






import math
def 						_a    (      a :int )							->			bool:
 assert isinstance(a	,							a ) 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

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

def 						_a    (      a :int	,							a :Optional[int]=1	,							**a :List[str] )							->			str:
 a		  =      factor * value
 a		  =      value

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

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










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


UpperCAmelCase__				   =		logging.get_logger(__name__)

UpperCAmelCase__				   =		{}






class 		lowercase_					(	lowercase   ):






      '''simple docstring'''




      __snake_case       =  '''llama'''
      __snake_case       =  ['''past_key_values''']







      def __init__(      self      :						Optional[Any] ,					__UpperCAmelCase      :						Union[str, Any]=32_000 ,					__UpperCAmelCase      :						str=4_096 ,					__UpperCAmelCase      :						int=11_008 ,					__UpperCAmelCase      :						Tuple=32 ,					__UpperCAmelCase      :						Optional[int]=32 ,					__UpperCAmelCase      :						List[str]=None ,					__UpperCAmelCase      :						Union[str, Any]="silu" ,					__UpperCAmelCase      :						Tuple=2_048 ,					__UpperCAmelCase      :						Optional[Any]=0.02 ,					__UpperCAmelCase      :						Any=1e-6 ,					__UpperCAmelCase      :						Union[str, Any]=True ,					__UpperCAmelCase      :						Optional[int]=0 ,					__UpperCAmelCase      :						Optional[int]=1 ,					__UpperCAmelCase      :						Optional[int]=2 ,					__UpperCAmelCase      :						Tuple=1 ,					__UpperCAmelCase      :						List[str]=False ,					__UpperCAmelCase      :						Tuple=None ,					**__UpperCAmelCase      :						Tuple ,					)    ->str:




       """simple docstring"""


       a		  =      vocab_size
       a		  =      max_position_embeddings
       a		  =      hidden_size
       a		  =      intermediate_size
       a		  =      num_hidden_layers
       a		  =      num_attention_heads

       # for backward compatibility
       if num_key_value_heads is None:
        a		  =      num_attention_heads

       a		  =      num_key_value_heads
       a		  =      hidden_act
       a		  =      initializer_range
       a		  =      rms_norm_eps
       a		  =      pretraining_tp
       a		  =      use_cache
       a		  =      rope_scaling
       self._rope_scaling_validation()

       super().__init__(
           pad_token_id=__UpperCAmelCase ,					bos_token_id=__UpperCAmelCase ,					eos_token_id=__UpperCAmelCase ,					tie_word_embeddings=__UpperCAmelCase ,					**__UpperCAmelCase ,					)







      def       __lowerCAmelCase					(      self      :						Tuple  )    ->Tuple:




       """simple docstring"""


       if self.rope_scaling is None:
        return

       if not isinstance(self.rope_scaling ,					__UpperCAmelCase  ) 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}"""  )
       a		  =      self.rope_scaling.get('''type''' ,					__UpperCAmelCase  )
       a		  =      self.rope_scaling.get('''factor''' ,					__UpperCAmelCase  )
       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(__UpperCAmelCase ,					__UpperCAmelCase  ) or rope_scaling_factor <= 1.0:
        raise ValueError(F"""`rope_scaling`'s factor field must be an float > 1, got {rope_scaling_factor}"""  )


