Python keras.layers.core 模块，ActivityRegularization() 实例源码

我们从Python开源项目中，提取了以下4个代码示例，用于说明如何使用keras.layers.core.ActivityRegularization()。

项目：keras 作者：GeekLiB | 项目源码 | 文件源码

def test_activity_regularization():
    from keras.engine import Input, Model

    layer = core.ActivityRegularization(l1=0.01, l2=0.01)

    # test in functional API
    x = Input(shape=(3,))
    z = core.Dense(2)(x)
    y = layer(z)
    model = Model(input=x, output=y)
    model.compile('rmsprop', 'mse', mode='FAST_COMPILE')

    model.predict(np.random.random((2, 3)))

    # test serialization
    model_config = model.get_config()
    model = Model.from_config(model_config)
    model.compile('rmsprop', 'mse')

项目：keras-customized 作者：ambrite | 项目源码 | 文件源码

def test_activity_regularization():
    from keras.engine import Input, Model

    layer = core.ActivityRegularization(l1=0.01, l2=0.01)

    # test in functional API
    x = Input(shape=(3,))
    z = core.Dense(2)(x)
    y = layer(z)
    model = Model(input=x, output=y)
    model.compile('rmsprop', 'mse', mode='FAST_COMPILE')

    model.predict(np.random.random((2, 3)))

    # test serialization
    model_config = model.get_config()
    model = Model.from_config(model_config)
    model.compile('rmsprop', 'mse')

项目：keras 作者：NVIDIA | 项目源码 | 文件源码

def test_activity_regularization():
    from keras.engine import Input, Model

    layer = core.ActivityRegularization(l1=0.01, l2=0.01)

    # test in functional API
    x = Input(shape=(3,))
    z = core.Dense(2)(x)
    y = layer(z)
    model = Model(input=x, output=y)
    model.compile('rmsprop', 'mse', mode='FAST_COMPILE')

    model.predict(np.random.random((2, 3)))

    # test serialization
    model_config = model.get_config()
    model = Model.from_config(model_config)
    model.compile('rmsprop', 'mse')

项目：deep-coref 作者：clarkkev | 项目源码 | 文件源码

def test_act_reg(self):
        layer = core.ActivityRegularization(0.5, 0.5)
        self._runner(layer)