code: def forward(self, x, bias=None):
      if bias is None:
          bias = 0.0
      if self.output_as_list:
          return self.fc(x) + bias, self.fc(x) + bias
  
      return self.fc(x) + bias
  
imports: import os
  from importlib.util import find_spec
  from typing import Optional, Union
  from unittest import mock
  from unittest.mock import MagicMock, patch
  import pytest
  import torch
  from packaging.version import Version
  from pytest import approx
  from torch.nn.functional import mse_loss
  from torch.optim import SGD
  import ignite.distributed
  from ignite.distributed.comp_models.base import _torch_version_le_112
  from ignite.engine import _check_arg, create_supervised_evaluator, create_supervised_trainer, Engine, Events, supervised_evaluation_step, supervised_evaluation_step_amp, supervised_training_step_tpu
  from ignite.metrics import MeanSquaredError
label_desc: Use image node_id 2 for calling the DummyModel obj's underlying member method code with example usage: obj.forward(x, bias) and returns: unknown, unknown,  unknown