convolutional_neural_network.py 文件源码

def CNN(n_epochs):
    net1 = NeuralNet(
        layers=[
            ('input', layers.InputLayer),
            ('conv1', layers.Conv2DLayer),  # Convolutional layer.  Params defined below
            ('pool1', layers.MaxPool2DLayer),  # Like downsampling, for execution speed
            ('conv2', layers.Conv2DLayer),
            ('hidden3', layers.DenseLayer),
            ('output', layers.DenseLayer),
        ],

        input_shape=(None, 1, 6, 5),
        conv1_num_filters=8,
        conv1_filter_size=(3, 3),
        conv1_nonlinearity=lasagne.nonlinearities.rectify,

        pool1_pool_size=(2, 2),

        conv2_num_filters=12,
        conv2_filter_size=(1, 1),
        conv2_nonlinearity=lasagne.nonlinearities.rectify,

        hidden3_num_units=1000,
        output_num_units=2,
        output_nonlinearity=lasagne.nonlinearities.softmax,

        update_learning_rate=0.0001,
        update_momentum=0.9,

        max_epochs=n_epochs,
        verbose=0,
    )
    return net1