code: def tile_batch(
      t: TensorLike, multiplier: int, name: Optional[str] = None
  ) -> tf.Tensor:
      """Tiles the batch dimension of a (possibly nested structure of) tensor(s).
  
      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:
        t: `Tensor` shaped `[batch_size, ...]`.
        multiplier: Python int.
        name: Name scope for any created operations.
  
      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.
      """
      with tf.name_scope(name or "tile_batch"):
          return tf.nest.map_structure(
              lambda t_: _tile_batch(t_, multiplier), t
          )
  
imports: import collections
  import numpy
  import tensorflow
  from tensorflow_addons import options
  from tensorflow_addons.seq2seq import attention_wrapper
  from tensorflow_addons.seq2seq import decoder
  from tensorflow_addons.utils import keras_utils
  from tensorflow_addons.utils.resource_loader import LazySO
  from tensorflow_addons.utils.types import FloatTensorLike, TensorLike, Number
  from typeguard import typechecked
  from typing import Callable, Optional
label_desc: Use image node_id 2 for calling a global function with example usage: tile_batch(t, multiplier, name) and returns: tf