nn.py 文件源码

def get_objective(l1=0, l2=0.005):
    def objective(layers, loss_function, target, aggregate=aggregate,
                  deterministic=False, get_output_kw=None):
        if get_output_kw is None:
            get_output_kw = {}
        output_layer = layers[-1]
        first_layer = layers[1]
        network_output = lasagne.layers.get_output(
            output_layer, deterministic=deterministic, **get_output_kw)
        if not deterministic:
            losses = loss_function(network_output, target) \
                    + l2 * regularization.regularize_network_params(
                        output_layer, regularization.l2) \
                    + l1 * regularization.regularize_layer_params(
                        output_layer, regularization.l1)
        else:
            losses = loss_function(network_output, target)
        return aggregate(losses)
    return objective