., 7.]]), array([[ 8.,  9., 10., 11.],
           [12., 13., 14., 15.]])]
    >>> np.vsplit(x, np.array([3, 6]))
    [array([[ 0.,  1.,  2.,  3.],
           [ 4.,  5.,  6.,  7.],
           [ 8.,  9., 10., 11.]]), array([[12., 13., 14., 15.]]), array([], shape=(0, 4), dtype=float64)]

    With a higher dimensional array the split is still along the first axis.

    >>> x = np.arange(8.0).reshape(2, 2, 2)
    >>> x
    array([[[0.,  1.],
            [2.,  3.]],
           [[4.,  5.],
            [6.,  7.]]])
    >>> np.vsplit(x, 2)
    [array([[[0., 1.],
            [2., 3.]]]), array([[[4., 5.],
            [6., 7.]]])]

    r‚