Consolidate worker state behind a session-centric abstraction.

State in workers is currently splayed across graph_mgr, rendezvous_mgr, and
additional components. This has resulted in it being difficult to ensure proper
cleanup and shut down of the worker components.

In addition to paving the way for a more reliable shut down, this CL also sets
up the beginnings of ClusterSpec propagation.

ClusterSpec propagation is a capability upgrade for TensorFlow that should make
it much easier to (1) build distributed TensorFlow clusters, and (2) handle
node failures. After the ClusterSpec propagation capability is fully
implemented, the TensorFlow workers can be booted independently of each other,
and with no knowledge about others. A client can then query a central cluster
scheduler or other API to find all of the workers, and then send the
ClusterDef (ClusterSpec) to the TF master, which then propagates that along to
all of the workers.

This change is only the first of a sequence to fully implement ClusterSpec
propagation in TensorFlow.
Change: 151229111

1 files changed, 4 insertions, 0 deletions

diff --git a/tensorflow/core/protobuf/worker_service.proto b/tensorflow/core/protobuf/worker_service.proto
index 689752cf3e..3de9e48b78 100644
--- a/tensorflow/core/protobuf/worker_service.proto
+++ b/tensorflow/core/protobuf/worker_service.proto
@@ -40,6 +40,10 @@ service WorkerService {
   rpc GetStatus(GetStatusRequest) returns (GetStatusResponse);
 
   // See worker.proto for details.
+  rpc CreateWorkerSession(CreateWorkerSessionRequest)
+      returns (CreateWorkerSessionResponse);
+
+  // See worker.proto for details.
   rpc RegisterGraph(RegisterGraphRequest) returns (RegisterGraphResponse);
 
   // See worker.proto for details.