def 	__snake_case(						self   :					List[Any]      )					->				Mapping[str, Mapping[int, str]]:



												'''simple docstring'''

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





from __future__ import annotations

import math





def 	__lowerCamelCase							(UpperCAmelCase__     :							int  ):

					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(UpperCAmelCase__  ) + 1  )      , 6  ):
										if number % i == 0 or number % (i + 2) == 0:
															return False
					return True


_lowerCamelCase					:   Tuple							=		[num for num in range(3, 10_00_01, 2) if not is_prime(num)]





def 	__lowerCamelCase							(UpperCAmelCase__     :							int  ):
					if not isinstance(UpperCAmelCase__      , UpperCAmelCase__  ):
										raise ValueError("n must be an integer"  )
					if n <= 0:
										raise ValueError("n must be >= 0"  )

					SCREAMING_SNAKE_CASE    			=       []
					for num in range(len(UpperCAmelCase__  )  ):
										SCREAMING_SNAKE_CASE    			=       0
										while 2 * i * i <= odd_composites[num]:
															SCREAMING_SNAKE_CASE    			=       odd_composites[num] - 2 * i * i
															if is_prime(UpperCAmelCase__  ):
																				break
															i += 1
										else:
															list_nums.append(odd_composites[num]  )
															if len(UpperCAmelCase__  ) == n:
																				return list_nums

					return []





def 	__lowerCamelCase							():
					return compute_nums(1  )[0]


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




