// using library runtime `runtime` on a device `dev` with given
// `inputs_arg_shape_and_dtype` and `input_handles`.
absl::StatusOr<std::string> GetCompilerIr(
    IrExportStage stage, ProcessFunctionLibraryRuntime* pflr,
    absl::string_view func_name, Device* dev, EagerContext* context,
    absl::Span<const ArgShapeAndDType> input_arg_shape_and_dtype,
    absl::Span<const TensorHandle* const> input_handles,

  Graph* graph = options.graph->get();

  OptimizerOptions opts;
  auto pflr = std::make_unique<ProcessFunctionLibraryRuntime>(
      nullptr, options.session_options->env, /*config=*/nullptr,
      TF_GRAPH_DEF_VERSION, options.flib_def, opts);
  FunctionLibraryRuntime* flr =
      pflr->GetFLR(ProcessFunctionLibraryRuntime::kDefaultFLRDevice);

  for (Node* node : graph->nodes()) {

  }
  FunctionLibraryRuntime* flr = pflr->GetFLR(device_name);
  if (flr == nullptr) {
    // Use CPU as the fallback to get the `FunctionLibraryRuntime`.
    flr = pflr->GetFLR("/device:CPU:0");
  }

  TF_ASSIGN_OR_RETURN(
      std::vector<XlaCompiler::Argument> args,
      PrepareXlaCompilerArgs(flr, function, context, /*dev=*/nullptr,

  TF_RETURN_IF_ERROR(scope.ToGraph(graph.get()));

  std::unique_ptr<ProcessFunctionLibraryRuntime> pflr(
      new ProcessFunctionLibraryRuntime(
          nullptr, Env::Default(), /*config=*/nullptr, TF_GRAPH_DEF_VERSION,
          flib_def, OptimizerOptions{}));
  FunctionLibraryRuntime* lib_runtime =
      pflr->GetFLR(ProcessFunctionLibraryRuntime::kDefaultFLRDevice);

  std::vector<bool> compile_time_const_nodes(graph->num_node_ids());
  OptimizerOptions opts;
  auto pflr = std::make_unique<ProcessFunctionLibraryRuntime>(
      nullptr, env, /*config=*/nullptr, TF_GRAPH_DEF_VERSION, flib_def, opts);
  FunctionLibraryRuntime* lib_runtime =
      pflr->GetFLR(ProcessFunctionLibraryRuntime::kDefaultFLRDevice);
  TF_RETURN_IF_ERROR(BackwardsConstAnalysis(*graph, nullptr,

  std::unique_ptr<ProcessFunctionLibraryRuntime> pflr(
      new ProcessFunctionLibraryRuntime(
          device_mgr.get(), options.session_options->env,
          /*config=*/config, TF_GRAPH_DEF_VERSION, library,
          config->graph_options().optimizer_options()));
  FunctionLibraryRuntime* flr =
      pflr->GetFLR("/job:localhost/replica:0/task:0/device:CPU:0");
  if (flr == nullptr) {
    return errors::Internal(

  OptimizerOptions opts;
  std::unique_ptr<ProcessFunctionLibraryRuntime> pflr(
      new ProcessFunctionLibraryRuntime(nullptr, env_, /*config=*/nullptr,
                                        TF_GRAPH_DEF_VERSION, flib_def_, opts));
  FunctionLibraryRuntime* lib_runtime =
      pflr->GetFLR(ProcessFunctionLibraryRuntime::kDefaultFLRDevice);

  auto device_mgr = std::make_unique<StaticDeviceMgr>(std::move(devices));
  auto pflr = std::make_unique<ProcessFunctionLibraryRuntime>(
      device_mgr.get(), Env::Default(), /*config=*/nullptr,
      TF_GRAPH_DEF_VERSION, lib_def.get(), opts,
      /*default_thread_pool=*/nullptr, /*cluster_flr=*/nullptr);
  auto flr = pflr->GetFLR("/job:localhost/replica:0/task:0/cpu:0");

  std::unique_ptr<Graph> graph_out;

  Device* GetDevice(const string& device_name);
  FunctionLibraryRuntime* flr() { return flr_; }

 private:
  FunctionLibraryRuntime* flr_;
  std::unique_ptr<DeviceMgr> device_mgr_;
  std::unique_ptr<FunctionLibraryDefinition> lib_def_;
  std::unique_ptr<ProcessFunctionLibraryRuntime> pflr_;
};

}  // namespace tensorflow

      std::make_unique<PjRtDeviceCompilerClient>(pjrt_client));
}

absl::StatusOr<std::optional<std::set<int>>> GetAllowedGpus(
    FunctionLibraryRuntime* flr) {
  std::optional<std::set<int>> gpu_ids = std::nullopt;

  if (flr->config_proto()) {
    string allowed_gpus =
        flr->config_proto()->gpu_options().visible_device_list();
    TF_ASSIGN_OR_RETURN(gpu_ids, ParseVisibleDeviceList(allowed_gpus));
  }

  return gpu_ids;
}