cnn_cascade_lasagne.py 文件源码

def __build_48_net__(self):
        network = layers.InputLayer((None, 3, 48, 48), input_var=self.__input_var__)

        network = layers.Conv2DLayer(network,num_filters=64,filter_size=(5,5),stride=1,nonlinearity=relu)
        network = layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2)        
        network = layers.batch_norm(network)

        network = layers.Conv2DLayer(network,num_filters=64,filter_size=(5,5),stride=1,nonlinearity=relu)
        network = layers.batch_norm(network)
        network = layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2)

        network = layers.Conv2DLayer(network,num_filters=64,filter_size=(3,3),stride=1,nonlinearity=relu)
        network = layers.batch_norm(network)
        network = layers.MaxPool2DLayer(network, pool_size = (3,3),stride = 2)

        network = layers.DenseLayer(network,num_units = 256,nonlinearity = relu)
        network = layers.DenseLayer(network,num_units = 2, nonlinearity = softmax)
        return network