Hi,
This would not be correct. Because in my understanding, what Spatial Separable Conv does is that for e.g.
In the forward pass, there is a 3x3 kernel, then, it would break the kernel into two parts, say, (3x1) and (1x3), and then the convolution process would go on, as usual, 1st (3x1) and then (1x3). Now, in the backward pass, the model should give us a (3x3) kernel, which was our original kernel_size which then should be breakable into a (3x1) and (1x3) kernel.
This is my understanding. It might be I am wrong.
Thanks.