// Eager Service defines a TensorFlow service that executes operations eagerly
// on a set of local devices, on behalf of a remote Eager executor.
//
-// The service impl will keep track of the various peers and devices it has
+// The service impl will keep track of the various clients and devices it has
// access to and allows the client to enqueue ops on any devices that it is able
// to access and schedule data transfers from/to any of the peers.
//
+// A client can generate multiple contexts to be able to independently execute
+// operations, but cannot share data between the two contexts.
+//
+// NOTE: Even though contexts generated by clients should be independent, the
+// lower level tensorflow execution engine is not, so they might share some data
+// (e.g. a Device's ResourceMgr).
+//
////////////////////////////////////////////////////////////////////////////////
service EagerService {
// This initializes the worker, informing it about the other workers in the