}

TEST(TestUtil, MlirModuleDoesNotHave) {
  constexpr char arbirary_mlir[] = "arbirary_mlir";
  constexpr char bad_mlir[] = "bad_mlir";

  ASSERT_THAT(success(arbirary_mlir), Not(HasMlirModuleWith(bad_mlir)));
}

TEST(TestUtil, MlirModuleDoesNotHaveFiltered) {
  constexpr char arbirary_mlir[] = "arbirary_mlir";
  constexpr char bad_mlir[] = "bad_mlir";

using tpu::TPUCompileMetadataProto;

static constexpr char kMlirLegalizeCount[] =
    "/tensorflow/core/tf2xla/v1/mlir_failed_xla_legalize_tf_count";
static constexpr char kMlirLegalizeErrors[] =
    "/tensorflow/core/tf2xla/v1/mlir_failed_xla_legalize_tf_pass_count";
static constexpr char kBridgeStatusCounter[] =
    "/tensorflow/core/tf2xla/api/v2/phase2_compilation_status";
constexpr char kMlirCombinedMlirSuccess[] = "kMlirCombinedMlirSuccess";

namespace mlir::quant {
namespace {

using ::testing::IsNull;
using ::testing::NotNull;

using FindMainFuncOpTest = ::mlir::quant::QuantizationTestBase;

TEST_F(FindMainFuncOpTest, ReturnsMainFuncOp) {
  constexpr absl::string_view kModuleWithMainFunc = R"mlir(
    module {
      func.func @main() -> () {
        return
      }
    }
  )mlir";

  OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kModuleWithMainFunc);

// for debugging.
inline constexpr absl::string_view kTfQuantPtqPreCalibrationStepName =
    "tf_quant_ptq_pre_calibration";
inline constexpr absl::string_view kTfQuantPtqPostCalibrationStepName =
    "tf_quant_ptq_post_calibration";
inline constexpr absl::string_view kTfQuantQatStepName = "tf_quant_qat";
inline constexpr absl::string_view kTfQuantPtqDynamicRangeStepName =
    "tf_quant_ptq_dynamic_range";

using ::mlir::mhlo::test::GetMlirModuleFromString;
using ::tensorflow::monitoring::testing::CellReader;

constexpr char kNotDynamicFunctionName[] = "kNotDynamicFunction";
constexpr char kDynamicFunctionName[] = "kDynamicFunction";
static constexpr char kDynamismOpCounterStreamzName[] =
    "/tensorflow/core/tf2xla/api/v2/dynamism_op_counter";
static constexpr char kDynamismFunctionCounterStreamzName[] =
    "/tensorflow/core/tf2xla/api/v2/dynamism_function_counter";

// Device types.
inline constexpr llvm::StringRef kTpuDevice = "TPU";
// _xla_outside_compilation
inline constexpr llvm::StringRef kXlaOutsideCompilationAttr =
    "_xla_outside_compilation";
// device attr
inline constexpr llvm::StringRef kDeviceAttr = "device";
// Function attribute to signal that a function should be skipped from TPU
// island outlining. The attribute is set in

using ::tensorflow::monitoring::testing::CellReader;

static constexpr char kFailedLegalizationStreamz[] =
    "/tensorflow/core/tf2xla/mlir_second_phase_failed_legalization_op_count";
static constexpr char kNonStaticOpStreamz[] =
    "/tensorflow/core/tf2xla/mlir_second_phase_non_static_op_count";
static constexpr char kNonStaticOpSkipStreamz[] =
    "/tensorflow/core/tf2xla/mlir_second_phase_non_static_op_skip_count";

// the SessionInitializerOp.
inline constexpr StringRef kTfSavedModelInitializerTypeAttr =
    "tf_saved_model.initializer_type";

// Indicates that the initializer corresponds to the restore op.
inline constexpr StringRef kTfSavedModelInitializerRestoreType = "restore_op";

// Indicates that the initializer corresponds to the init op.
inline constexpr StringRef kTfSavedModelInitializerInitType = "init_op";

 private:
  MLIRContext context_;
  OwningOpRef<ModuleOp> module_;
  std::unique_ptr<mlir::PassManager> pm_;
};

TEST_F(VerifyNoOutsideCompilationMarkersPassTest, PassesValidOps) {
  static constexpr char kMlirModuleStr[] = R"(
  module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 268 : i32}} {
    func.func @main() -> tensor<1xi32> {

#include "mlir/Interfaces/SideEffectInterfaces.h"  // from @llvm-project

namespace mlir {
namespace TFR {

constexpr char kAttrArgumentNameAttr[] = "tfr.name";
constexpr char kAttrArgumentDefaultAttr[] = "tfr.default";
constexpr char kAttrArgumentTypeAttr[] = "tfr.type";

class TFRDialect : public Dialect {
 public:
  explicit TFRDialect(MLIRContext *context);