code: def dstack(tup):
      """
      Stack arrays in sequence depth wise (along third axis).
  
      This is equivalent to concatenation along the third axis after 2-D arrays
      of shape `(M,N)` have been reshaped to `(M,N,1)` and 1-D arrays of shape
      `(N,)` have been reshaped to `(1,N,1)`. Rebuilds arrays divided by
      `dsplit`.
  
      This function makes most sense for arrays with up to 3 dimensions. For
      instance, for pixel-data with a height (first axis), width (second axis),
      and r/g/b channels (third axis). The functions `concatenate`, `stack` and
      `block` provide more general stacking and concatenation operations.
  
      Parameters
      ----------
      tup : sequence of arrays
          The arrays must have the same shape along all but the third axis.
          1-D or 2-D arrays must have the same shape.
  
      Returns
      -------
      stacked : ndarray
          The array formed by stacking the given arrays, will be at least 3-D.
  
      See Also
      --------
      concatenate : Join a sequence of arrays along an existing axis.
      stack : Join a sequence of arrays along a new axis.
      block : Assemble an nd-array from nested lists of blocks.
      vstack : Stack arrays in sequence vertically (row wise).
      hstack : Stack arrays in sequence horizontally (column wise).
      column_stack : Stack 1-D arrays as columns into a 2-D array.
      dsplit : Split array along third axis.
  
      Examples
      --------
      >>> a = np.array((1,2,3))
      >>> b = np.array((2,3,4))
      >>> np.dstack((a,b))
      array([[[1, 2],
              [2, 3],
              [3, 4]]])
  
      >>> a = np.array([[1],[2],[3]])
      >>> b = np.array([[2],[3],[4]])
      >>> np.dstack((a,b))
      array([[[1, 2]],
             [[2, 3]],
             [[3, 4]]])
  
      """
      arrs = atleast_3d(*tup)
      if not isinstance(arrs, list):
          arrs = [arrs]
      return _nx.concatenate(arrs, 2)
  
imports: import functools
  import numpy.core.numeric
  from numpy.core.numeric import asarray, zeros, array, asanyarray
  from numpy.core.fromnumeric import reshape, transpose
  from numpy.core.multiarray import normalize_axis_index
  from numpy.core import overrides
  from numpy.core import vstack, atleast_3d
  from numpy.core.numeric import normalize_axis_tuple
  from numpy.core.shape_base import _arrays_for_stack_dispatcher
  from numpy.lib.index_tricks import ndindex
  from numpy.matrixlib.defmatrix import matrix
label_desc: Use image node_id 15 for calling a global function with example usage: dstack(tup) and returns: _nx