status->status = absl::OkStatus();
  if (s == nullptr) return;
  TF_Graph* const graph = s->graph;
  if (graph != nullptr) {
    graph->mu.lock();
    graph->sessions.erase(s);
    const bool del = graph->delete_requested && graph->sessions.empty();
    graph->mu.unlock();
    if (del) delete graph;
  }
  delete s->session;
  delete s;
}

                        const int in_flight_nodes_limit)
      : status_(TF_NewStatus()),
        // If the context's default exector is set to async, re-using that in
        // each thread would cause collectives to deadlock. For consistency we
        // create a new sync executor for every thread.
        //
        // TODO(allenl): We should have an async API that works with the
        // parallel device.

// on both the main function side and the component function side, an error will
// be thrown in the registered graph optimization pass.
TEST(CAPI, DistributedFunctionGraphPassOnlyOnce) {
  // Register graph pass that will raise error if called more than once.
  tensorflow::optimization_registration::OptimizationPassRegistration
      register_test_pass(tensorflow::OptimizationPassRegistry::PRE_PLACEMENT, 0,

  // in an initialized context.
  for (auto d = devices.begin(); d != devices.end();) {
    if (absl::StrContains(d->get()->name(), "CPU:0")) {
      d = devices.erase(d);
    } else {
      ++d;
    }
  }

  status->status = tensorflow::unwrap(ctx)->AddDevices(std::move(devices));
}

void TFE_InsertConfigKeyValue(TFE_Context* ctx, const char* key,