* so.
 */
@SuppressWarnings({"SunApi", "removal"}) // b/345822163
@GwtIncompatible
@ElementTypesAreNonnullByDefault
abstract class Striped64 extends Number {
  /*
   * This class maintains a lazily-initialized table of atomically
   * updated variables, plus an extra "base" field. The table size
   * is a power of two. Indexing uses masked per-thread hash codes.
   * Nearly all declarations in this class are package-private,

 * so.
 */
@SuppressWarnings({"SunApi", "removal"}) // b/345822163
@GwtIncompatible
@ElementTypesAreNonnullByDefault
abstract class Striped64 extends Number {
  /*
   * This class maintains a lazily-initialized table of atomically
   * updated variables, plus an extra "base" field. The table size
   * is a power of two. Indexing uses masked per-thread hash codes.
   * Nearly all declarations in this class are package-private,

    func.return %1 : tensor<100x50xf32>
  }
}

// -----

// Test with empty initializers.
module attributes {tf_saved_model.semantics, tf_saved_model.under_construction} {

  "tf_saved_model.session_initializer"() {initializers = []} : () -> ()

type Instance struct {
	TypeArgs *TypeList
	Type     Type
}

// An Initializer describes a package-level variable, or a list of variables in case
// of a multi-valued initialization expression, and the corresponding initialization
// expression.
type Initializer struct {
	Lhs []*Var // var Lhs = Rhs
	Rhs syntax.Expr
}

func (init *Initializer) String() string {
	var buf strings.Builder
	for i, lhs := range init.Lhs {

	cloudConfig := config.ComponentConfig.KubeCloudShared.CloudProvider
	// initialize cloud provider with the cloud provider name and config file provided
	cloud, err := cloudprovider.InitCloudProvider(cloudConfig.Name, cloudConfig.CloudConfigFile)
	if err != nil {
		klog.Fatalf("Cloud provider could not be initialized: %v", err)
	}
	if cloud == nil {
		klog.Fatalf("Cloud provider is nil")
	}

      const tensorflow::thread::ThreadPoolOptions& thread_pool_options)
      override;

 private:
  void InitVariables();
  void BuildDeviceManager();
  void Initialize();

  std::unique_ptr<tensorflow::DeviceMgr> device_mgr_;
  bool initialized_ = false;
};

}  // namespace test_util
}  // namespace TF
}  // namespace mlir

    // CHECK: "tfl.assign_variable"(%[[RESOURCE]], %[[CST]]) : (tensor<!tf_type.resource<tensor<1x10xf32>>>, tensor<1x10xf32>) -> ()
  }

  "tf_saved_model.session_initializer"() {initializers = [@init_all_tables]} : () -> ()
  // CHECK: "tf_saved_model.session_initializer"() <{initializers = [@init_all_tables]}> : () -> ()

  // CHECK-LABEL: serving_default
  func.func @serving_default(%arg0: tensor<1x10xf32> {tf_saved_model.index_path = ["x"]}) ->

type Instance struct {
	TypeArgs *TypeList
	Type     Type
}

// An Initializer describes a package-level variable, or a list of variables in case
// of a multi-valued initialization expression, and the corresponding initialization
// expression.
type Initializer struct {
	Lhs []*Var // var Lhs = Rhs
	Rhs ast.Expr
}

func (init *Initializer) String() string {
	var buf bytes.Buffer
	for i, lhs := range init.Lhs {

  if (!attr) return nullptr;
  return symbol_table.lookup(attr.getValue());
}

SessionInitializerOp GetSessionInitializerOp(mlir::ModuleOp op) {
  auto initializers = op.getOps<SessionInitializerOp>();
  if (initializers.empty()) return {};
  return *initializers.begin();
}

class OptimizeSessionInitializerPattern
    : public OpRewritePattern<SessionInitializerOp> {
 public:
  using OpRewritePattern::OpRewritePattern;

  // No initializer function matches the initializer type.
  EXPECT_THAT(init_func_op, IsNull());
}

TEST_F(TfSavedModelTest, GetInitializerFunctionsEmptyWhenNoInitFunctions) {
  constexpr StringRef kModuleOpStr = R"mlir(
    module attributes {tf_saved_model.semantics} {
      "tf_saved_model.session_initializer"() {initializers = []} : () -> ()
    }
  )mlir";

  Block block;