




'''simple docstring'''

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


a       :						Optional[Any]								=		logging.get_logger(__name__)

a       :						int								=		{
    '''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__  (			_UpperCamelCase	):
			__SCREAMING_SNAKE_CASE    =			"""gpt_neox"""





			def __init__(      self						:    Dict      ,		a_						:    Any=50_432      ,		a_						:    Dict=6_144      ,		a_						:    Union[str, Any]=44      ,		a_						:    Optional[Any]=64      ,		a_						:    List[Any]=24_576      ,		a_						:    List[str]="gelu"      ,		a_						:    str=0.25      ,		a_						:    Dict=10_000      ,		a_						:    Union[str, Any]=0.0      ,		a_						:    Any=0.0      ,		a_						:    Any=0.1      ,		a_						:    Optional[Any]=2_048      ,		a_						:    Dict=0.02      ,		a_						:    Optional[Any]=1e-5      ,		a_						:    Dict=True      ,		a_						:    List[Any]=0      ,		a_						:    Union[str, Any]=2      ,		a_						:    List[Any]=False      ,		a_						:    Dict=True      ,		a_						:    List[str]=None      ,		**a_						:    Dict      ,		):



						"""simple docstring"""




						super().__init__(bos_token_id=a_      ,		eos_token_id=a_      ,		**a_							)
						__snake_case			=		vocab_size
						__snake_case			=		max_position_embeddings
						__snake_case			=		hidden_size
						__snake_case			=		num_hidden_layers
						__snake_case			=		num_attention_heads
						__snake_case			=		intermediate_size
						__snake_case			=		hidden_act
						__snake_case			=		rotary_pct
						__snake_case			=		rotary_emb_base
						__snake_case			=		attention_dropout
						__snake_case			=		hidden_dropout
						__snake_case			=		classifier_dropout
						__snake_case			=		initializer_range
						__snake_case			=		layer_norm_eps
						__snake_case			=		use_cache
						__snake_case			=		tie_word_embeddings
						__snake_case			=		use_parallel_residual
						__snake_case			=		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 							A (      self						:    Union[str, 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}'''							)
						__snake_case			=		self.rope_scaling.get("type"      ,		a_							)
						__snake_case			=		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}'''							)






'''simple docstring'''


import math
import sys

def   A_      (       SCREAMING_SNAKE_CASE_						)			->int:
  if number != int(SCREAMING_SNAKE_CASE_						):
    raise ValueError("""the value of input must be a natural number"""						)
  if number < 0:
    raise ValueError("""the value of input must not be a negative number"""						)
  if number == 0:
    return 1
  lowercase_     =       [-1] * (number + 1)
  lowercase_     =       0
  for i in range(1 ,	number + 1						):
    lowercase_     =       sys.maxsize
    lowercase_     =       int(math.sqrt(SCREAMING_SNAKE_CASE_						)						)
    for j in range(1 ,	root + 1						):
      lowercase_     =       1 + answers[i - (j**2)]
      lowercase_     =       min(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)
    lowercase_     =       answer
  return answers[number]


if __name__ == "__main__":
       import doctest

       doctest.testmod()

