static constexpr size_t kResultIndex = 0;

  // Shapes of the input arguments.
  static constexpr int32_t kArg0Shapes[] = {
1, 2
  };
  static constexpr int32_t kArg1Shapes[] = {
3, 4
  };
  static constexpr int32_t kArg2Shapes[] = {
1
  };
  static constexpr int32_t kArg3Shapes[] = {
1
  };
  static constexpr int32_t kArg4Shapes[] = {
5
  };

using tpu::FunctionToHloArgs;
using tpu::MlirToHloArgs;
using tpu::ShardingAndIndex;
using tpu::TPUCompileMetadataProto;

static constexpr char kCompilationTimeStreamzName[] =
    "/tensorflow/core/tf2xla/api/v2/phase2_compilation_time";
static constexpr char kFullBridge[] = "full_bridge";
static constexpr char kCompilationStatusStreamzName[] =
    "/tensorflow/core/tf2xla/api/v2/phase2_compilation_status";

using ::testing::IsEmpty;
using ::testing::IsNull;
using ::testing::NotNull;
using ::testing::Optional;
using ::tsl::testing::StatusIs;

using AttrsAndConstraintsTest = ::mlir::quant::QuantizationTestBase;

constexpr absl::string_view kModuleStatic = R"mlir(
  module {
    func.func @main(%arg0: tensor<1x1024xf32>, %arg1: tensor<1024x3xf32>) -> tensor<1x3xf32> attributes {_from_xla_call_module} {

using ::tsl::monitoring::testing::Histogram;

static constexpr char kCompilationTimeStreamzName[] =
    "/tensorflow/core/tf2xla/api/v1/phase2_compilation_time";

static constexpr char kCompilationStatusStreamzName[] =
    "/tensorflow/core/tf2xla/api/v1/phase2_compilation_status";

static constexpr char kPlatformName[] = "Host";
constexpr char kEntryFuncName[] = "main";

static constexpr char kMlirModuleStr[] = R"(

using ::testing::UnorderedElementsAre;

using IsOpQuantizableStableHloTest = ::mlir::quant::QuantizationTestBase;

// Quantizable ops: constants
// Non-quantizable ops: normal StableHLO ops and terminators
constexpr absl::string_view kModuleConstantAdd = R"mlir(
  module {
    func.func @constant_add() -> (tensor<3x2xf32>) {
      %cst1 = stablehlo.constant dense<2.4> : tensor<3x2xf32>

#include "tensorflow/compiler/mlir/tensorflow/utils/xla_call_module_attrs.h"

namespace mlir::quant {

constexpr char kAttrMapAttribute[] = "attr_map";

// Name of the string attribute attached to `XlaCallModuleOp`, which is the
// textproto representation of `Method`.
inline constexpr StringRef kQuantizationMethodAttr = "_quantization_method";

// Permutation from the NHWC tensor format to NCHW. This is an inverse

  std::unique_ptr<xla::PjRtClient> pjrt_client_;
  xla::PjRtDevice* device_;
  absl::BitGen bitgen_;
};

TEST_F(ConvertTfQuantToMhloIntTest, UniformQuantizeAndDequantizeToValidGraph) {
  constexpr absl::string_view kProgram = R"mlir(
func.func @main(%arg0: tensor<10xf32>) -> tensor<10xf32> {
  %scale = "tf.Const"() { value = dense<0.347> : tensor<f32> } : () -> tensor<f32>

namespace mlir {
namespace TFTPU {
namespace {
constexpr char kStepMarkerLocationAttr[] = "step_marker_location";
constexpr char kUseXlaSpmdAttr[] = "use_spmd_for_xla_partitioning";

constexpr char kBadStringArrayElementMsg[] =
    "bad '{0}' attribute at index {1}, not a string";
constexpr char kBadArrayElementMsg[] =
    "bad '{0}' attribute at index {1} with value '{2}': failed to parse to {3}";
constexpr char kBadArrayAttrLengthMsg[] =

using ::testing::SizeIs;
using ::testing::StrEq;
using ::tsl::protobuf::util::MessageDifferencer;
using ::tsl::testing::IsOk;
using ::tsl::testing::StatusIs;

using LiftAsFunctionCallTest = QuantizationTestBase;

constexpr absl::string_view kModuleLifted = R"mlir(
  module {

#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"

namespace mlir {
namespace TFL {

namespace {

constexpr char kNgrams[] = "tftext:Ngrams";
constexpr char kWhitespaceTokenizer[] = "tftext:WhitespaceTokenizer";
constexpr char kCustomSgnnProjection[] = "tftext:custom:SgnnProjection";
constexpr char kTFImplements[] = "tf._implements";

using mlir::TF::FuncAttr;
using mlir::TF::StringType;