code: def flip(
      x: torch.Tensor,
      /,
      *,
      copy: Optional[bool] = None,
      axis: Optional[Union[int, Sequence[int]]] = None,
      out: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      if copy:
          x = x.clone().detach()
      num_dims = len(x.shape)
      if not num_dims:
          return x
      if axis is None:
          new_axis = list(range(num_dims))
      else:
          new_axis = axis
      if isinstance(new_axis, int):
          new_axis = [new_axis]
      else:
          new_axis = new_axis
      new_axis = [
          item + num_dims if item < 0 else item for item in new_axis
      ]
      return torch.flip(x, new_axis)
  
imports: import math
  from numbers import Number
  from typing import Union, Optional, Tuple, List, Sequence, Iterable
  import torch
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes
  from ivy.functional.ivy.manipulation import _calculate_out_shape
  from .None import backend_version
label_desc: Use image node_id 4 for calling a global function with example usage: flip() and returns: torch, x