code: def expand_dims(
      x: paddle.Tensor,
      /,
      *,
      copy: Optional[bool] = None,
      axis: Union[int, Sequence[int]] = 0,
      out: Optional[paddle.Tensor] = None,
  ) -> paddle.Tensor:
      out_shape = _calculate_out_shape(axis, x.shape)
      if 0 in x.shape:
          return paddle.empty(out_shape, dtype=x.dtype)
      # reshape since unsqueeze sets a maximum limit of dimensions
      return x.reshape(out_shape)
  
imports: from numbers import Number
  from typing import Union, Optional, Tuple, List, Sequence, Iterable
  import math
  import paddle
  import ivy
  import ivy.functional.backends.paddle
  from ivy.func_wrapper import with_unsupported_device_and_dtypes, with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
  from ...ivy.manipulation import _calculate_out_shape
label_desc: Use image node_id 2 for calling a global function with example usage: expand_dims() and returns: x, paddle