code: def gif_summary(
      name, tensor, max_outputs=3, fps=10, collections=None, family=None
  ):
      """Outputs a `Summary` protocol buffer with gif animations.
  
      Args:
        name: Name of the summary.
        tensor: A 5-D `uint8` `Tensor` of shape `[batch_size, time, height, width,
          channels]` where `channels` is 1 or 3.
        max_outputs: Max number of batch elements to generate gifs for.
        fps: frames per second of the animation
        collections: Optional list of tf.GraphKeys.  The collections to add the
          summary to.  Defaults to [tf.GraphKeys.SUMMARIES]
        family: Optional; if provided, used as the prefix of the summary tag name,
          which controls the tab name used for display on Tensorboard.
  
      Returns:
        A scalar `Tensor` of type `string`. The serialized `Summary` protocol
        buffer.
  
      Raises:
        ValueError: if the given tensor has the wrong shape.
      """
      tensor = tf.convert_to_tensor(tensor)
      if len(tensor.get_shape()) != 5:
          raise ValueError(
              "Assuming videos given as tensors in the format "
              "[batch, time, height, width, channels] but got one "
              "of shape: %s" % str(tensor.get_shape())
          )
      tensor = tf.cast(tensor, tf.uint8)
      if distribute_summary_op_util.skip_summary():
          return tf.constant("")
      with summary_op_util.summary_scope(
          name, family, values=[tensor]
      ) as (tag, scope):
          val = tf.py_func(
              py_gif_summary,
              [tag, tensor, max_outputs, fps],
              tf.string,
              stateful=False,
              name=scope,
          )
          summary_op_util.collect(
              val, collections, [tf.GraphKeys.SUMMARIES]
          )
      return val
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  from tensor2tensor.layers import common_layers
  from tensor2tensor.utils import contrib
  import tensorflow.compat.v1
  from tensorflow.python.ops import summary_op_util
label_desc: Use image node_id 17 for calling a global function with example usage: gif_summary(name, tensor, max_outputs, fps, collections, family) and returns: val, tf