如何让Tensorflow使用多路GPU

import tensorflow as tf
from tensorflow.keras import layers

strategy = tf.distribute.MirroredStrategy()

with strategy.scope():
    model = tf.keras.Sequential([
        layers.Dense(64, activation='relu', input_shape=(784,)),
        layers.Dense(64, activation='relu'),
        layers.Dense(10, activation='softmax')
    ])
    model.compile(loss='categorical_crossentropy',
                  optimizer=tf.keras.optimizers.Adam(),
                  metrics=['accuracy'])

(train_images, train_labels), (test_images, test_labels) = tf.keras.datasets.mnist.load_data()

train_dataset = tf.data.Dataset.from_tensor_slices((train_images, train_labels)).batch(64)
test_dataset = tf.data.Dataset.from_tensor_slices((test_images, test_labels)).batch(64)

model.fit(train_dataset, epochs=10)