


"""simple docstring"""







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


__lowercase    =				logging.get_logger(__name__)

__lowercase    =				{
    """abeja/gpt-neox-japanese-2.7b""": """https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json""",
}






class 						_A  (  _a  ):







    """simple docstring"""




    UpperCAmelCase	:							Union[str, Any]     =	"""gpt_neox_japanese"""






    def __init__( self    :   Any    ,			__UpperCAmelCase    :   Optional[int]=32000    ,			__UpperCAmelCase    :   str=2560    ,			__UpperCAmelCase    :   List[str]=32    ,			__UpperCAmelCase    :   Optional[int]=32    ,			__UpperCAmelCase    :   List[Any]=4    ,			__UpperCAmelCase    :   Any="gelu"    ,			__UpperCAmelCase    :   Optional[Any]=1.00    ,			__UpperCAmelCase    :   List[Any]=10000    ,			__UpperCAmelCase    :   Any=2048    ,			__UpperCAmelCase    :   List[Any]=0.02    ,			__UpperCAmelCase    :   List[Any]=1e-5    ,			__UpperCAmelCase    :   List[Any]=True    ,			__UpperCAmelCase    :   Tuple=31996    ,			__UpperCAmelCase    :   Any=31999    ,			__UpperCAmelCase    :   List[str]=0.1    ,			__UpperCAmelCase    :   str=0.0    ,			**__UpperCAmelCase    :   int    ,			):
      super().__init__(bos_token_id=__UpperCAmelCase    ,			eos_token_id=__UpperCAmelCase    ,			**__UpperCAmelCase)
      a						:		str											=      vocab_size
      a						:		Optional[int]											=      max_position_embeddings
      a						:		List[Any]											=      hidden_size
      a						:		List[Any]											=      num_hidden_layers
      a						:		str											=      num_attention_heads
      a						:		Tuple											=      intermediate_multiple_size
      a						:		Union[str, Any]											=      hidden_act
      a						:		Dict											=      rotary_pct
      a						:		Union[str, Any]											=      rotary_emb_base
      a						:		Tuple											=      initializer_range
      a						:		Tuple											=      layer_norm_eps
      a						:		str											=      use_cache
      a						:		str											=      attention_dropout
      a						:		Union[str, Any]											=      hidden_dropout










"""simple docstring"""







from math import ceil, sqrt


def 					lowercase      (    A_ = 1_000_000	)->				int:
  '''simple docstring'''







  a						:		Tuple											=      0

  for outer_width in range(3  ,       (limit // 4) + 2	):
    if outer_width**2 > limit:
      a						:		str											=      max(ceil(sqrt(outer_width**2 - limit	)	)  ,       1	)
    else:
      a						:		Tuple											=      1
    if (outer_width - hole_width_lower_bound) % 2:
      hole_width_lower_bound += 1

    answer += (outer_width - hole_width_lower_bound - 2) // 2 + 1

  return answer


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






