code: def forward(self, x, x_lengths, **kwargs):
      x = self.layer1(x)
      x = self.layer2(x)
      retval = {
          "loss": x.mean(),
          "stats": {"loss": x.mean()},
          "weight": len(x),
          "optim_idx": torch.randint(0, 2, [1]),
      }
      return force_gatherable(retval, device=x.device)
  
imports: import configargparse
  import pytest
  import torch
  from espnet2.tasks.abs_task import AbsTask
  from espnet2.torch_utils.device_funcs import force_gatherable
  from espnet2.train.abs_espnet_model import AbsESPnetModel
  from espnet2.train.collate_fn import CommonCollateFn
label_desc: Use image node_id 3 for calling the DummyModel obj's underlying member method code with example usage: obj.forward(x, x_lengths) and returns: force_gatherable