code: def test_trainer_subprocess_plugin(self):
      pl_model = LightningModule(
          self.model,
          self.loss,
          self.optimizer,
          metrics=[
              torchmetrics.F1Score(
                  "multiclass", num_classes=num_classes
              ),
              torchmetrics.Accuracy(
                  "multiclass", num_classes=num_classes
              ),
          ],
      )
      trainer = Trainer(
          num_processes=2,
          distributed_backend="subprocess",
          max_epochs=4,
          use_ipex=True,
          callbacks=[CheckIPEXCallback()],
      )
      trainer.fit(pl_model, self.data_loader, self.test_data_loader)
      trainer.test(pl_model, self.test_data_loader)
  
imports: import os
  import pytest
  from unittest import TestCase
  import torch
  import torchmetrics
  from torch import nn
  from bigdl.nano.pytorch.lightning import LightningModule
  from bigdl.nano.pytorch import Trainer
  from test.pytorch.utils._train_torch_lightning import create_data_loader, data_transform
  from test.pytorch.utils._train_torch_lightning import create_test_data_loader
  from test.pytorch.utils._train_ipex_callback import CheckIPEXCallback, CheckIPEXFusedStepCallback
  from test.pytorch.tests.train.trainer.test_lightning import ResNet18
  from bigdl.nano.utils.pytorch import TORCH_VERSION_LESS_2_0
  from bigdl.nano.utils.common import _avx2_checker
label_desc: Use image node_id 2 for calling the Plugin obj's underlying member method code with example usage: obj.test_trainer_subprocess_plugin() without return types