我在网上尝试了很多教程，但都不管用，mnist数据集只能用tf.keras.datasets.mnist.load_data

(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data(datapath)
model = keras.models.Sequential([
    layers.Conv2D(filters=16, kernel_size=(5,5), padding='same',
                 input_shape=(28,28,1),  activation='relu'),
    layers.MaxPooling2D(pool_size=(2, 2)),
    layers.Conv2D(filters=36, kernel_size=(5,5), padding='same',
                 activation='relu'),
    layers.MaxPooling2D(pool_size=(2, 2)),
    layers.Dropout(0.25),
    layers.Flatten(),
    layers.Dense(128, activation='relu'),
    layers.Dropout(0.5),
    layers.Dense(10,activation='softmax')
])
model.fit(x=x_train, y=y_train, validation_split=0.2, 
                        epochs=30, batch_size=128, verbose=1)

但我怎么能得到这些：(x_train, y_train), (x_test, y_test)从tfrecord文件中删除吗？
我是个新手，希望你能帮我。