class_docstr: See function `stack_or_none`
code: def forward(ctx, dim: int, *tensors: torch.Tensor):
      ctx.dim = dim
      return _stack_or_none_fw(tensors, dim=dim)
  
file_path: xformers/xformers/ops/unbind.py
imports: from typing import List, Optional, Sequence, Tuple, Union
  import torch
  from .common import _get_storage_base
label_desc: Use image node_id 1 for calling the _StackOrNone obj's underlying member method code with example usage: obj.forward(ctx, dim) and returns: _stack_or_none_fw