


'''simple docstring'''





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


_UpperCAmelCase			:  List[Any]     =logging.get_logger(__name__)

_UpperCAmelCase			:  Tuple     ={}







class 				snake_case__(							UpperCAmelCase__							):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__      :  str					=							"""llama"""
						SCREAMING_SNAKE_CASE__      :  Any					=							["""past_key_values"""]




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

										# for backward compatibility
										if num_key_value_heads is None:
														lowerCAmelCase_ :      List[Any]    				=				num_attention_heads

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

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




						def 						lowercase_ (				self							)					->    str:
										if self.rope_scaling is None:
														return

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



from __future__ import annotations

from math import pi



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )-> dict[str, float]:

				if (inductance, frequency, reactance).count(0 ) != 1:
								raise ValueError('''One and only one argument must be 0''' )
				if inductance < 0:
								raise ValueError('''Inductance cannot be negative''' )
				if frequency < 0:
								raise ValueError('''Frequency cannot be negative''' )
				if reactance < 0:
								raise ValueError('''Inductive reactance cannot be negative''' )
				if inductance == 0:
								return {"inductance": reactance / (2 * pi * frequency)}
				elif frequency == 0:
								return {"frequency": reactance / (2 * pi * inductance)}
				elif reactance == 0:
								return {"reactance": 2 * pi * frequency * inductance}
				else:
								raise ValueError('''Exactly one argument must be 0''' )


if __name__ == "__main__":
						import doctest

						doctest.testmod()