I am wondering if there is a way to confirm that my TF model is training on my GPU after I stored the training data on it as advised in the TF tutorial. Here is a short code example:

```py
import tensorflow as tf

print('Num GPUs Available:', len(tf.config.experimental.list_physical_devices('GPU')))

# load data on GPU
with tf.device('/GPU:0'):
    mnist = tf.keras.datasets.mnist
    (x_train, y_train), (x_test, y_test) = mnist.load_data()
    x_train, x_test = x_train / 255.0, x_test / 255.0
# define, compile and train the model
model = tf.keras.models.Sequential([tf.keras.layers.Dense(1)])
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['acc'])
model.fit(x_train, y_train, batch_size=32, epochs=5)

```