

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


a__												=						logging.get_logger(__name__)

a__												=						{}

class 							UpperCAmelCase_						(     __lowercase  ):
							"""simple docstring"""







							UpperCAmelCase__			:		Optional[int]             =       "llama"
							UpperCAmelCase__			:		List[str]             =       ["past_key_values"]


							def __init__(     self			,				_a=3_2_0_0_0			,				_a=4_0_9_6			,				_a=1_1_0_0_8			,				_a=3_2			,				_a=3_2			,				_a=None			,				_a="silu"			,				_a=2_0_4_8			,				_a=0.02			,				_a=1e-6			,				_a=True			,				_a=0			,				_a=1			,				_a=2			,				_a=1			,				_a=False			,				_a=None			,				**_a			,				)       ->       Dict:
												_a      :       str   =						vocab_size
												_a      :       List[Any]   =						max_position_embeddings
												_a      :       str   =						hidden_size
												_a      :       List[Any]   =						intermediate_size
												_a      :       Tuple   =						num_hidden_layers
												_a      :       Optional[int]   =						num_attention_heads

												# for backward compatibility
												if num_key_value_heads is None:
																	_a      :       List[str]   =						num_attention_heads

												_a      :       Optional[int]   =						num_key_value_heads
												_a      :       Optional[Any]   =						hidden_act
												_a      :       Union[str, Any]   =						initializer_range
												_a      :       str   =						rms_norm_eps
												_a      :       List[Any]   =						pretraining_tp
												_a      :       Any   =						use_cache
												_a      :       int   =						rope_scaling
												self._rope_scaling_validation()

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




							def 							__lowercase							(     self			)       ->       Any:
												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}"""			)
												_a      :       List[str]   =						self.rope_scaling.get('''type'''			,				_a			)
												_a      :       Dict   =						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"""






def      UpperCAmelCase__			(							lowerCAmelCase__	:int = 1_0**9						)					->       int:
      '''simple docstring'''


      lowercase								=      1
      lowercase								=      2

      lowercase								=      0
      lowercase								=      0
      lowercase								=      0
      while perimeter <= max_perimeter:
            perimeters_sum += perimeter

            prev_value += 2 * value
            value += prev_value

            lowercase								=      2 * value + 2 if i % 2 == 0 else 2 * value - 2
            i += 1

      return perimeters_sum


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



