fix according to comments

doc/design/session.md

@@ -6,26 +6,36 @@ This design doc proposes to have an object called *Session* which
 encapsulates the environment in which the computation graph is
 executed.
 
+The session is able to distinguish running a graph locally or
+remotely, using CPU only or using one or more GPUs. Different sessions
+have different runtime environments such as [scopes](./scope.md) and
+device contexts.
+
+
 ## Background
 
-A computation graph is executed in an environment which contains the
-[scope](./scope.md) and other states. PaddlePaddle used to only have
-an implicit global session on which `paddle.eval()` is executed.
+A computation graph runs in an environment which contains states such
+as the scope and device contexts. The current design has an implicit
+global session on which `paddle.eval()` is executed.
+
+Since the user is not able to explicitly switch between runtime
+environments such as the scope and the device contexts, the user
+cannot run a topology in two independent environments. For example, in
+reinforcement learning, the user may want to have a stale model for
+inference and a fresh model for training, and only replace the stale
+model with the fresh model periodically. Also, we have no concept that
+can encapsulate a remote environment that could execute a computation
+graph.
 
-This has the limitation that the user can not create two independent
-environments. For example, in reinforcement learning, the user may
-want to have a stale model for inference and a fresh model for
-training, and only replace the stale model with the fresh model
-periodically. Also, we have no concept that can encapsulate a remote
-environment that could execute a computation graph.
+We need a session concept to address above issues.
 
 ## Session
 
-Session is an object that owns all runtime states such as scope,
+A session is an object that owns all runtime states such as scope,
 reader OP's file handles, connection to a remote PaddlePaddle cluster,
 etc.
 
-Session has two methods: `eval` and `close`. `eval` executes the
+The session has two methods: `eval` and `close`. `eval` executes the
 target OP in a given graph, and `close` closes the session and
 releases all related resources:
 
@@ -51,7 +61,7 @@ image = reader.column(0)
 label = reader.column(1)
 fc1 = paddle.op.fc(image, size=256, act="sigmoid")
 fc2 = paddle.op.fc(fc1, size=10, act="softmax")
-cost = paddle.op.cross_entropy(fc2)
+cost = paddle.op.cross_entropy(fc2, label)
 opt = paddle.optimizer.sgd(cost)
 
 remote_config = ... # remote configuration such as endpoint, number of nodes and authentication.