message: With distribution strategy `steps=` is required for keras model's `evaluate` and `predict` otherwise the functions error.
  Also without importing tf and keras from tf the example also errors, so this is the minimal set of edits to actually make the example work.
diff: @@ -46,6 +46,9 @@ Let's see how to scale to multiple GPUs on one machine using `MirroredStrategy`
  Take a very simple model consisting of a single layer:
  ```python
  +import tensorflow as tf
  +from tensorflow import keras
  +
  inputs = tf.keras.layers.Input(shape=(1,))
  predictions = tf.keras.layers.Dense(1)(inputs)
  model = tf.keras.models.Model(inputs=inputs, outputs=predictions)
  @@ -90,8 +93,8 @@ Similarly, we can also call `evaluate` and `predict` as before using appropriate
  datasets.
  ```python
  -model.evaluate(eval_dataset)
  -model.predict(predict_dataset)
  +model.evaluate(eval_dataset, steps=1)
  +model.predict(predict_dataset, steps=1)
  ```
  That's all you need to train your model with Keras on multiple GPUs with
  