如何在Kaggle Notebook的图形处理器上运行Tensorflow的Keras model.fit()函数？

import tensorflow as tf
from tensorflow import keras

print(tf.config.list_physical_devices('GPU'))

model = keras.Sequential([...])  # 构建您的模型
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])  # 编译模型

(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()  # 加载MNIST数据集
x_train = x_train.reshape(-1, 28, 28, 1).astype('float32') / 255.0  # 数据预处理
x_test = x_test.reshape(-1, 28, 28, 1).astype('float32') / 255.0

train_dataset = tf.data.Dataset.from_tensor_slices((x_train, y_train)).shuffle(10000).batch(64)
test_dataset = tf.data.Dataset.from_tensor_slices((x_test, y_test)).batch(64)

model.fit(train_dataset, epochs=10, validation_data=test_dataset)