They shoud be None before the first backward pass. If they become 0 after that first backward pass, that means that gradient were propagated.
You will need to check your function but it is quite easy to write functions that have a gradient of 0. If you do step functions for example.
One thing you can use is some_tensor.register_hook() that you can use to get the gradient for any Tensor in your model.
If you use given it the print function, it will print that gradient. If you need something more fancy you can use:
def my_hook(grad):
    print("Gradient for some_tensor")
    print(grad)