code: def test_device_id(self):
      if self.use_gpu_in_tests:
          self.assertEqual(
              dst.get_rank(), DistributedHelper.get_device_id()
          )
          self.assertEqual(
              torch.device(f"cuda:{dst.get_rank()}"),
              DistributedHelper.make_device(),
          )
      else:
          self.assertEqual(-1, DistributedHelper.get_device_id())
          self.assertEqual(
              torch.device("cpu"), DistributedHelper.make_device()
          )
  
imports: import os
  import random
  import shutil
  import tempfile
  import time
  import unittest
  import numpy
  import torch
  import torch.distributed
  from torch.nn import Module
  from torch.nn.parallel import DistributedDataParallel
  from avalanche.benchmarks.scenarios.deprecated.generators import dataset_benchmark
  from avalanche.benchmarks.utils.classification_dataset import _make_taskaware_tensor_classification_dataset
  from avalanche.distributed import DistributedHelper
  from avalanche.distributed.distributed_helper import RollingSeedContext, BroadcastSeedContext
  from avalanche.models import SimpleMLP, as_multitask
  from avalanche.models.utils import avalanche_model_adaptation
  from avalanche.training.determinism.rng_manager import RNGManager
  from tests.distributed.distributed_test_utils import check_skip_distributed_slow_test, check_skip_distributed_test, suppress_dst_tests_output, common_dst_tests_setup
label_desc: Use image node_id 2 for calling the DistributedHelperTests obj's underlying member method code with example usage: obj.test_device_id() without return types