TFE_NewOp(context.get(), "VarHandleOp", status.get()), TFE_DeleteOp);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  TFE_OpSetAttrType(handle_op.get(), "dtype", TF_FLOAT);
  TFE_OpSetAttrShape(handle_op.get(), "shape", /*dims=*/nullptr, /*num_dims=*/0,
                     status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  auto outputs =

  ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
  TF_DeleteGraph(function_graph);
  TFE_ContextOptions* opts = TFE_NewContextOptions();
  TFE_Context* ctx = TFE_NewContext(opts, status);
  ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);
  TFE_DeleteContextOptions(opts);
  TFE_ContextAddFunction(ctx, fn, status);
  ASSERT_TRUE(TF_GetCode(status) == TF_OK) << TF_Message(status);

  std::unique_ptr<tensorflow::GrpcServer> worker_server1;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(
                  server_def, tensorflow::Env::Default(), &worker_server1)
                  .ok());
  ASSERT_TRUE(worker_server1->Start().ok());

  server_def.set_task_index(2);
  std::unique_ptr<tensorflow::GrpcServer> worker_server2;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(

  server_def.set_task_index(1);

  std::unique_ptr<tensorflow::GrpcServer> worker_server;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(
                  server_def, tensorflow::Env::Default(), &worker_server)
                  .ok());
  ASSERT_TRUE(worker_server->Start().ok());

  TF_Status* status = TF_NewStatus();
  TFE_ContextOptions* opts = TFE_NewContextOptions();

  std::unique_ptr<tensorflow::GrpcServer> worker_server1;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(
                  server_def, tensorflow::Env::Default(), &worker_server1)
                  .ok());
  ASSERT_TRUE(worker_server1->Start().ok());

  server_def.set_task_index(2);
  std::unique_ptr<tensorflow::GrpcServer> worker_server2;
  ASSERT_TRUE(tensorflow::GrpcServer::Create(

  }
  const string gpu_1_name(TF_DeviceListName(devices, 1, status.get()));
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK);
  const string gpu_2_name(TF_DeviceListName(devices, 2, status.get()));
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK);
  TFE_TensorHandle* hdevice =
      TFE_TensorHandleCopyToDevice(hcpu, ctx, gpu_1_name.c_str(), status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK);

  EXPECT_TRUE(neg == neg2);
  NodeDef node_def2;
  ASSERT_TRUE(GetNodeDef(neg2, &node_def2));
  EXPECT_EQ(node_def.DebugString(), node_def2.DebugString());

  TF_Operation* feed2 = TF_GraphOperationByName(graph, "feed");
  EXPECT_TRUE(feed == feed2);
  ASSERT_TRUE(GetNodeDef(feed, &node_def));
  ASSERT_TRUE(GetNodeDef(feed2, &node_def2));
  EXPECT_EQ(node_def.DebugString(), node_def2.DebugString());

        const auto& v = a_edges.insert({iter->second, arg.name()});
        ASSERT_TRUE(v.second) << "Duplicate edge " << iter->second << " -> "
                              << arg.name() << ". fdef: " << fdef.DebugString();
      } else {
        const auto& v = a_edges.insert({arg.name(), arg.name()});
        ASSERT_TRUE(v.second) << "Duplicate edge " << arg.name() << " -> "

                                                value_two.get()};
    TensorHandlePtr combined_value = CreatePerDeviceValues(
        context.get(), components, device_name, status.get());
    ASSERT_TRUE(TF_GetCode(status.get()) == TF_INVALID_ARGUMENT)
        << TF_Message(status.get());
  }

  {
    // Try to extract the wrong number of components from a parallel tensor

task_index: 1
protocol: "grpc"
)");

  TF_Status* status = TF_NewStatus();
  TF_Buffer* result = TFE_GetServerDef(expected_text_proto.c_str(), status);
  EXPECT_EQ(TF_GetCode(status), TF_OK);

  ServerDef actual;
  ASSERT_TRUE(actual.ParseFromArray(result->data, result->length));
  string actual_text_proto;
  tensorflow::protobuf::TextFormat::PrintToString(actual, &actual_text_proto);
  EXPECT_EQ(expected_text_proto, actual_text_proto);