docstr: Necessary to implement for `HybridEngineContainer`
docstr_tok: ["Necessary","to","implement","for","`","HybridEngineContainer","`"]
code: def set_lora_params(self):
      """
      Necessary to implement for `HybridEngineContainer`
      """
      self.lora_params = [
          maybe_get_lora(p)
          for p in [
              self.policy.client_module.feed_forward.w3.weight,
              self.policy.client_module.feed_forward.w1.weight,
              self.policy.client_module.feed_forward.w2.weight,
              self.policy.client_module.attention.wq.weight,
              self.policy.client_module.attention.wk.weight,
              self.policy.client_module.attention.wv.weight,
              self.policy.client_module.attention.wo.weight,
          ]
      ]
  
imports: from .base import *
  from .features import HybridSplitQKVContainer, HybridGatedMLPContainer, MetaTensorContainer
  from deepspeed.utils.types import ActivationFuncType, NormType
  from deepspeed.model_implementations.transformers.ds_llama2 import DeepSpeedLlama2Inference
  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 3 for calling the DS_LLAMA2Container obj's underlying member method code with example usage: obj.set_lora_params() without return types