1 files changed, 16 insertions, 10 deletions
diff --git a/tensorflow/g3doc/api_docs/python/train.md b/tensorflow/g3doc/api_docs/python/train.md
index 0c2e2d5e60..6b6683d92e 100644
--- a/tensorflow/g3doc/api_docs/python/train.md
+++ b/tensorflow/g3doc/api_docs/python/train.md
@@ -3558,6 +3558,7 @@ inialize/restore.
 Session-like object that handles initialization, recovery and hooks.
 
 Example usage:
+
 ```python
 saver_hook = CheckpointSaverHook(...)
 summary_hook = SummaryHook(...)
@@ -3591,20 +3592,25 @@ Exit: At the `close()`, the monitored session does following things in order:
 
 * calls `hook.end()`
 * closes the queue runners and the session
-* surpresses `OutOfRange` error which indicates that all inputs have been
-  processed if the monitored_session is used as a context.
+* suppresses `OutOfRange` error which indicates that all inputs have been
+  processed if the monitored_session is used as a context
 
 How to set `tf.Session` arguments:
+
 * In most cases you can set session arguments as follows:
-  ```python
-  MonitoredSession(
-    session_creator=ChiefSessionCreator(master=..., config=...))
-  ```
+
+```python
+MonitoredSession(
+  session_creator=ChiefSessionCreator(master=..., config=...))
+```
+
 * In distributed setting for a non-chief worker, you can use following:
-  ```python
-  MonitoredSession(
-    session_creator=WorkerSessionCreator(master=..., config=...))
-  ```
+
+```python
+MonitoredSession(
+  session_creator=WorkerSessionCreator(master=..., config=...))
+```
+
 See `MonitoredTrainingSession` for an example usage based on chief or worker.
 
 Args: