code: def expand(
      x: Union[tf.Tensor, tf.Variable],
      shape: Union[List[int], List[Tuple]],
      /,
      *,
      copy: Optional[bool] = None,
      out: Optional[Union[tf.Tensor, tf.Variable]] = None,
  ) -> Union[tf.Tensor, tf.Variable]:
      shape = list(shape)
      n_extra_dims = len(shape) - len(x.shape)
      if n_extra_dims > 0:
          new_shape = (1,) * n_extra_dims + tuple(x.shape)
          x = tf.reshape(x, new_shape)
      for i, dim in enumerate(shape):
          if dim < 0:
              shape[i] = x.shape[i]
      return tf.broadcast_to(x, shape)
  
imports: from collections import namedtuple
  from typing import Iterable, Union, Optional, Sequence, Tuple, NamedTuple, List, Literal, Callable, Any
  from numbers import Number
  import tensorflow
  from ivy.func_wrapper import with_unsupported_dtypes
  from ..None import backend_version
  import ivy
  from ivy.functional.ivy.experimental.manipulation import _to_tf_padding
label_desc: Use image node_id 21 for calling a global function with example usage: expand() and returns: tf