code: def forward(self, x):
      x = self.layer_1(x)
      x = self.layer_2(x)
      x = self.layer_3(x)
      return x
  
imports: import collections
  import os
  from copy import deepcopy
  from unittest import mock
  from unittest.mock import MagicMock, call, patch
  import lightning.fabric
  import pytest
  import torch
  from lightning.fabric.utilities.imports import _IS_WINDOWS
  from lightning.pytorch import Trainer
  from lightning.pytorch.accelerators import CPUAccelerator, XLAAccelerator
  from lightning.pytorch.demos.boring_classes import BoringModel, RandomDataset
  from lightning.pytorch.plugins import Precision, XLACheckpointIO, XLAPrecision
  from lightning.pytorch.strategies import DDPStrategy, XLAStrategy
  from lightning.pytorch.utilities import find_shared_parameters
  from torch import nn
  from torch.utils.data import DataLoader
  from tests_pytorch.helpers.runif import RunIf
  from tests_pytorch.trainer.connectors.test_accelerator_connector import DeviceMock
  from tests_pytorch.trainer.optimization.test_manual_optimization import assert_emtpy_grad
label_desc: Use image node_id 2 for calling the WeightSharingModule obj's underlying member method code with example usage: obj.forward(x) and returns: x