Should the depth on convolutional layers be set to a figure divisible by 2?
You are right, the way it says it, it means that the height and width should be divisible by 2.

While the argument he makes is invalid, it is a good practice for the sakes of memory efficiency to make some parameters like the batch size divisible by 2. I'm guessing you want to make more efficient use of memory blocks. The same logic could apply to the depth of convolutional layers.

This is no way as important as the author of the book says!