you can get or set the weights:
def set_weights(m):
    classname = m.__class__.__name__
    if classname.find('Conv2d') != -1:
        print(m.weight.data)
        m.weight.data.normal_(0.0, 0.02)

# then
sequential_model = sequential_model.apply(set_weights)

but what exactly do you mean by ‘custom regularization’ you mean you’d like to apply some constraint to just those weights?
Is that a good idea? Maybe someone else could chime in? it may be worth trying to apply regularization to other non conv layers as well and see if it improves your model.