code: def test_attributes_print(self):
      log_stream = StringIO()
      log_handler = logging.StreamHandler(log_stream)
      log_handler.setLevel(logging.INFO)
      key_to_handler = "test_logging"
  
      # set up engine
      def _train_func(engine, batch):
          return [torch.tensor(0.0)]
  
      engine = Engine(_train_func)
  
      # set up dummy metric
      @engine.on(Events.EPOCH_COMPLETED)
      def _update_metric(engine):
          if not hasattr(engine.state, "test1"):
              engine.state.test1 = 0.1
              engine.state.test2 = 0.2
          else:
              engine.state.test1 += 0.1
              engine.state.test2 += 0.2
  
      # set up testing handler
      logger = logging.getLogger(key_to_handler)
      logger.setLevel(logging.INFO)
      logger.addHandler(log_handler)
      stats_handler = StatsHandler(
          name=key_to_handler,
          state_attributes=["test1", "test2", "test3"],
      )
      stats_handler.attach(engine)
  
      engine.run(range(3), max_epochs=2)
  
      # check logging output
      output_str = log_stream.getvalue()
      log_handler.close()
      has_key_word = re.compile(".*State values.*")
      content_count = 0
      for line in output_str.split("\n"):
          if has_key_word.match(line):
              content_count += 1
      self.assertTrue(content_count > 0)
  
imports: from __future__ import annotations
  import logging
  import os
  import re
  import tempfile
  import unittest
  from io import StringIO
  import torch
  from ignite.engine import Engine, Events
  from parameterized import parameterized
  from monai.handlers import StatsHandler
label_desc: Use image node_id 6 for calling the TestHandlerStats obj's underlying member method code with example usage: obj.test_attributes_print() and returns: list