message: Update tf.distribute overview doc page
diff: @@ -63,7 +63,7 @@ the same way with eager and graph execution.
  each replica are aggregated together before updating the model variables. This
  is in contrast to _asynchronous_, or _async_ training, where each replica
  updates the model variables independently. You may also have replicas
  - partitioned into gropus which are in sync within each group but async between
  + partitioned into groups which are in sync within each group but async between
  groups.
  * _Parameter servers_: These are machines that hold a single copy of
  parameters/variables, used by some strategies (right now just
  