Extend your get_deconv_filter from 2D to 3D. How?

[John1231983]

I want to extend your get_deconv_filter from 2D to 3D. In CAFFE, it can be implemented as

int f = ceil(blob->shape(-1) / 2.);
    float c = (2 * f - 1 - f % 2) / (2. * f);
    for (int i = 0; i < blob->count(); ++i) {
      float x = i % blob->shape(-1);
      float y = (i / blob->shape(-1)) % blob->shape(-2);
      float z = (i/(blob->shape(-1)*blob->shape(-2))) % blob->shape(-3);
      data[i] = (1 - fabs(x / f - c)) * (1 - fabs(y / f - c)) * (1-fabs(z / f - c));

So, the get_deconv_filter function will be changed as

def get_deconv_filter(self, f_shape):
        width = f_shape[0]
        heigh = f_shape[0]
        depth = f_shape[0]
        f = ceil(width/2.0)
        c = (2 * f - 1 - f % 2) / (2.0 * f)
        bilinear = np.zeros([f_shape[0], f_shape[1],f_shape[2]])
        for x in range(width):
            for y in range(heigh):
                for z in range(depth):
                      value = (1 - abs(x / f - c)) * (1 - abs(y / f - c))*(1 - abs(z / f - c))
                      bilinear[x, y, z] = value
        weights = np.zeros(f_shape)
        for i in range(f_shape[2]):
            weights[:, :, :, i, i] = bilinear

        init = tf.constant_initializer(value=weights,
                                       dtype=tf.float32)
        return tf.get_variable(name="up_filter", initializer=init,
                               shape=weights.shape)

Could you please look at my code and correct help me if it wrong? Thanks