[minor] OSS doc fix - add the DDP wrap (#131)

* wrapping the model in DDP in the tutorial

* typo

docs/source/tutorials/oss.rst

 Optimizer state sharding
 ========================
 
-Using torch.nn.parallel.DistributedDataParallel leads to some wasted communications, but it is possible and makes OSS a drop in solution in your existing torch distributed code.
+Using torch.nn.parallel.DistributedDataParallel leads to some wasted communications in the case of OSS, but it is possible and makes OSS a drop in solution in your existing torch distributed code.
 Let's suppose that your trainer looks like
 
 .. code-block:: python
 
 
     import torch
+    from torch.nn.parallel import DistributedDataParallel as DDP
+
 
     def train(
         rank: int,
@@ -19,6 +21,7 @@ Let's suppose that your trainer looks like
 
         # Problem statement
         model = myAwesomeModel().to(rank)
+        model = DDP(model, device_ids=[rank])
         dataloader = mySuperFastDataloader()
         loss_ln = myVeryRelevantLoss()
 
@@ -50,6 +53,7 @@ Then sharding the optimizer state is merely a matter of wrapping your optimizer
 
     import torch
     from fairscale.optim.oss import OSS
+    from torch.nn.parallel import DistributedDataParallel as DDP
 
     def train(
         rank: int,
@@ -61,6 +65,7 @@ Then sharding the optimizer state is merely a matter of wrapping your optimizer
 
         # Problem statement
         model = myAwesomeModel().to(rank)
+        model = DDP(model, device_ids=[rank])
         dataloader = mySuperFastDataloader()
         loss_ln = myVeryRelevantLoss()