name:      "* and ns1 together are not allowed",
			namespace: "ns5",
			exportTo:  []string{"*", "ns1"},
			wantErr:   true,
		},
		{
			name:      ". and same namespace in exportTo is not okay",
			namespace: "ns5",
			exportTo:  []string{".", "ns5"},
			wantErr:   true,
		},
		{
			name:      "duplicate namespaces in exportTo is not okay",
			namespace: "ns5",
			exportTo:  []string{"ns1", "ns2", "ns1"},

func (m *IngressClassParametersReference) MarshalToSizedBuffer(dAtA []byte) (int, error) {
	i := len(dAtA)
	_ = i
	var l int
	_ = l
	if m.Namespace != nil {
		i -= len(*m.Namespace)
		copy(dAtA[i:], *m.Namespace)
		i = encodeVarintGenerated(dAtA, i, uint64(len(*m.Namespace)))
		i--
		dAtA[i] = 0x2a
	}
	if m.Scope != nil {
		i -= len(*m.Scope)
		copy(dAtA[i:], *m.Scope)

#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/gtl/cleanup.h"
#include "tensorflow/core/platform/macros.h"
#include "tensorflow/core/util/dump_graph.h"

namespace tensorflow {

namespace {

// Control return mapping function for outside compilation host graphs.
// All nodes with kXlaHasHostTransfer attribute are control outputs.
std::optional<string> HostGraphControlRetMapping(const Node* n) {

#include "tensorflow/core/framework/kernel_shape_util.h"
#include "tensorflow/core/lib/math/math_util.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/util/padding.h"

namespace mlir {
namespace odml {
namespace {

#define DEBUG_TYPE "tf-legalize-hlo"

#define GEN_PASS_DEF_LEGALIZEHLOTOTFPASS
#include "tensorflow/compiler/mlir/lite/stablehlo/transforms/passes.h.inc"

#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/public/session_options.h"
#include "tensorflow/core/public/version.h"
#include "tensorflow/core/util/equal_graph_def.h"

namespace tensorflow {
namespace {

const char* const kXlaHostTransferSequencerAttr =
    "_xla_host_transfer_sequencer";

Status AddGraphDefToFunctionLibrary(const GraphDefBuilder& graphdef_builder,

using ::int64_t;
using mlir::func::FuncOp;
using tensorflow::shape_inference::DimensionHandle;
using tensorflow::shape_inference::InferenceContext;
using tensorflow::shape_inference::ShapeHandle;

namespace mlir {
namespace TF {
namespace {

// Compute a refined type between two types `lhs` and `rhs`, the result type
// is always more refined (i.e. has more static information) than `lhs`

			pv := volumeToMount.VolumeSpec.PersistentVolume
			pvc, err := og.kubeClient.CoreV1().PersistentVolumeClaims(pv.Spec.ClaimRef.Namespace).Get(context.TODO(), pv.Spec.ClaimRef.Name, metav1.GetOptions{})
			if err != nil {
				eventErr, detailedErr := volumeToMount.GenerateError("VerifyControllerAttachedVolume fetching pvc failed", err)

// libstdc++ (which is where cxxabi.h comes from).
# if GTEST_HAS_CXXABI_H_
#  include <cxxabi.h>
# elif defined(__HP_aCC)
#  include <acxx_demangle.h>
# endif  // GTEST_HASH_CXXABI_H_

namespace testing {
namespace internal {

// GetTypeName<T>() returns a human-readable name of type T.
// NB: This function is also used in Google Mock, so don't move it inside of
// the typed-test-only section below.
template <typename T>

// libstdc++ (which is where cxxabi.h comes from).
# if GTEST_HAS_CXXABI_H_
#  include <cxxabi.h>
# elif defined(__HP_aCC)
#  include <acxx_demangle.h>
# endif  // GTEST_HASH_CXXABI_H_

namespace testing {
namespace internal {

// GetTypeName<T>() returns a human-readable name of type T.
// NB: This function is also used in Google Mock, so don't move it inside of
// the typed-test-only section below.
template <typename T>

utes)&&("attributes"!==n||!d.attributeFilter||null===o.namespace&&d.attributeFilter.indexOf(o.name)!==-1)&&("characterData"!==n||d.characterData)&&("childList"!==n||d.childList)){var p=u.observer;i[p.uid_]=p,("attributes"===n&&d.attributeOldValue||"characterData"===n&&d.characterDataOldValue)&&(a[p.uid_]=o.oldValue)}}}for(var f in i){var p=i[f],m=new r(n,e);"name"in o&&"namespace"in o&&(m.attributeName=o.name,m.attributeNamespace=o.namespace),o.addedNodes&&(m.addedNodes=o.addedNodes),o.removedNo...