message: Fix docstring formatting.
diff: @@ -295,6 +295,7 @@ def train_and_evaluate(estimator, train_spec, eval_spec):
  model will be trained with three epochs of training data instead of one epoch.
  Example of local (non-distributed) training:
  +
  ```python
  # Set up feature columns.
  categorial_feature_a = categorial_column_with_hash_bucket(...)
  @@ -339,12 +340,14 @@ def train_and_evaluate(estimator, train_spec, eval_spec):
  Setting environment variable depends on the platform. For example, on Linux,
  it can be done as follows (`$` is the shell prompt):
  +
  ```
  $ TF_CONFIG='<replace_with_real_content>' python train_model.py
  ```
  For the content in `TF_CONFIG`, assume that the training cluster spec looks
  like:
  +
  ```
  cluster = {"chief": ["host0:2222"],
  "worker": ["host1:2222", "host2:2222", "host3:2222"],
  @@ -352,6 +355,7 @@ def train_and_evaluate(estimator, train_spec, eval_spec):
  ```
  Example of `TF_CONFIG` for chief training worker (must have one and only one):
  +
  ```
  # This should be a JSON string, which is set as environment variable. Usually
  # the cluster manager handles that.
  @@ -371,6 +375,7 @@ def train_and_evaluate(estimator, train_spec, eval_spec):
  Example of `TF_CONFIG` for non-chief training worker (optional, could be
  multiple):
  +
  ```
  # This should be a JSON string, which is set as environment variable. Usually
  # the cluster manager handles that.
  @@ -387,6 +392,7 @@ def train_and_evaluate(estimator, train_spec, eval_spec):
  for non-chief training workers.
  Example of `TF_CONFIG` for parameter server, aka ps (could be multiple):
  +
  ```
  # This should be a JSON string, which is set as environment variable. Usually
  # the cluster manager handles that.
  @@ -405,6 +411,7 @@ def train_and_evaluate(estimator, train_spec, eval_spec):
  Example of `TF_CONFIG` for evaluator task. Evaluator is a special task that is
  not part of the training cluster. There could be only one. It is used for
  model evaluation.
  +
  ```
  # This should be a JSON string, which is set as environment variable. Usually
  # the cluster manager handles that.
  