code: def testConvertPredictionsToVideoSummaries(
      self, num_decodes=5, max_output_steps=5
  ):
      # Initialize predictions.
      rng = np.random.RandomState(0)
      inputs = rng.randint(0, 255, (2, 32, 32, 3))
      outputs = rng.randint(0, 255, (max_output_steps, 32, 32, 3))
      targets = rng.randint(0, 255, (5, 32, 32, 3))
  
      # batch it up.
      prediction = [
          {"outputs": outputs, "inputs": inputs, "targets": targets}
      ] * 5
      predictions = [prediction] * num_decodes
      decode_hparams = decoding.decode_hparams(
          overrides="max_display_decodes=5"
      )
  
      decode_hooks = decoding.DecodeHookArgs(
          estimator=None,
          problem=None,
          output_dirs=None,
          hparams=decode_hparams,
          decode_hparams=decode_hparams,
          predictions=predictions,
      )
      summaries = video_utils.display_video_hooks(decode_hooks)
  
      for summary in summaries:
          self.assertIsInstance(summary, tf.Summary.Value)
  
file_path: tensor2tensor/tensor2tensor/data_generators/video_utils_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  from tensor2tensor.data_generators import video_generated
  from tensor2tensor.data_generators import video_utils
  from tensor2tensor.utils import decoding
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
label_desc: Use image node_id 4 for calling the VideoUtilsTest obj's underlying member method code with example usage: obj.testConvertPredictionsToVideoSummaries(num_decodes, max_output_steps) without return types