hintbot.py 文件源码

def createModel(w=None,h=None):
    # Input placeholder
    original = Input(shape=(w, h, 4), name='icon_goes_here')

    # Model layer stack
    x = original
    x = Convolution2D(64, 4, 4, activation='relu', border_mode='same', b_regularizer=l2(0.1))(x)
    x = Convolution2D(64, 4, 4, activation='relu', border_mode='same', b_regularizer=l2(0.1))(x)
    x = Convolution2D(64, 4, 4, activation='relu', border_mode='same', b_regularizer=l2(0.1))(x)
    x = Convolution2D(64, 4, 4, activation='relu', border_mode='same', b_regularizer=l2(0.1))(x)
    x = AveragePooling2D((2, 2), border_mode='valid')(x)
    x = Convolution2D(16, 4, 4, activation='relu', border_mode='same', b_regularizer=l2(0.1))(x)
    x = Convolution2D(4, 4, 4, activation='relu', border_mode='same',  b_regularizer=l2(0.1))(x)
    downscaled = x

    # Compile model
    hintbot = Model(input=original, output=downscaled)
    hintbot.compile(optimizer='adam', loss='mean_squared_error')
    # Train
    if (os.path.isfile(load_weights_filepath)):
        hintbot.load_weights(load_weights_filepath)
    return hintbot