





"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase:						Optional[int]				   =logging.get_logger(__name__)

lowerCAmelCase:						Optional[Any]				   ={
    'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json',
    # See all GPTNeoX models at https://huggingface.co/models?filter=gpt_neox
}
class lowerCamelCase__	(     __snake_case					):
   __UpperCAmelCase										=       """gpt_neox"""



   def __init__(							self   , snake_case=5_0_4_3_2   , snake_case=6_1_4_4   , snake_case=4_4   , snake_case=6_4   , snake_case=2_4_5_7_6   , snake_case="gelu"   , snake_case=0.25   , snake_case=1_0_0_0_0   , snake_case=0.0   , snake_case=0.0   , snake_case=0.1   , snake_case=2_0_4_8   , snake_case=0.02   , snake_case=1E-5   , snake_case=True   , snake_case=0   , snake_case=2   , snake_case=False   , snake_case=True   , snake_case=None   , **snake_case   , )			->     Optional[Any]:







      """simple docstring"""
      super().__init__(bos_token_id=__lowerCamelCase   , eos_token_id=__lowerCamelCase   , **__lowerCamelCase						)
      lowercase     :      Tuple	=							vocab_size
      lowercase     :      List[Any]	=							max_position_embeddings
      lowercase     :      Optional[int]	=							hidden_size
      lowercase     :      int	=							num_hidden_layers
      lowercase     :      List[str]	=							num_attention_heads
      lowercase     :      int	=							intermediate_size
      lowercase     :      Dict	=							hidden_act
      lowercase     :      str	=							rotary_pct
      lowercase     :      str	=							rotary_emb_base
      lowercase     :      int	=							attention_dropout
      lowercase     :      List[Any]	=							hidden_dropout
      lowercase     :      Optional[int]	=							classifier_dropout
      lowercase     :      Optional[Any]	=							initializer_range
      lowercase     :      List[str]	=							layer_norm_eps
      lowercase     :      Optional[Any]	=							use_cache
      lowercase     :      Optional[int]	=							tie_word_embeddings
      lowercase     :      Any	=							use_parallel_residual
      lowercase     :      str	=							rope_scaling
      self._rope_scaling_validation()

      if self.hidden_size % self.num_attention_heads != 0:
         raise ValueError(
             """The hidden size is not divisble by the number of attention heads! Make sure to update them!"""						)





   def  _UpperCAmelCase						(							self						)			->     Optional[Any]:







      """simple docstring"""
      if self.rope_scaling is None:
         return

      if not isinstance(self.rope_scaling   , __lowerCamelCase						) or len(self.rope_scaling						) != 2:
         raise ValueError(
             """`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, """
             f'''got {self.rope_scaling}'''						)
      lowercase     :      int	=							self.rope_scaling.get("""type"""   , __lowerCamelCase						)
      lowercase     :      Any	=							self.rope_scaling.get("""factor"""   , __lowerCamelCase						)
      if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
         raise ValueError(
             f'''`rope_scaling`\'s name field must be one of [\'linear\', \'dynamic\'], got {rope_scaling_type}'''						)
      if rope_scaling_factor is None or not isinstance(__lowerCamelCase   , __lowerCamelCase						) or rope_scaling_factor <= 1.0:
         raise ValueError(f'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''						)





import os





def 	__a     (      ):
    SCREAMING_SNAKE_CASE										=   os.path.join(os.path.dirname(A__       )			,  "num.txt"       )
    with open(A__       ) as file_hand:
        return str(sum(int(A__       ) for line in file_hand       )       )[:10]


if __name__ == "__main__":
    print(solution())