message: Add quick doc for tf.keras.estimator.model_to_estimator.
diff: @@ -151,3 +151,26 @@ We recommend the following workflow:
  best results.
  4. Possibly, further improve your model by building your own custom Estimator.
  +
  +## Creating Estimators from Keras models
  +
  +You can convert existing Keras models to Estimators. Doing so enables your Keras
  +model to access Estimator's strengths, such as distributed training. Call
  +@{tf.keras.estimator.model_to_estimator} as in the
  +following sample:
  +
  +```python
  +# Instantiate a Keras inception v3 model.
  +keras_inception_v3 = tf.keras.applications.inception_v3.InceptionV3(weights=None)
  +# Compile model with the optimizer, loss, and metrics you'd like to train with.
  +keras_inception_v3.compile(optimizer=tf.keras.optimizers.SGD(lr=0.0001, momentum=0.9),
  + loss='categorical_crossentropy',
  + metric='accuracy')
  +# Create an Estimator from the compiled Keras model.
  +est_inception_v3 = tf.keras.estimator.model_to_estimator(keras_model=keras_inception_v3)
  +# Treat the derived Estimator as you would any other Estimator. For example,
  +# the following derived Estimator calls the train method:
  +est_inception_v3.train(input_fn=my_training_set, steps=2000)
  +```
  +For more details, please refer to the documentation for
  +@{tf.keras.estimator.model_to_estimator}.
  