STConvolution.py 文件源码

def seqCNN_LReLU(n_flow=4, seq_len=3, map_height=32, map_width=32):
    model=Sequential()
    model.add(Convolution2D(64, 3, 3, input_shape=(n_flow*seq_len, map_height, map_width), border_mode='same'))
    model.add(LeakyReLU(0.2))
    # model.add(BatchNormalization())

    model.add(Convolution2D(128, 3, 3, border_mode='same'))
    model.add(LeakyReLU(0.2))
    # model.add(BatchNormalization())

    model.add(Convolution2D(64, 3, 3, border_mode='same'))
    model.add(LeakyReLU(0.2))
    # model.add(BatchNormalization())

    model.add(Convolution2D(n_flow, 3, 3, border_mode='same'))
    model.add(Activation('tanh'))
    return model