# Stride in convolutional neural networks (horizontal/vertical direction)?

I feel like this question has been asked before, but I can't seem to find any old material on this.

In the convolutional layer for CNNs, when you specify the stride of a filter, typical notes show some examples of this but only for the horizontal panning. Is this same stride applied for the vertical direction too when you're done with the current row?

In other words, say our input volume is 7x7, and we apply a stride of 1 for a 3x3 filter. Is the output volume 5x5? (which would mean you applied the stride in both the horizontal and vertical panning).

Is it possible to apply a different stride for each direction?

In Pytorch, too you can specify the values in a tuple for the stride argument. Link to Pytorch Documentation for stride