


'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCAmelCase						=					logging.get_logger(__name__)

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






class        lowerCAmelCase_  (     UpperCAmelCase	):
       __UpperCAmelCase					='open-llama'






       def __init__( self			,     _UpperCamelCase=10_0000			,     _UpperCamelCase=4096			,     _UpperCamelCase=1_1008			,     _UpperCamelCase=32			,     _UpperCamelCase=32			,     _UpperCamelCase="silu"			,     _UpperCamelCase=2048			,     _UpperCamelCase=0.02			,     _UpperCamelCase=1e-6			,     _UpperCamelCase=True			,     _UpperCamelCase=0			,     _UpperCamelCase=1			,     _UpperCamelCase=2			,     _UpperCamelCase=False			,     _UpperCamelCase=True			,     _UpperCamelCase=0.1			,     _UpperCamelCase=0.1			,     _UpperCamelCase=True			,     _UpperCamelCase=True			,     _UpperCamelCase=None			,     **_UpperCamelCase			,     )->      Tuple:
            _A				=							vocab_size
            _A				=							max_position_embeddings
            _A				=							hidden_size
            _A				=							intermediate_size
            _A				=							num_hidden_layers
            _A				=							num_attention_heads
            _A				=							hidden_act
            _A				=							initializer_range
            _A				=							rms_norm_eps
            _A				=							use_cache
            _A				=							kwargs.pop(
                'use_memorry_efficient_attention'			,     _UpperCamelCase   )
            _A				=							hidden_dropout_prob
            _A				=							attention_dropout_prob
            _A				=							use_stable_embedding
            _A				=							shared_input_output_embedding
            _A				=							rope_scaling
            self._rope_scaling_validation()

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






       def   UpperCamelCase						( self   )->      List[str]:
            if self.rope_scaling is None:
                 return

            if not isinstance(self.rope_scaling			,     _UpperCamelCase   ) 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				=							self.rope_scaling.get('type'			,     _UpperCamelCase   )
            _A				=							self.rope_scaling.get('factor'			,     _UpperCamelCase   )
            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(_UpperCamelCase			,     _UpperCamelCase   ) 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_ ( __UpperCamelCase					:       int							,    __UpperCamelCase					:       int		)					->	int:







     """simple docstring"""
     while second != 0:
          _A				=							first & second
          first ^= second
          _A				=							c << 1
     return first


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    lowerCAmelCase						=					int(input("""Enter the first number: """).strip())
    lowerCAmelCase						=					int(input("""Enter the second number: """).strip())
    print(F'{add(first, second) = }')





