namespace tensorflow {

bool XlaKernelCreator::CanCreateKernel(
    const FunctionLibraryRuntime& flr,
    const std::shared_ptr<const NodeProperties>& props) const {
  return CanCreateXlaKernel(props->node_def) &&
         !XlaOpRegistry::IsCompilationDevice(flr.device()->device_type());
}

static Status CreateXlaKernel(FunctionLibraryRuntime* flr,
                              const NodeDef& node_def,

          << ",detailed_logging=" << options.detailed_logging << "]";
}
}  // namespace

XlaCompiler::Options GenerateCompilerOptions(
    const XlaDeviceCompiler& xla_device_compiler,
    const FunctionLibraryRuntime& function_library, DeviceBase* device,
    se::Stream* stream, const XlaPlatformInfo& platform_info,
    bool has_ref_vars) {
  XlaCompiler::Options options;

namespace tensorflow {

class FunctionLibraryRuntime;
class OpKernel;

class XlaKernelCreator : public CustomKernelCreator {
 public:
  // Given a NodeDef 'node_def' and the function library runtime 'flr', returns
  // true if 'node_def' is a call to a compilable function defined in 'flr',
  // with the kXlaCompileAttr set.
  bool CanCreateKernel(
      const FunctionLibraryRuntime& flr,

// the persistor used in the DeviceCompiler. The platform ID from
// `platform_info` must not be null in CPU case.
Status BuildXlaDeviceCompiler(
    DeviceBase* dev, FunctionLibraryRuntime* flr,
    const XlaPlatformInfo& platform_info, DeviceType compilation_device_type,
    DeviceCompiler<xla::LocalExecutable, xla::LocalClient>**
        xla_device_compiler);

    const DeviceCompiler<xla::LocalExecutable, xla::LocalClient>&
        xla_device_compiler,
    const FunctionLibraryRuntime& function_library);

// Returns created options for XLA compiler when PjRt (Device API) is used for
// compilation and execution.
XlaCompiler::Options GenerateCompilerOptionsForPjRt(
    const FunctionLibraryRuntime& function_library,
    const DeviceBase* device_base, const XlaPlatformInfo& platform_info,

    const NameAttrList& func_name_attrs, const string& new_func_name,
    const string& host_graph_func_name,
    const std::map<string, int>& host_compute_core, FunctionLibraryRuntime* flr,
    FunctionLibraryDefinition* fld, std::vector<string>* shape_inference_graphs,
    bool* has_outside_compilation);

// Rewrites XLA computation in `clusters` to replace outside compilation nodes

// computation.
// - `flr`: the FunctionLibraryRuntime for the `function`.
Status CompileToPjRtLoadedExecutable(
    const DeviceBase* device, const XlaPlatformInfo& platform_info,
    const NameAttrList& function,
    const std::vector<XlaCompiler::Argument>& args,
    DeviceCompileMode compile_mode, bool has_ref_vars,
    bool may_alias_resource_update, FunctionLibraryRuntime* flr,

      const std::vector<std::string>& device_names,
      const std::optional<FunctionDef>& fdef = std::nullopt);
  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_;
};

    const NameAttrList& function,
    const std::vector<XlaCompiler::Argument>& args,
    DeviceCompileMode compile_mode, bool has_ref_vars,
    bool may_alias_resource_update, FunctionLibraryRuntime* flr,
    ResourceMgr* rm, const XlaCompiler::CompilationResult** compilation_result,
    xla::PjRtClient** client, xla::PjRtLoadedExecutable** executable) {
  PjRtDeviceCompiler* pjrt_device_compiler;

  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()) {
    if (CanCreateXlaKernel(node->def())) {
      const FunctionBody* fbody = nullptr;