tensorflow2.0导入variance_scaling_initializer

在 TensorFlow 2.0 中，可以使用以下代码导入 `variance_scaling_initializer`：

from tensorflow.keras.initializers import VarianceScaling

然后，可以将其作为参数传递给模型的某些层或参数初始化器：

model.add(Dense(10, activation='relu', kernel_initializer=VarianceScaling(scale=2.0)))

或者在自定义层中使用：

class MyLayer(layers.Layer):
    def __init__(self, units, activation=None, **kwargs):
        super().__init__(**kwargs)
        self.units = units
        self.activation = activations.get(activation)
        self.kernel_initializer = VarianceScaling(scale=2.0)

    def build(self, input_shape):
        self.kernel = self.add_weight(
            shape=(input_shape[-1], self.units),
            initializer=self.kernel_initializer,
            name='kernel',
            trainable=True)
        super().build(input_shape)

    def call(self, inputs):
        output = tf.matmul(inputs, self.kernel)
        if self.activation is not None:
            output = self.activation(output)
        return output