code: def pack_or_pad(
      dataset, length, pack=True, feature_keys=None, ensure_eos=False
  ):
      """Creates a 'packed' version of a dataset or pads examples with zeros.
  
      If pack=True, then multiple examples concatenated to form one combined
      example with the given length.
  
      If pack=False, then examples are padded with zeros to 'length'.
  
      Args:
        dataset: a tf.data.Dataset
        length: an integer or a dict from feature-key to integer
        pack: a boolean, whether to pack (True) or pad (False).
        feature_keys: (optional) collection of strings, the feature names to limit
          packing or padding to. Packing will filter out other features whereas
          padding will pass them through unchanged. Defaults to all features.
        ensure_eos: a boolean or collection of strings, whether to replace the final
          token with EOS=1 if it is not PAD=0. If True, will be applied to all keys
          in `feature_keys`. If False, will be applied to none. If a collection of
          strings, will only be applied to these features in the collection.
      Returns:
        a tf.data.Dataset where all features have fixed shape [length].
      """
      feature_keys = set(
          feature_keys or tf.data.get_output_shapes(dataset).keys()
      )
  
      if pack:
          dataset = pack_dataset(
              dataset, length=length, keys=feature_keys
          )
      # Pad/trim length of each example to length.
      dataset = trim_and_pad_dataset(
          dataset, length=length, feature_keys=feature_keys
      )
      if ensure_eos:
          eos_keys = (
              feature_keys
              if isinstance(ensure_eos, bool)
              else ensure_eos
          )
          dataset = ensure_dataset_eos(dataset, eos_keys)
  
      return dataset
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import os
  import gin
  import tensorflow.compat.v1
  import tensorflow_datasets
label_desc: Use image node_id 1 for calling a global function with example usage: pack_or_pad(dataset, length, pack, feature_keys, ensure_eos) and returns: dataset