code: def test_fields(self):
      self.assertEqual(dst.get_rank(), DistributedHelper.rank)
      self.assertEqual(
          dst.get_world_size(), DistributedHelper.world_size
      )
      self.assertEqual(True, DistributedHelper.is_distributed)
      self.assertEqual(
          dst.get_rank() == 0, DistributedHelper.is_main_process
      )
  
      if self.use_gpu_in_tests:
          self.assertEqual("nccl", DistributedHelper.backend)
          self.assertTrue(DistributedHelper.forced_cuda_comm)
      else:
          self.assertEqual("gloo", DistributedHelper.backend)
          self.assertFalse(DistributedHelper.forced_cuda_comm)
  
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 14 for calling the DistributedHelperTests obj's underlying member method code with example usage: obj.test_fields() without return types