def get_lr_scalers(self):
        rval = OrderedDict()

        params = self.get_params()

        for layer in self.hidden_layers + [self.visible_layer]:
            contrib = layer.get_lr_scalers()

            # No two layers can contend to scale a parameter
            assert not any([key in rval for key in contrib])
            # Don't try to scale anything that's not a parameter
            assert all([key in params for key in contrib])

            rval.update(contrib)
        assert all([isinstance(val, float) for val in rval.values()])

        return rval
Set the intelligence for this actor to an ephemeral L{IEventObserver}.
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/models/dbm/dbm.py/DBM.get_lr_scalers--crossover with--dataset/ETHPy150Open twisted/imaginary/imaginary/iimaginary.py/IActor.setEphemeralIntelligence