I want to perform a convolution over an image, in tensorflow. I want the kernel to be as tall as the image and very thin. For example: 

```
kernel_size = [200, 24]
image_size = [200, 400]

```

If I use padding "SAME", instead of getting a vector out, I get a [200, 400] image back, since tensorflow pads the image at the top and bottom and convolves with the kernel over the padded image.

If, on the other hand, I use padding "VALID", the problem for the top and bottom disappears, but it also does not fully cover the horizontal direction of my image, such that, if the horizontal dimension of the image is not divisible by the kernel dimension, you lose a part of it. 

Is there a way to perform "VALID" padding at the top and bottom and "SAME" padding left and right? Or is there another way of doing this?