code: def test_beholder_video(self):
      LOG_DIRECTORY = self.LOG_DIRECTORY
      tensor_and_name = namedtuple("tensor_and_name", "tensor, name")
      fake_param = [
          tensor_and_name(np.random.randn(128, 768, 3), "test" + str(i))
          for i in range(5)
      ]
      arrays = [
          tensor_and_name(np.random.randn(128, 768, 3), "test" + str(i))
          for i in range(5)
      ]
      beholder = beholder_lib.Beholder(logdir=self.LOG_DIRECTORY)
      pkl = fio.read_pickle(
          LOG_DIRECTORY + "/plugins/beholder/config.pkl"
      )
      pkl["is_recording"] = True
      fio.write_pickle(
          pkl, LOG_DIRECTORY + "/plugins/beholder/config.pkl"
      )
      for i in range(3):
          if i == 2:
              pkl = fio.read_pickle(
                  LOG_DIRECTORY + "/plugins/beholder/config.pkl"
              )
              pkl["is_recording"] = False
              fio.write_pickle(
                  pkl, LOG_DIRECTORY + "/plugins/beholder/config.pkl"
              )
          beholder.update(
              trainable=fake_param,
              arrays=arrays,
              frame=np.random.randn(128, 128),
          )
  
file_path: pytorch-tensorboardx/tests/test_beholder.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import unittest
  import tensorboardX.beholder
  import tensorboardX.beholder.file_system_tools
  import tempfile
  from collections import namedtuple
  import shutil
label_desc: Use image node_id 4 for calling the BeholderTest obj's underlying member method code with example usage: obj.test_beholder_video() without return types