Tensorflow：3D卷积NN的对角线Subtensor

Question

Theano使用2D CNN变体的3D卷积神经网络（CNN）解决方法：

https://github.com/Theano/Theano/blob/master/theano/tensor/nnet/conv3d2d.py

它依赖于能够抓住矩阵的对角线并重塑它。来自上面的网站：

So the relevant part of `x` is some matrix `u`. Suppose it has 7 rows
and 4 columns::
    [ 0 0 0 0 ]
    [ 0 0 0 0 ]
    [ 0 0 0 0 ]
    [ 0 0 0 0 ]
    [ 0 0 0 0 ]
    [ 0 0 0 0 ]

The view returned by this function is also a matrix. It is a thick,
diagonal `stripe` across u that discards the lower left triangle
and the upper right triangle:
    [ x 0 0 0 ]
    [ x x 0 0 ]
    [ x x x 0 ]
    [ 0 x x x ]
    [ 0 0 x x ]
    [ 0 0 0 x ]

In this case the return value would be this view of shape 3x4. The
returned view has the same number of dimensions as the input
`x`, and the only difference is that the shape along dimension
`i0` has been reduced by `shape[i1] - 1` because of the
triangles that got chopped out.

这可以在Tensorflow中完成吗？这似乎是一个相对容易的任务，在处理3D数据类型时仍然可以使用绝大多数Tensorflow的CNN框架。