message: Doc updates for distribute_coordinator.py
diff: @@ -648,7 +648,7 @@ def run_distribute_coordinator(worker_fn,
  for a task. The distribute coordinator will make a copy of the `strategy`
  object, call its `configure` method and pass it to `worker_fn` as an argument.
  - The `worker_fn` defines the training logic and is called under a its own
  + The `worker_fn` defines the training logic and is called under its own
  worker context which can be accessed to via `get_current_worker_context`. A
  worker context provides access to configurations for each task, e.g. the
  task_type, task_id, master target and so on. Since `worker_fn` will be called
  @@ -674,7 +674,7 @@ def run_distribute_coordinator(worker_fn,
  the worker context.
  The `cluster_spec` can be either passed by the argument or parsed from the
  - "TF_CONFIG" envrionment variable. Example of a TF_CONFIG:
  + "TF_CONFIG" environment variable. Example of a TF_CONFIG:
  ```
  cluster = {'chief': ['host0:2222'],
  'ps': ['host1:2222', 'host2:2222'],
  @@ -689,19 +689,19 @@ def run_distribute_coordinator(worker_fn,
  will be created to call `eval_fn` with its `task_type` set to "evaluator". If
  `eval_fn` is not defined, fall back to `worker_fn`. This implies that
  evaluation will be done on a single machine if there is an "evaluator" task.
  - If "evaluator" doesn't exit in the cluster_spec, it entirely depends on the
  + If "evaluator" doesn't exist in the cluster_spec, it entirely depends on the
  `worker_fn` for how to do evaluation.
  Args:
  worker_fn: the function to be called. The function should accept a
  `strategy` object and will be given access to a context object via a
  context manager scope.
  - strategy: a DistributionStrategy object which specifying whether it should
  + strategy: a DistributionStrategy object specifying whether it should
  run between-graph replicated training or not, whether to run init ops,
  etc. This object will also be configured given `session_config`,
  `cluster_spec`, `task_type` and `task_id`.
  eval_fn: optional function for "evaluator" task. If `eval_fn` is not passed
  - in but a "evaluator" task found in the `cluster_spec`, the `worker_fn`
  + in but a "evaluator" task is found in the `cluster_spec`, the `worker_fn`
  will be used for this task.
  eval_strategy: optional DistributionStrategy object for "evaluator" task.
  mode: in which mode this distribute coordinator runs.
  @@ -736,7 +736,7 @@ def run_distribute_coordinator(worker_fn,
  rpc_layer = tf_config.get("rpc_layer", rpc_layer)
  environment = tf_config.get("environment", None)
  - # Setting the session config is necessary for some strategies such
  + # Setting the session config is necessary for some strategies such as
  # CollectiveAllReduceStrategy.
  session_config = session_config or config_pb2.ConfigProto(
  allow_soft_placement=True)
  