}
    }
  )mlir";

  OwningOpRef<ModuleOp> module_op_ref = ParseModuleOpString(kModuleCode);
  const auto test_func =
      module_op_ref->lookupSymbol<func::FuncOp>("test_fold_constant");
  ASSERT_THAT(test_func, NotNull());

  Operation* mul_op = FindOperationOfType<TF::MulOp>(test_func);
  SmallVector<Value> results = ConstantFoldOpIfPossible(mul_op);
  EXPECT_THAT(results, SizeIs(1));

  ASSERT_TRUE(module_op);

  auto test_func =
      module_op->lookupSymbol<func::FuncOp>("same_scale_after_composite");
  ASSERT_THAT(test_func, NotNull());

  auto quantize_op = FindOperationOfType<quantfork::QuantizeCastOp>(test_func);
  EXPECT_FALSE(IsOpQuantizableStableHlo(quantize_op));

  auto dequantize_op =
      FindOperationOfType<quantfork::DequantizeCastOp>(test_func);

	Uint64("test_uint64", 0, "uint64 value")
	String("test_string", "0", "string value")
	Float64("test_float64", 0, "float64 value")
	Duration("test_duration", 0, "time.Duration value")
	Func("test_func", "func value", func(string) error { return nil })
	BoolFunc("test_boolfunc", "func", func(string) error { return nil })

	m := make(map[string]*Flag)
	desired := "0"
	visitor := func(f *Flag) {

func formatTestmain(t *testFuncs) ([]byte, error) {
	var buf bytes.Buffer
	tmpl := testmainTmpl
	if cfg.Experiment.CoverageRedesign {
		tmpl = testmainTmplNewCoverage
	}
	if err := tmpl.Execute(&buf, t); err != nil {
		return nil, err
	}
	return buf.Bytes(), nil
}

type testFuncs struct {
	Tests       []testFunc
	Benchmarks  []testFunc
	FuzzTargets []testFunc

		expectedPVC *v1.PersistentVolumeClaim
		testFunc    func(*v1.PersistentVolumeClaim, clientset.Interface, resource.Quantity) (*v1.PersistentVolumeClaim, error)
	}{
		{
			name:        "mark fs resize, with no other conditions",
			pvc:         basePVC.get(),
			expectedPVC: basePVC.withStorageResourceStatus(v1.PersistentVolumeClaimNodeResizePending).get(),

		maker fileMaker
		tests []testFnc
	}{{
		maker: makeReg{0, ""},
		tests: []testFnc{
			testRemaining{0, 0},
			testWrite{"", 0, nil},
			testWrite{"a", 0, ErrWriteTooLong},
			testReadFrom{fileOps{""}, 0, nil},
			testReadFrom{fileOps{"a"}, 0, ErrWriteTooLong},
			testRemaining{0, 0},
		},
	}, {
		maker: makeReg{1, "a"},
		tests: []testFnc{
			testRemaining{1, 1},

				NodeCIDRMaskSizes:    []int{24},
			},
			expectedAllocatedCIDR: map[int]string{
				0: "10.10.1.0/24",
			},
		},
	}

	// test function
	_, tCtx := ktesting.NewTestContext(t)
	testFunc := func(tc testCase) {
		fakeNodeInformer := test.FakeNodeInformer(tc.fakeNodeHandler)
		nodeList, _ := tc.fakeNodeHandler.List(tCtx, metav1.ListOptions{})
		// Initialize the range allocator.

          %outputs_5, %control_6 = tf_executor.island(%control_4) wraps "tf._XlaHostComputeMlir"() {host_mlir_module = "module {\0A func.func @host_func() -> tensor<1x2xf32> {\0A %0 = \22tf.Const\22() {value = dense<0.1> : tensor<1x2xf32>} : () -> tensor<1x2xf32> \0A return %0 : tensor<1x2xf32>}}", manual_sharding = true, recv_key = "host_compute_channel_1_retvals", send_key = "host_compute_channel_1_args"}...

				featuregatetesting.SetFeatureGateDuringTest(t, utilfeature.DefaultFeatureGate, fg, f)
				t.Run(fmt.Sprintf("%v (%t)", fg, f), tf)
			}()
		}
	}
}

func TestGetTargetNodeName(t *testing.T) {
	testFun := func(t *testing.T) {
		tests := []struct {
			pod         *v1.Pod
			nodeName    string
			expectedErr bool
		}{
			{
				pod: &v1.Pod{
					ObjectMeta: metav1.ObjectMeta{
						Name:      "pod1",

    for (Type ty : op.getResultTypes()) {
      shape_attrs.push_back(TF::ShapeAttr::get(rewriter.getContext(),
                                               mlir::cast<ShapedType>(ty)));
    }

    // Clone the `host_func` in the `host_mlir_module` attribute if it exists
    // and use it for `shape_inference_graph` attribute on XlaHostCompute.
    func::FuncOp cloned_func;
    SymbolTable manager(op->getParentOfType<ModuleOp>());