unimodal.py 文件源码

def extract_encoder(dbn):
    dbn_layers = dbn.get_all_layers()
    encoder = NeuralNet(
        layers=[
            (InputLayer, {'name': 'input', 'shape': dbn_layers[0].shape}),
            (DenseLayer, {'name': 'l1', 'num_units': dbn_layers[1].num_units, 'nonlinearity': sigmoid,
                          'W': dbn_layers[1].W, 'b': dbn_layers[1].b}),
            (DenseLayer, {'name': 'l2', 'num_units': dbn_layers[2].num_units, 'nonlinearity': sigmoid,
                          'W': dbn_layers[2].W, 'b': dbn_layers[2].b}),
            (DenseLayer, {'name': 'l3', 'num_units': dbn_layers[3].num_units, 'nonlinearity': sigmoid,
                          'W': dbn_layers[3].W, 'b': dbn_layers[3].b}),
            (DenseLayer, {'name': 'l4', 'num_units': dbn_layers[4].num_units, 'nonlinearity': linear,
                          'W': dbn_layers[4].W, 'b': dbn_layers[4].b}),
        ],
        update=adadelta,
        update_learning_rate=0.01,
        objective_l2=0.005,
        verbose=1,
        regression=True
    )
    encoder.initialize()
    return encoder