NameAttrList function;
  function.set_name(std::string{func_name});

  std::string device_name;
  if (!platform_name.empty()) {
    device_name = absl::StrCat("/device:", platform_name, ":0");
  }
  FunctionLibraryRuntime* flr = pflr->GetFLR(device_name);
  if (flr == nullptr) {
    // Use CPU as the fallback to get the `FunctionLibraryRuntime`.
    flr = pflr->GetFLR("/device:CPU:0");

    return absl::OkStatus();
  }

  int device_count = platform->VisibleDeviceCount();

  for (int i = 0; i < device_count; ++i) {
    const string device_name = absl::StrCat("/physical_device:TPU:", i);
    devices->push_back(device_name);
  }

  return absl::OkStatus();
}

Status TpuNodeDeviceFactory::CreateDevices(
    const SessionOptions& session_options, const string& name_prefix,

    const char* node_name = opdef.name().c_str();
    const char* op_name = opdef.name().c_str();
    const char* device_name = "CPU";
    static auto fake_compute_func = [](void* kernel, TF_OpKernelContext* ctx) {
    };

    TF_KernelBuilder* builder =
        TF_NewKernelBuilder(op_name, device_name, /*create_func=*/nullptr,
                            fake_compute_func, /*delete_func=*/nullptr);

                                                         TF_Status* status);

// Create a new TFE_TensorHandle with the same contents as 'h' but placed
// in the memory of the device name 'device_name'.
// If source and destination are the same device, then this creates a new handle
// that shares the underlying buffer. Otherwise, it currently requires at least

  if (!device || device.getValue().empty()) {
    return std::nullopt;
  }
  const std::string device_name = device.str();
  tensorflow::DeviceNameUtils::ParsedName parsed_name;
  if (!tensorflow::DeviceNameUtils::ParseFullName(device_name, &parsed_name)) {
    return std::nullopt;
  }
  if (!parsed_name.has_type) {
    return std::nullopt;
  }
  return parsed_name.type;
}

// ParallelDevice.
void DeleteParallelDevice(void* device_info) {
  delete reinterpret_cast<NamedParallelDevice*>(device_info);
}

}  // namespace

void AllocateParallelDevice(const char* device_name,
                            const char* const* underlying_devices,
                            int num_underlying_devices,
                            TFE_CustomDevice* device, void** device_info) {

        flags->xla_auto_jit_flag.optimization_level_general);
  }

  return result;
}

int GetGpuNumber(const string& device_name) {
  DeviceNameUtils::ParsedName parsed_name;
  if (!DeviceNameUtils::ParseFullName(device_name, &parsed_name)) {
    return -1;
  }

  return parsed_name.type == DEVICE_GPU ? parsed_name.id : -1;
}
}  // namespace

  return launch_context;
}

Status GetTaskName(const std::string_view device_name, std::string* task_name) {
  string ignored;
  if (!DeviceNameUtils::SplitDeviceName(device_name, task_name, &ignored)) {
    return errors::InvalidArgument("Unable to parse device name: ",
                                   device_name);
  }

  return absl::OkStatus();
}

//   SP_Device device { SP_DEVICE_STRUCT_SIZE };
//   SE_CreateDeviceParams params { SE_CREATE_DEVICE_PARAMS_STRUCT_SIZE } ;
//   params.device = &device;
//
//   /* Plugin code below */
//   constexpr char DEVICE_NAME[] = "MY_DEVICE";
//   constexpr char DEVICE_TYPE[] = "GPU";
//
//   void create_device(const SP_Platform* platform,
//                      SE_CreateDeviceParams* params, TF_Status* status) {

// some reason, the kernel builder will not be registered, the caller should
// delete it with TF_DeleteKernelBuilder.
TF_CAPI_EXPORT extern TF_KernelBuilder* TF_NewKernelBuilder(
    const char* op_name, const char* device_name,
    void* (*create_func)(TF_OpKernelConstruction*),
    void (*compute_func)(void*, TF_OpKernelContext*),
    void (*delete_func)(void*));

// Allocates a new kernel builder and returns a pointer to it.
//