Tensorflow2 dropout

# tf.keras.models.Sequential()model = keras.models.Sequential()model.add(keras.layers.Flatten(input_shape=[28, 28]))for _ in range(20):    model.add(keras.layers.Dense(100, activation="selu"))model.add(keras.layers.AlphaDropout(rate=0.5))# AlphaDropout: 1. 均值和方差不变 2. 归一化性质也不变# model.add(keras.layers.Dropout(rate=0.5))model.add(keras.layers.Dense(10, activation="softmax"))model.compile(loss="sparse_categorical_crossentropy",              optimizer = "sgd",              metrics = ["accuracy"])通常在最后几层使用dropout来防止过拟合