code: def forward(self, input):
      out = super().forward(input)
      if self.return_obj:
          out_obj = self.d_linear(out)
          assert out_obj.bias.ds_status == ZeroParamStatus.AVAILABLE
          # forward the external param
          return out_obj.out, out_obj.bias
      else:
          out, bias = self.d_linear(out)
          assert bias.ds_status == ZeroParamStatus.AVAILABLE
          return out, bias
  
imports: import os
  from types import SimpleNamespace
  import torch
  import pytest
  import deepspeed
  from deepspeed.runtime.zero.partition_parameters import ZeroParamStatus, partitioned_param_data_shape
  import deepspeed.comm
  from unit.common import DistributedTest, get_master_port
label_desc: Use image node_id 2 for calling the DanglingAttention obj's underlying member method code with example usage: obj.forward(input) and returns: out_obj,  out_obj, out,  bias