// The main function's name in the serialized stablehlo module embedded in
// XlaCallModule's `module` attribute.
constexpr llvm::StringRef kStablehloMainFunctionName = "main";

// After deserializing the stablehlo functions from XlaCallModule,
// this XlaCallModule attribute refers to the deserialized stablehlo main
// function.
constexpr llvm::StringRef kStablehloEntryFunctionAttrName = "_entry_function";

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";

namespace mlir {
namespace TFL {
namespace tac {
namespace {
// CPU
constexpr float kCPUArithmeticUnitCost = 1.0;

// This basically assumes pure load/store. This is just fake data.
constexpr float kCPUCopyUnitCost = 0.5;

// Default values.
constexpr float kCPUDefaultFixedValuedCost = 10000.0;

// Quantized inference cost efficiency.

// with existing function's name.
inline constexpr StringRef kTfQuantSaveFuncName = "tf_quant__save";

// Name of the TensorFlow Operation to be fetched to save the variables to
// checkpoint. This save op follows the SavedModel's load semantics, so it
// should return the file prefix of the checkpoint as a string tensor.
inline constexpr StringRef kTfQuantSaveOpName = "tf_quant__save_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);

// to represent calling a TF host callback function.
constexpr llvm::StringRef kTfTargetName = "tf.call_tf_function";

// `tf.backend_config` is a DictionaryAttr, JAX2TF sets the value of its
// string attribute `caller_name` to the TF host callback function's name.
constexpr llvm::StringRef kTfBackendConfigAttrName = "tf.backend_config";
constexpr llvm::StringRef kCalledFuncAttrName = "called_func";

}  // namespace

#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/MLIRContext.h"  // from @llvm-project

namespace tensorflow {
namespace quantization {

inline constexpr absl::string_view kTfQuantConstantUnfreezingStepName =
    "tf_quant_constant_unfreezing";
inline constexpr absl::string_view kTfQuantInsertRestoreOpStepName =
    "tf_quant_insert_restore_op";

absl::Status UnfreezeConstantsAndSaveVariables(absl::string_view checkpoint_dir,

 public:
  using Base::Base;
  static constexpr mlir::StringLiteral name = "mlrt.compiler.future";
};

// The MLIR type represents a C++ mlrt::Promise.
class PromiseType
    : public mlir::Type::TypeBase<PromiseType, mlir::Type, mlir::TypeStorage> {
 public:
  using Base::Base;
  static constexpr mlir::StringLiteral name = "mlrt.compiler.promise";
};