code: def test_container(self):
      net = torch.nn.Conv2d(1, 1, 3, padding=1)
  
      opt = torch.optim.Adam(net.parameters())
  
      img = torch.rand(1, 16, 16)
      data = {CommonKeys.IMAGE: img, CommonKeys.LABEL: img}
      loader = DataLoader([data for _ in range(10)])
  
      trainer = SupervisedTrainer(
          device=torch.device("cpu"),
          max_epochs=1,
          train_data_loader=loader,
          network=net,
          optimizer=opt,
          loss_function=torch.nn.L1Loss(),
      )
  
      con = ThreadContainer(trainer)
      con.start()
      time.sleep(1)  # wait for trainer to start
  
      self.assertTrue(con.is_alive)
      self.assertIsNotNone(con.status())
      self.assertTrue(len(con.status_dict) > 0)
  
      con.join()
  
file_path: MONAI/tests/test_threadcontainer.py
imports: from __future__ import annotations
  import os
  import tempfile
  import time
  import unittest
  import torch
  from monai.data import DataLoader
  from monai.utils import optional_import, set_determinism
  from monai.utils.enums import CommonKeys
  from tests.utils import SkipIfNoModule
label_desc: Use image node_id 1 for calling the TestThreadContainer obj's underlying member method code with example usage: obj.test_container() without return types