code: def get_lora_matched_pair(self):
      (
          up_proj_lora,
          gate_proj_lora,
          down_proj_lora,
          q_lora,
          k_lora,
          v_lora,
          out_lora,
      ) = self.get_lora_params()
      ret = [
          (up_proj_lora, self.inter_up_w),
          (gate_proj_lora, self.inter_gate_w),
          (down_proj_lora, self._4hh_w),
          (out_lora, self.dense_w),
          (q_lora, self.qw),
          (k_lora, self.kw),
          (v_lora, self.vw),
      ]
      return ret
  
imports: from .base import *
  from .features import HybridSplitQKVContainer, HybridGatedMLPContainer, MetaTensorContainer
  from deepspeed.utils.types import ActivationFuncType, NormType
  from deepspeed.model_implementations.transformers.ds_gpt import DeepSpeedGPTInference
  import torch
  from torch.nn.parameter import Parameter
  from ..policy import TransformerPolicy, transformer_param_names, maybe_copy, maybe_copy_qkv, maybe_copy_geglu, maybe_get_lora
label_desc: Use image node_id 4 for calling the DS_LLAMAContainer obj's underlying member method code with example usage: obj.get_lora_matched_pair() and returns: ret