

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


snake_case_			  = logging.get_logger(__name__)

snake_case_			  = {
    '''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       SCREAMING_SNAKE_CASE__					(__snake_case     ):
    __lowerCamelCase						:       List[str]														=     """gpt_neox"""





    def __init__(      self						,   a=5_0432						,   a=6144						,   a=44						,   a=64						,   a=2_4576						,   a="gelu"						,   a=0.25						,   a=1_0000						,   a=0.0						,   a=0.0						,   a=0.1						,   a=2048						,   a=0.02						,   a=1e-5						,   a=True						,   a=0						,   a=2						,   a=False						,   a=True						,   a=None						,   **a						,   ):
         super().__init__(bos_token_id=a						,   eos_token_id=a						,   **a)
         lowercase__    :   List[str]      =       vocab_size
         lowercase__    :   Optional[int]      =       max_position_embeddings
         lowercase__    :   Union[str, Any]      =       hidden_size
         lowercase__    :   List[Any]      =       num_hidden_layers
         lowercase__    :   str      =       num_attention_heads
         lowercase__    :   Tuple      =       intermediate_size
         lowercase__    :   Union[str, Any]      =       hidden_act
         lowercase__    :   Optional[int]      =       rotary_pct
         lowercase__    :   Dict      =       rotary_emb_base
         lowercase__    :   int      =       attention_dropout
         lowercase__    :   str      =       hidden_dropout
         lowercase__    :   Dict      =       classifier_dropout
         lowercase__    :   Optional[int]      =       initializer_range
         lowercase__    :   List[Any]      =       layer_norm_eps
         lowercase__    :   Optional[int]      =       use_cache
         lowercase__    :   Optional[int]      =       tie_word_embeddings
         lowercase__    :   Dict      =       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       snake_case_				(      self):
         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}""")
         lowercase__    :   Union[str, Any]      =       self.rope_scaling.get('type'						,   a)
         lowercase__    :   Optional[int]      =       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 	snake_case__			(    SCREAMING_SNAKE_CASE_		:    int			):



     '''simple docstring'''





     lowercase__    :   Optional[Any]      =       []
     lowercase__    :   str      =       2
     lowercase__    :   Optional[Any]      =       int(math.sqrt(SCREAMING_SNAKE_CASE_			)			)  # Size of every segment
     lowercase__    :   Dict      =       [True] * (end + 1)
     lowercase__    :   Union[str, Any]      =       []

     while start <= end:
          if temp[start] is True:
               in_prime.append(SCREAMING_SNAKE_CASE_			)
               for i in range(start * start	,     end + 1	,     SCREAMING_SNAKE_CASE_			):
                    lowercase__    :   int      =       False
          start += 1
     prime += in_prime

     lowercase__    :   Optional[int]      =       end + 1
     lowercase__    :   List[str]      =       min(2 * end	,     SCREAMING_SNAKE_CASE_			)

     while low <= n:
          lowercase__    :   str      =       [True] * (high - low + 1)
          for each in in_prime:
               lowercase__    :   str      =       math.floor(low / each			) * each
               if t < low:
                    t += each

               for j in range(SCREAMING_SNAKE_CASE_	,     high + 1	,     SCREAMING_SNAKE_CASE_			):
                    lowercase__    :   Optional[Any]      =       False

          for j in range(len(SCREAMING_SNAKE_CASE_			)			):
               if temp[j] is True:
                    prime.append(j + low			)

          lowercase__    :   Optional[Any]      =       high + 1
          lowercase__    :   Optional[int]      =       min(high + end	,     SCREAMING_SNAKE_CASE_			)

     return prime

print(sieve(10**6))

