example_gan_cifar10.py 文件源码

def model_discriminator():
    nch = 256
    h = 5
    reg = lambda: l1l2(l1=1e-7, l2=1e-7)

    c1 = Convolution2D(nch / 4, h, h, border_mode='same', W_regularizer=reg(),
                       input_shape=dim_ordering_shape((3, 32, 32)))
    c2 = Convolution2D(nch / 2, h, h, border_mode='same', W_regularizer=reg())
    c3 = Convolution2D(nch, h, h, border_mode='same', W_regularizer=reg())
    c4 = Convolution2D(1, h, h, border_mode='same', W_regularizer=reg())

    model = Sequential()
    model.add(c1)
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(LeakyReLU(0.2))
    model.add(c2)
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(LeakyReLU(0.2))
    model.add(c3)
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(LeakyReLU(0.2))
    model.add(c4)
    model.add(AveragePooling2D(pool_size=(4, 4), border_mode='valid'))
    model.add(Flatten())
    model.add(Activation('sigmoid'))
    return model