message: Point out gotcha when using batch_normalization
diff: @@ -673,9 +673,16 @@ def batch_normalization(inputs,
  Note: when training, the moving_mean and moving_variance need to be updated.
  By default the update ops are placed in `tf.GraphKeys.UPDATE_OPS`, so they
  - need to be added as a dependency to the `train_op`. For example:
  + need to be added as a dependency to the `train_op`. Also, be sure to add
  + any batch_normalization ops before getting the update_ops collection.
  + Otherwise, update_ops will be empty, and training/inference will not work
  + properly. For example:
  ```python
  + x_norm = tf.layers.batch_normalization(x, training=training)
  +
  + # ...
  +
  update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS)
  with tf.control_dependencies(update_ops):
  train_op = optimizer.minimize(loss)
  