code: def test_events(self):
      runner = click.testing.CliRunner()
      c2_dir = tempfile.mkdtemp()
      np.random.seed(1701)
      n_iters = 2
      blobs = ["w", "b"]
      data = np.random.randn(len(blobs), n_iters, 10)
      for i, blob in enumerate(blobs):
          with open(os.path.join(c2_dir, blob), "w") as f:
              for row in data[i]:
                  stats = [row.min(), row.max(), row.mean(), row.std()]
                  f.write(" ".join(str(s) for s in stats) + "\n")
  
      # Test error handling path
      with open(os.path.join(c2_dir, "not-a-summary"), "w") as f:
          f.write("not-a-summary")
  
      tf_dir = tempfile.mkdtemp()
      result = runner.invoke(
          tb.cli,
          [
              "tensorboard-events",
              "--c2-dir",
              c2_dir,
              "--tf-dir",
              tf_dir,
          ],
      )
      self.assertEqual(result.exit_code, 0)
      entries = list(os.walk(tf_dir))
      self.assertEqual(len(entries), 1)
      ((d, _, (fname,)),) = entries
      self.assertEqual(tf_dir, d)
      events = load_events(os.path.join(tf_dir, fname))
      self.assertEqual(len(events), n_iters + 1)
      events = events[1:]
      self.maxDiff = None
      self.assertEqual(len(events), 2)
  
file_path: pytorch/caffe2/contrib/tensorboard/tensorboard_test.py
imports: import click.testing
  import numpy
  import os
  import tempfile
  import unittest
  from caffe2.python import brew, core, model_helper
  import caffe2.contrib.tensorboard.tensorboard
  import caffe2.contrib.tensorboard.tensorboard_exporter
label_desc: Use image node_id 1 for calling the TensorboardTest obj's underlying member method code with example usage: obj.test_events() without return types