code: def cross(
      x1: torch.Tensor,
      x2: torch.Tensor,
      /,
      *,
      axisa: int = -1,
      axisb: int = -1,
      axisc: int = -1,
      axis: Optional[int] = None,
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      if axis is None:
          axis = -1
      x1, x2 = ivy.promote_types_of_inputs(x1, x2)
  
      if axis is not None:
          return torch.linalg.cross(input=x1, other=x2, dim=axis)
      x1 = torch.transpose(x1, axisa, 1)
      x2 = torch.transpose(x2, axisb, 1)
      return torch.transpose(
          torch.linalg.cross(input=x1, other=x2, out=out),
          dim0=axisc,
          dim1=1,
      )
  
imports: import torch
  from typing import Union, Optional, Tuple, Literal, List, NamedTuple, Sequence
  from collections import namedtuple
  import ivy
  from ivy import inf
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from .None import backend_version
  from .elementwise import _cast_for_unary_op
label_desc: Use image node_id 2 for calling a global function with example usage: cross() and returns: torch, torch