code: def copy_data_to_new_module(self):
      params = {"attn_nw": self.attn_nw, "attn_nb": self.attn_nb}
      for key in params:
          if params[key] is None:
              setattr(self.module.mlp, key, None)
          else:
              setattr(
                  self.module.mlp,
                  key,
                  torch.nn.parameter.Parameter(
                      params[key].to(
                          get_accelerator().current_device_name()
                      )
                  ),
              )
  
      params = {"norm_w": self.input_nw, "norm_b": self.input_nb}
      for key in params:
          if params[key] is None:
              setattr(self.module, key, None)
          else:
              setattr(
                  self.module,
                  key,
                  torch.nn.parameter.Parameter(
                      params[key].to(
                          get_accelerator().current_device_name()
                      )
                  ),
              )
  
imports: from abc import ABC
  import torch
  import deepspeed
  from deepspeed.ops.transformer.inference.config import DeepSpeedInferenceConfig
  from deepspeed.accelerator import get_accelerator
label_desc: Use image node_id 22 for calling the BaseTransformerContainer obj's underlying member method code with example usage: obj.copy_data_to_new_module() without return types