code: def tile_batch(tensors: types.NestedTensor, multiplier: types.Int):
      """Tile the batch dimension of a (possibly nested structure of) tensor(s).
  
      Copied from tensorflow/contrib/seq2seq/python/ops/beam_search_decoder.py
  
      For each tensor t in a (possibly nested structure) of tensors,
      this function takes a tensor t shaped `[batch_size, s0, s1, ...]` composed of
      minibatch entries `t[0], ..., t[batch_size - 1]` and tiles it to have a shape
      `[batch_size * multiplier, s0, s1, ...]` composed of minibatch entries
      `t[0], t[0], ..., t[1], t[1], ...` where each minibatch entry is repeated
      `multiplier` times.
  
      Args:
        tensors: A nested structure of `Tensor` shaped `[batch_size, ...]`.
        multiplier: Python int or a Tensor. Note that if the multiplier is a tensor
          the shape can not be ensured.
  
      Returns:
        A (possibly nested structure of) `Tensor` shaped
        `[batch_size * multiplier, ...]`.
  
      Raises:
        ValueError: if tensor(s) `t` do not have a statically known rank or
        the rank is < 1.
      """
      ensure_shape = False if tf.is_tensor(multiplier) else True
      return tf.nest.map_structure(
          lambda t: _tile_batch(
              t, multiplier, ensure_shape=ensure_shape
          ),
          tensors,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import numbers
  from typing import Optional, Text
  from absl import logging
  import numpy
  from six.moves import zip
  import tensorflow
  from tf_agents.typing import types
  from tf_agents.utils import composite
  import wrapt
  from tensorflow.python.util import nest
label_desc: Use image node_id 35 for calling a global function with example usage: tile_batch(tensors, multiplier) and returns: tf