K.gradients: NotImplementedError

[namp]

OK, I'm looking at the mxnet_backend.py and especially on how gradients are calculated since I'm developing a custom optimizer. However K.gradients do not implement any kind of call to mx:

def gradients(loss, variables):
    """Returns the gradients of `variables` (list of tensor variables)
    with regard to `loss`.
    """
    raise NotImplementedError

So my question is, how are gradients actually calculated, say in a call like:

grads=K.gradients(loss, params)

in my optimizer?

I mean, how the heck does even SGD work with the mx backend?

Thanks