code: def test_set_random_seeds_and_align(self):
      DistributedHelper.set_random_seeds(5678)
  
      self.assertEqual(297076, np.random.randint(0, 1000000))
      self.assertEqual(643380, torch.randint(0, 1000000, (1,)).item())
      self.assertEqual(683410, random.randint(0, 1000000))
  
      if DistributedHelper.is_main_process:
          np.random.randint(0, 1000000)
          torch.randint(0, 1000000, (1,))
          random.randint(0, 1000000)
  
      DistributedHelper.align_seeds()
  
      ref_values = (
          int(np.random.randint(0, 1000000)),
          int(torch.randint(0, 1000000, (1,))),
          int(random.randint(0, 1000000)),
      )
  
      DistributedHelper.check_equal_objects(ref_values)
  
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 15 for calling the DistributedHelperTests obj's underlying member method code with example usage: obj.test_set_random_seeds_and_align() without return types