namespace ResourceEffects {

struct Variable : ::mlir::SideEffects::Resource::Base<Variable> {
  StringRef getName() final { return "Variable"; }
};

struct Stack : ::mlir::SideEffects::Resource::Base<Stack> {
  StringRef getName() final { return "Stack"; }
};

struct TensorArray : ::mlir::SideEffects::Resource::Base<TensorArray> {
  StringRef getName() final { return "TensorArray"; }
};

static inline absl::string_view StringRefToView(llvm::StringRef ref) {
  return absl::string_view(ref.data(), ref.size());
}

static inline llvm::StringRef StringViewToRef(absl::string_view view) {
  return llvm::StringRef(view.data(), view.size());
}

namespace tensorflow {

OpOrArgNameMapper::~OpOrArgNameMapper() = default;

llvm::StringRef OpOrArgNameMapper::GetUniqueName(llvm::StringRef prefix,

// 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";

// SavedModel loader attaches the prefix for you during loading.
StringRef MaybeStripAssetDirectoryPrefix(const StringRef filename) {
  if (filename.find("assets/") == 0) {
    return filename.drop_front(7);
  } else {
    return filename;
  }
}

AssetFileDef CreateAssetFileDef(const StringRef filename,
                                const StringRef tensor_name) {
  AssetFileDef asset_file_def{};

namespace mlir {
namespace quant {
namespace {

constexpr StringRef kSharedNameAttr = "shared_name";

class LiftHashTableOpsAsArgsPass
    : public PassWrapper<LiftHashTableOpsAsArgsPass, OperationPass<ModuleOp>> {
 public:
  MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(LiftHashTableOpsAsArgsPass)
  explicit LiftHashTableOpsAsArgsPass() = default;

  StringRef getArgument() const final {

// bridge pipeline or non TPU bridge pipeline.
tensorflow::Status RunTFXLABridge(
    ModuleOp module,
    llvm::function_ref<void(OpPassManager &pm)> pipeline_builder,
    llvm::StringRef module_name = llvm::StringRef(),
    llvm::StringRef dump_prefix = "tf_xla_bridge_v2") {
  // Explicitly check that the TensorFlow dialect can constant fold ops.
  // Constant folding is essential for the bridge. Without this check, the

#include "tensorflow/compiler/mlir/tensorflow/transforms/passes.h"

namespace mlir {
namespace TF {
namespace {

// Location attribute.
constexpr StringRef kClassAttr = "_class";
constexpr StringRef kSharedNameAttr = "shared_name";
constexpr StringRef kLocationPrefix = "loc:@";

#define GEN_PASS_DEF_CONVERTREADONLYREFERENCEVARIABLESTORESOURCEVARIABLESPASS
#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.h.inc"

// CHECK-LABEL: func @testTFDialect
func.func @testTFDialect(%arg0: tensor<4x?x!tf_type.stringref>) -> tensor<4x2x!tf_type.string> {
  %0 = "tf.Identity"(%arg0) : (tensor<4x?x!tf_type.stringref>) -> tensor<4x2x!tf_type.string>
  func.return %0 : tensor<4x2x!tf_type.string>
}


// -----

func.func @testTFDialect(%arg0: tensor<4x?x!tf_type.stringref>) -> tensor<4x2x!tf_type.string> {

    // Op type is a NameLoc with the ":" suffix.
    StringRef op_type_with_suffix =
        mlir::cast<NameLoc>(locations.front()).getName().strref();
    StringRef op_type =
        op_type_with_suffix.substr(0, op_type_with_suffix.size() - 1);
    new_unit.set_op_type(op_type.str());

    if (isa<NameLoc>(locations.back())) {
      StringRef name_loc_id =

// associated compilation cluster and replication metadata op.
inline constexpr llvm::StringRef kTpuReplicateAttr = "_tpu_replicate";
// 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";