fr3dnet.py 文件源码

def define_network(inputs):

    network = lasagne.layers.InputLayer(shape=(None, params.CHANNELS, params.INPUT_SIZE, params.INPUT_SIZE, params.INPUT_SIZE),
                                input_var=inputs)

    network = Conv3DDNNLayer(
            network, num_filters=64, filter_size=(5, 5, 5),
            nonlinearity=lasagne.nonlinearities.leaky_rectify,
            W=HeNormal(gain='relu'))

    network = MaxPool3DDNNLayer(network, pool_size=(2, 2, 2))

    if params.BATCH_NORMALIZATION:
        network = lasagne.layers.batch_norm(network)

    network = Conv3DDNNLayer(
            network, num_filters=64, filter_size=(5, 5, 5),
            nonlinearity=lasagne.nonlinearities.leaky_rectify,
            W=HeNormal(gain='relu'))

    network = Conv3DDNNLayer(
            network, num_filters=96, filter_size=(5, 5, 5),
            nonlinearity=lasagne.nonlinearities.leaky_rectify,
            W=HeNormal(gain='relu'))

    if params.BATCH_NORMALIZATION:
        network = lasagne.layers.batch_norm(network)

    network = lasagne.layers.DenseLayer(
            network,
            num_units=420,
            nonlinearity=lasagne.nonlinearities.leaky_rectify,
            W=HeNormal(gain='relu')
    )

    network = lasagne.layers.DenseLayer(
            network, num_units=params.N_CLASSES,
            nonlinearity=lasagne.nonlinearities.softmax)

    return network