If I understood the question correctly, you want to know more about 3 dimension in kernel size. So for one feature-map that you have, you will have several kernels. For example for your conv_2 layer, you have a kernel with h=3, w=3 and depth of 64 which the same as your feature-map depth. You slide this kernel on your feature-map and do the multiplications and create one feature layer for the feature-map in the next layer. You do this for kernel_number=64 times and create a feature-map of depth 64 for the next layer.