code: def stack(tensors, new_dim, dim=0, out=None):
      if isinstance(dim, int):
          return torch.stack(tensors, dim, out).index(dim, new_dim)
      index = None
      if out is not None:
          out, index = _positional_no_permute(out, dim, expand_dim=True)
      ptensors = []
      for t in tensors:
          pt, pi = _positional_no_permute(t, dim, expand_dim=True)
          if index is not None and pi != index:
              pt = pt.move_dim(pi, index)
          else:
              index = pi
          ptensors.append(pt)
      pr = torch.stack(ptensors, index, out=out)
      return pr.index((index, index + 1), (new_dim, dim))
  
imports: import torch
  from functorch._C import dim
  from .None import op_properties
  from .batch_tensor import _enable_layers
  from .tree_map import tree_flatten, tree_map
  import operator
  from functools import reduce
label_desc: Use image node_id 18 for calling a global function with example usage: stack(tensors, new_dim, dim, out) and returns: pr, torch