





from collections import OrderedDict
from typing import Mapping

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


_UpperCAmelCase             =							logging.get_logger(__name__)

_UpperCAmelCase             =							{
    'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/config.json',
    'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/config.json',
    'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/config.json',
    'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/config.json',
    'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/config.json',
    'roberta-large-openai-detector': 'https://huggingface.co/roberta-large-openai-detector/resolve/main/config.json',
}






class        snake_case_    (		__lowercase						):
  A_      							=   'roberta'






  def __init__(							self			:					Union[str, Any]       ,  _snake_case			:					List[Any]=50265       ,  _snake_case			:					Dict=768       ,  _snake_case			:					Dict=12       ,  _snake_case			:					Optional[Any]=12       ,  _snake_case			:					Optional[int]=3072       ,  _snake_case			:					Dict="gelu"       ,  _snake_case			:					Optional[Any]=0.1       ,  _snake_case			:					List[str]=0.1       ,  _snake_case			:					int=512       ,  _snake_case			:					Tuple=2       ,  _snake_case			:					Dict=0.02       ,  _snake_case			:					Optional[Any]=1E-12       ,  _snake_case			:					Dict=1       ,  _snake_case			:					Optional[int]=0       ,  _snake_case			:					Dict=2       ,  _snake_case			:					Any="absolute"       ,  _snake_case			:					Any=True       ,  _snake_case			:					int=None       ,  **_snake_case			:					Optional[int]       ,  )->Union[str, Any]:






   '''simple docstring'''

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

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






class        snake_case_    (		__lowercase						):






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






   '''simple docstring'''

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






from math import isqrt






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:int   )      ->   list[int]:
 __lowerCAmelCase					:	Tuple      =       [True] * max_number
 for i in range(2   ,   isqrt(max_number - 1   ) + 1   ):
  if is_prime[i]:
   for j in range(i**2   ,   SCREAMING_SNAKE_CASE   ,   SCREAMING_SNAKE_CASE   ):
    __lowerCAmelCase					:	Tuple      =       False

 return [i for i in range(2   ,   SCREAMING_SNAKE_CASE   ) if is_prime[i]]






def 	_SCREAMING_SNAKE_CASE		(      SCREAMING_SNAKE_CASE		:int = 10**8   )      ->   int:
 __lowerCAmelCase					:	int      =       calculate_prime_numbers(max_number // 2   )

 __lowerCAmelCase					:	List[Any]      =       0
 __lowerCAmelCase					:	List[str]      =       0
 __lowerCAmelCase					:	List[Any]      =       len(SCREAMING_SNAKE_CASE   ) - 1
 while left <= right:
  while prime_numbers[left] * prime_numbers[right] >= max_number:
   right -= 1
  semiprimes_count += right - left + 1
  left += 1

 return semiprimes_count


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