





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


__lowerCamelCase :  List[str]										=  logging.get_logger(__name__)

__lowerCamelCase :  Any										=  {
    '''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-430m-pile''': '''https://huggingface.co/RWKV/rwkv-4-430m-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-1b5-pile''': '''https://huggingface.co/RWKV/rwkv-4-1b5-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-3b-pile''': '''https://huggingface.co/RWKV/rwkv-4-3b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-7b-pile''': '''https://huggingface.co/RWKV/rwkv-4-7b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-4-14b-pile''': '''https://huggingface.co/RWKV/rwkv-4-14b-pile/resolve/main/config.json''',
    '''RWKV/rwkv-raven-1b5''': '''https://huggingface.co/RWKV/rwkv-raven-1b5/resolve/main/config.json''',
    '''RWKV/rwkv-raven-3b''': '''https://huggingface.co/RWKV/rwkv-raven-3b/resolve/main/config.json''',
    '''RWKV/rwkv-raven-7b''': '''https://huggingface.co/RWKV/rwkv-raven-7b/resolve/main/config.json''',
    '''RWKV/rwkv-raven-14b''': '''https://huggingface.co/RWKV/rwkv-raven-14b/resolve/main/config.json''',
}



class       A__     ( UpperCamelCase__    ):
      _UpperCAmelCase			:Any							=     """rwkv"""
      _UpperCAmelCase			:List[Any]							=     {"""max_position_embeddings""": """context_length"""}





      def __init__(				self ,							A_=5_0277 ,							A_=1024 ,							A_=4096 ,							A_=32 ,							A_=None ,							A_=None ,							A_=1e-5 ,							A_=0 ,							A_=0 ,							A_=6 ,							A_=False ,							A_=True ,							**A_ ,							):
       '''simple docstring'''




       UpperCamelCase			:      List[Any] 			=     vocab_size
       UpperCamelCase			:      str 			=     context_length
       UpperCamelCase			:      Tuple 			=     hidden_size
       UpperCamelCase			:      int 			=     num_hidden_layers
       UpperCamelCase			:      Optional[int] 			=     attention_hidden_size if attention_hidden_size is not None else hidden_size
       UpperCamelCase			:      Optional[int] 			=     intermediate_size if intermediate_size is not None else 4 * hidden_size
       UpperCamelCase			:      List[Any] 			=     layer_norm_epsilon
       UpperCamelCase			:      Tuple 			=     rescale_every
       UpperCamelCase			:      Tuple 			=     use_cache

       UpperCamelCase			:      int 			=     bos_token_id
       UpperCamelCase			:      Dict 			=     eos_token_id

       super().__init__(
           tie_word_embeddings=A_ ,							bos_token_id=A_ ,							eos_token_id=A_ ,							**A_     )







from __future__ import annotations



def 	A_       (  _lowerCAmelCase  )		->				list[int]:
 UpperCamelCase			:      Optional[Any] 			=     [True] * limit
 UpperCamelCase			:      Optional[Any] 			=     False
 UpperCamelCase			:      List[str] 			=     False
 UpperCamelCase			:      Tuple 			=     True

 for i in range(3							,     int(limit**0.5 + 1  )							,     2  ):
  UpperCamelCase			:      Optional[Any] 			=     i * 2
  while index < limit:
   UpperCamelCase			:      int 			=     False
   UpperCamelCase			:      Optional[int] 			=     index + i

 UpperCamelCase			:      Any 			=     [2]

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

 return primes



def 	A_       (  _lowerCAmelCase = 100_0000  )		->				int:
 UpperCamelCase			:      Union[str, Any] 			=     prime_sieve(_lowerCAmelCase  )
 UpperCamelCase			:      List[str] 			=     0
 UpperCamelCase			:      Union[str, Any] 			=     0

 for i in range(len(_lowerCAmelCase  )  ):
  for j in range(i + length							,     len(_lowerCAmelCase  )  ):
   UpperCamelCase			:      Dict 			=     sum(primes[i:j]  )
   if sol >= ceiling:
    break

   if sol in primes:
    UpperCamelCase			:      int 			=     j - i
    UpperCamelCase			:      Dict 			=     sol

 return largest


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