class_docstr: Concatenate multiple tensors along third axis (depth wise).
code: def forward(self, xs):
      xp = backend.get_array_module(*xs)
      return (xp.dstack(xs),)
  
file_path: chainer/chainer/functions/array/dstack.py
imports: import numpy
  import six
  import chainer
  from chainer import backend
  from chainer import function_node
  from chainer.utils import type_check
label_desc: Use image node_id 2 for calling the Dstack obj's underlying member method code with example usage: obj.forward(xs) and returns: xp