





'''simple docstring'''







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


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

snake_case_     :       str						=  {
    "s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json",
}


class 					__a      (lowerCamelCase     ):
							__a					:   Tuple									=       """open-llama"""

							def __init__(							self							:     Dict       ,     __magic_name__							:     Optional[Any]=10_00_00       ,     __magic_name__							:     Tuple=40_96       ,     __magic_name__							:     Union[str, Any]=1_10_08       ,     __magic_name__							:     List[Any]=32       ,     __magic_name__							:     Optional[Any]=32       ,     __magic_name__							:     List[str]="silu"       ,     __magic_name__							:     Optional[int]=20_48       ,     __magic_name__							:     str=0.0_2       ,     __magic_name__							:     Any=1E-6       ,     __magic_name__							:     Tuple=True       ,     __magic_name__							:     Any=0       ,     __magic_name__							:     Dict=1       ,     __magic_name__							:     Any=2       ,     __magic_name__							:     Optional[Any]=False       ,     __magic_name__							:     Optional[int]=True       ,     __magic_name__							:     Any=0.1       ,     __magic_name__							:     Union[str, Any]=0.1       ,     __magic_name__							:     List[Any]=True       ,     __magic_name__							:     Any=True       ,     __magic_name__							:     int=None       ,     **__magic_name__							:     Dict       ,     )					->       List[str]:







													"""simple docstring"""
													UpperCAmelCase_			:      Union[str, Any]     						=  vocab_size
													UpperCAmelCase_			:      List[str]     						=  max_position_embeddings
													UpperCAmelCase_			:      str     						=  hidden_size
													UpperCAmelCase_			:      Union[str, Any]     						=  intermediate_size
													UpperCAmelCase_			:      Optional[Any]     						=  num_hidden_layers
													UpperCAmelCase_			:      str     						=  num_attention_heads
													UpperCAmelCase_			:      Tuple     						=  hidden_act
													UpperCAmelCase_			:      List[str]     						=  initializer_range
													UpperCAmelCase_			:      Dict     						=  rms_norm_eps
													UpperCAmelCase_			:      List[Any]     						=  use_cache
													UpperCAmelCase_			:      Dict     						=  kwargs.pop(
													    '''use_memorry_efficient_attention'''       ,     __magic_name__   )
													UpperCAmelCase_			:      Union[str, Any]     						=  hidden_dropout_prob
													UpperCAmelCase_			:      Tuple     						=  attention_dropout_prob
													UpperCAmelCase_			:      List[Any]     						=  use_stable_embedding
													UpperCAmelCase_			:      List[str]     						=  shared_input_output_embedding
													UpperCAmelCase_			:      List[Any]     						=  rope_scaling
													self._rope_scaling_validation()

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



							def     UpperCAmelCase__	(							self							:     Optional[Any]   )					->       Any:







													"""simple docstring"""

													if self.rope_scaling is None:
																			return

													if not isinstance(self.rope_scaling       ,     __magic_name__   ) 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}"""   )
													UpperCAmelCase_			:      Dict     						=  self.rope_scaling.get('''type'''       ,     __magic_name__   )
													UpperCAmelCase_			:      Tuple     						=  self.rope_scaling.get('''factor'''       ,     __magic_name__   )
													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(__magic_name__       ,     __magic_name__   ) 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        lowerCamelCase_      (  SCREAMING_SNAKE_CASE__      :			int   ) ->	str:
						if number > 0:
												raise ValueError('''input must be a negative integer'''   )
						UpperCAmelCase_			:      Union[str, Any]     						=  len(bin(SCREAMING_SNAKE_CASE__   )[3:]   )
						UpperCAmelCase_			:      Union[str, Any]     						=  bin(abs(SCREAMING_SNAKE_CASE__   ) - (1 << binary_number_length)   )[3:]
						UpperCAmelCase_			:      Optional[Any]     						=  (
						    (
						        '''1'''
						        + '''0''' * (binary_number_length - len(SCREAMING_SNAKE_CASE__   ))
						        + twos_complement_number
						    )
						    if number < 0
						    else '''0'''
						)
						return "0b" + twos_complement_number


if __name__ == "__main__":
					import doctest

					doctest.testmod()





