Fix formatting error in tutorial.

doc/source/tutorial.rst

@@ -16,22 +16,22 @@ for large computations.
 When using Ray, several processes are involved.
 
 - Multiple **worker** processes execute tasks and store results in object
-stores. Each worker is a separate process.
+  stores. Each worker is a separate process.
 - One **object store** per node stores immutable objects in shared memory and
-allows workers to efficiently share objects on the same node with minimal
-copying and deserialization.
+  allows workers to efficiently share objects on the same node with minimal
+  copying and deserialization.
 - One **local scheduler** per node assigns tasks to workers on the same node.
 - A **global scheduler** receives tasks from local schedulers and assigns them
-to other local schedulers.
+  to other local schedulers.
 - A **driver** is the Python process that the user controls. For example, if the
-user is running a script or using a Python shell, then the driver is the Python
-process that runs the script or the shell. A driver is similar to a worker in
-that it can submit tasks to its local scheduler and get objects from the object
-store, but it is different in that the local scheduler will not assign tasks to
-the driver to be executed.
+  user is running a script or using a Python shell, then the driver is the Python
+  process that runs the script or the shell. A driver is similar to a worker in
+  that it can submit tasks to its local scheduler and get objects from the object
+  store, but it is different in that the local scheduler will not assign tasks to
+  the driver to be executed.
 - A **Redis server** maintains much of the system's state. For example, it keeps
-track of which objects live on which machines and of the task specifications
-(but not data). It can also be queried directly for debugging purposes.
+  track of which objects live on which machines and of the task specifications
+  (but not data). It can also be queried directly for debugging purposes.
 
 Starting Ray
 ------------