code: def test_even(self):
      data = [1, 2, 3, 4, 5]
      sampler = DistributedSampler(dataset=data, shuffle=False)
      samples = np.array([data[i] for i in list(sampler)])
      self.assertEqual(dist.get_rank(), sampler.rank)
      if dist.get_rank() == 0:
          np.testing.assert_allclose(samples, np.array([1, 3, 5]))
  
      if dist.get_rank() == 1:
          np.testing.assert_allclose(samples, np.array([2, 4, 1]))
  
file_path: MONAI/tests/test_sampler_dist.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  import torch.distributed
  from torch.multiprocessing import Manager
  from monai.data import CacheDataset, DataLoader, DistributedSampler
  from monai.transforms import ToTensor
  from tests.utils import DistCall, DistTestCase, assert_allclose
label_desc: Use image node_id 1 for calling the DistributedSamplerTest obj's underlying member method code with example usage: obj.test_even() without return types