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


SCREAMING_SNAKE_CASE__		:					str						=					logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__		:					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       snake_case					(      UpperCamelCase_						):
  lowercase_			=     'gpt_neox'




  def __init__(      self     :	Any     , a_     :	Optional[int]=5_0432     , a_     :	int=6144     , a_     :	List[str]=44     , a_     :	int=64     , a_     :	str=2_4576     , a_     :	Dict="gelu"     , a_     :	Any=0.25     , a_     :	Any=1_0000     , a_     :	Tuple=0.0     , a_     :	str=0.0     , a_     :	int=0.1     , a_     :	List[Any]=2048     , a_     :	List[Any]=0.02     , a_     :	Dict=1e-5     , a_     :	Optional[int]=True     , a_     :	Optional[int]=0     , a_     :	Any=2     , a_     :	int=False     , a_     :	Tuple=True     , a_     :	Dict=None     , **a_     :	List[Any]     , )->       Tuple:




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




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

       if not isinstance(self.rope_scaling     , a_				) 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}'''				)
       SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		self.rope_scaling.get('type'     , a_				)
       SCREAMING_SNAKE_CASE__				:				List[str]			=		self.rope_scaling.get('factor'     , a_				)
       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(a_     , a_				) or rope_scaling_factor <= 1.0:
            raise ValueError(F'''`rope_scaling`\'s factor field must be an float > 1, got {rope_scaling_factor}'''				)




import math







def     _a				(      lowercase__  :			int ):







     '''simple docstring'''


     assert isinstance(lowercase__     ,  lowercase__ ) and (
         number >= 0
     ), "'number' must been an int and positive"

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

     SCREAMING_SNAKE_CASE__				:				Tuple			=		range(3     ,  int(math.sqrt(lowercase__ ) + 1 )     ,  2 )
     return not any(not number % i for i in odd_numbers )







def     _a				(      lowercase__  :			List[str]     ,  lowercase__  :			Any=1     ,  **lowercase__  :			Any ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				int			=		factor * value
     SCREAMING_SNAKE_CASE__				:				Dict			=		value

     while not is_prime(lowercase__ ):
          value += 1 if not ("desc" in kwargs and kwargs["desc"] is True) else -1

     if value == first_value_val:
          return next_prime(value + 1     ,  **lowercase__ )
     return value



