diff --git a/docs/keras_example.ipynb b/docs/keras_example.ipynb index 90d6dad1733..af5ca2b0178 100644 --- a/docs/keras_example.ipynb +++ b/docs/keras_example.ipynb @@ -130,11 +130,11 @@ " return tf.cast(image, tf.float32) / 255., label\n", "\n", "ds_train = ds_train.map(\n", - " normalize_img, num_parallel_calls=tf.data.experimental.AUTOTUNE)\n", + " normalize_img, num_parallel_calls=tf.data.AUTOTUNE)\n", "ds_train = ds_train.cache()\n", "ds_train = ds_train.shuffle(ds_info.splits['train'].num_examples)\n", "ds_train = ds_train.batch(128)\n", - "ds_train = ds_train.prefetch(tf.data.experimental.AUTOTUNE)" + "ds_train = ds_train.prefetch(tf.data.AUTOTUNE)" ] }, { @@ -160,10 +160,10 @@ "outputs": [], "source": [ "ds_test = ds_test.map(\n", - " normalize_img, num_parallel_calls=tf.data.experimental.AUTOTUNE)\n", + " normalize_img, num_parallel_calls=tf.data.AUTOTUNE)\n", "ds_test = ds_test.batch(128)\n", "ds_test = ds_test.cache()\n", - "ds_test = ds_test.prefetch(tf.data.experimental.AUTOTUNE)" + "ds_test = ds_test.prefetch(tf.data.AUTOTUNE)" ] }, {