def get_lr_scalers_from_layers(owner):
    rval = OrderedDict()

    params = owner.get_params()

    for layer in owner.layers:
        contrib = layer.get_lr_scalers()

        assert isinstance(contrib, OrderedDict)
        # 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
Get the learning rate scalers for all member layers of
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/models/mlp.py/get_lr_scalers_from_layers