code: def image_summary(seqs, name, num=None):
      """Visualizes sequences as TensorBoard summaries.
  
      Args:
        seqs: A tensor of shape [n, t, h, w, c].
        name: String name of this summary.
        num: Integer for the number of examples to visualize. Defaults to
          all examples.
      """
      seqs = tf1.clip_by_value(seqs, 0.0, 1.0)
      seqs = tf1.unstack(seqs[:num])
      joined_seqs = [tf1.concat(tf1.unstack(seq), 1) for seq in seqs]
      joined_seqs = tf1.expand_dims(tf1.concat(joined_seqs, 0), 0)
      tf.summary.image(
          name,
          joined_seqs,
          max_outputs=1,
          step=tf1.train.get_or_create_global_step(),
      )
  
imports: from datetime import datetime
  import functools
  from absl import app
  from absl import flags
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  import tensorflow_probability
  from tensorflow_probability.examples import sprites_dataset
  from tensorflow_probability.python.internal import tf_keras
label_desc: Use image node_id 1 for calling a global function with example usage: image_summary(seqs, name, num) without return types