gans_1d_vonly.py 文件源码

def discriminator_model():
    model = Sequential()
    model.add(Convolution1D(
        12, 5,
        border_mode='same',
        input_shape=(INPUT_LN, 1)))
    model.add(Activation('relu'))
    model.add(MaxPooling1D(pool_length=N_GEN_l[0]))

    model.add(Convolution1D(12, 5, border_mode='same'))
    model.add(Activation('relu'))
    model.add(MaxPooling1D(pool_length=N_GEN_l[1]))

    #model.add(Reshape((128*7,)))
    model.add(Flatten())
    model.add(Dense(64))
    model.add(Activation('relu'))
    model.add(Dense(1))
    model.add(Activation('sigmoid'))
    return model