code: def _tile_batch(t, multiplier, ensure_shape=True):
      """Core single-tensor implementation of tile_batch."""
      t = tf.convert_to_tensor(t, name="t")
      shape_t = tf.shape(t)
      if t.shape.ndims is None or t.shape.ndims < 1:
          raise ValueError("t must have statically known rank")
      tiling = [1] * (t.shape.ndims + 1)
      tiling[1] = multiplier
      num_batch_dims = tf.compat.dimension_value(t.shape.dims[0])
      tiled_static_batch_size = (
          num_batch_dims * multiplier
          if num_batch_dims is not None
          else None
      )
      tiled = tf.tile(tf.expand_dims(t, 1), tiling)
      tiled = tf.reshape(
          tiled, tf.concat(([shape_t[0] * multiplier], shape_t[1:]), 0)
      )
  
      if ensure_shape:
          tiled = tf.ensure_shape(
              tiled,
              tf.TensorShape([tiled_static_batch_size]).concatenate(
                  t.shape[1:]
              ),
          )
      return tiled
  
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 34 for calling a global function with example usage: _tile_batch(t, multiplier, ensure_shape) and returns: tiled