// vanilla TensorFlow op as long as the bridge supports it.
class XlaCompileOnDemandOp : public OpKernel {
 public:
  explicit XlaCompileOnDemandOp(OpKernelConstruction* ctx)
      : OpKernel(ctx),
        platform_info_(XlaPlatformInfoFromDevice(ctx->device())) {}
  void Compute(OpKernelContext* ctx) override;

 private:
  Status Compile(const std::vector<XlaCompiler::Argument>& args,
                 OpKernelContext* ctx,

  // Indexes of compile-time constant inputs
  const std::vector<int> constants_;
  // Indexes of resource inputs
  const std::vector<int> resources_;

  const NameAttrList function_;
  const XlaPlatformInfo platform_info_;

  bool has_ref_vars_;
};

// XlaLocalLaunchOp is used to replace a region of the TensorFlow graph
// which will be compiled and executed using XLA.  The XlaLocalLaunchOp is

  options.graph_def_version = function_library.graph_def_version();
  options.allow_cpu_custom_calls =
      (platform_info.platform_id() == se::host::kHostPlatformId);
  options.device_allocator = GetAllocator(device, stream, platform_info);
  if (platform_info.xla_device_metadata()) {
    options.shape_determination_fns =
        platform_info.xla_device_metadata()->default_shape_determination_fns();
  }

// Builds a DeviceCompiler that uses xla::LocalClient using `platform_info` and
// `compilation_device_type` (in non-TPU case) and sets *xla_device_compiler to
// point to it. Uses flags from `MarkForCompilationPassFlags` for configuring
// the persistor used in the DeviceCompiler. The platform ID from
// `platform_info` must not be null in CPU case.
Status BuildXlaDeviceCompiler(

  TF_ASSIGN_OR_RETURN(ResourceMgr * rm, GetResourceMgrForDeviceCompiler(
                                            ctx, platform_info.device_type()));
  return CompileToPjRtLoadedExecutable(
      ctx.device(), platform_info, function, args, compile_mode, has_ref_vars,
      may_alias_resource_update, ctx.function_library(), rm, compilation_result,
      client, executable);
}

    const DeviceCompiler<xla::LocalExecutable, xla::LocalClient>&
        xla_device_compiler,
    const FunctionLibraryRuntime& function_library, DeviceBase* device,
    se::Stream* stream, const XlaPlatformInfo& platform_info,
    bool has_ref_vars);

// Returns created options for XLA compiler when TFRT-TPU is used.
XlaCompiler::Options GenerateCompilerOptionsForTfrtTpu(
    const DeviceCompiler<xla::LocalExecutable, xla::LocalClient>&

  TF_ASSERT_OK_AND_ASSIGN(auto fdef, SampleFuntionAddXY("foo"));
  device_setup.AddDevicesAndSetUp({DEVICE_GPU}, fdef);

  Device* device = device_setup.GetDevice(DEVICE_GPU);
  const XlaPlatformInfo platform_info = XlaPlatformInfoFromDevice(device);

  NameAttrList function;
  function.set_name("foo");

  ResourceMgr resource_mgr("");

  const XlaCompiler::CompilationResult* compilation_result = nullptr;

// used for compilation is output in `client`. The PJRT executable is output in
// `executable`.
Status CompileToPjRtLoadedExecutable(
    const OpKernelContext& ctx, 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,