// Presence of this attribute will mark the function as quantization target.
inline constexpr StringRef kFusedFunctionAttr = "tf_quant.composite_function";
// The keyword to detect if this is a `NullAttribute`.
inline constexpr StringRef kNullAttributeValue = "N/A";

// Prefixes attached to lifted functions.
constexpr StringRef kQuantizedFuncPrefix = "quantized_";
constexpr StringRef kCompositeFuncPrefix = "composite_";

using ::tsl::protobuf::io::ArrayInputStream;

// Empty (default) `QuantizationSpecs` proto.
constexpr absl::string_view kSpecsEmpty = R"pb(specs
                                               [])pb";

// Configure `QuantizationSpecs` to disable quantization for all dot_general
// quantizable units.
constexpr absl::string_view kSpecsDisableAllDotGeneral =
    R"pb(specs
         [ {

namespace mlir {
namespace TFL {
namespace tac {

// The copy can be non-consectutive copy. This is just fake data.
constexpr float kNNAPICopyUnitCost = 0.2;

// Default values.
constexpr float kNNAPIDefaultFixedValuedCost = 10000.0;

constexpr char NNAPIHardware::kId[];  // Define kId.

mlir::RewritePatternSet NNAPIHardware::GetTransformations(
    MLIRContext* context) const {

          TPUPartitionedOpConversionPass> {
  void runOnOperation() override;
};

template <typename T>
LogicalResult ReplacePartitionedOp(IntegerAttr num_cores_per_replica, T op) {
  constexpr bool is_input =
      std::is_same_v<std::decay_t<T>, TF::TPUPartitionedInputOp>;
  static_assert(
      is_input || std::is_same_v<std::decay_t<T>, TF::TPUPartitionedOutputOp>,

namespace {

using ::mlir::MLIRContext;
using ::mlir::ModuleOp;
using ::mlir::OwningOpRef;
using ::mlir::mhlo::test::GetMlirModuleFromString;
using ::tensorflow::monitoring::testing::CellReader;

static constexpr char kHasTpuPartitionedCallStreamzName[] =
    "/tensorflow/core/tf2xla/internal/inference/tpu_partitioned_call";

class InferenceMetricsPassTest : public ::testing::Test {
 protected:

  int64_t operands_size = get_size(inst->getOperandTypes());

  constexpr int kSizeFactor = 2;
// TODO(b/233827625): Remove TF_DISABLE_CONSTANT_FOLDING macro.
#ifdef TF_DISABLE_CONSTANT_FOLDING
  constexpr int64_t kResultsSizeThreshold = 0;
#else
  constexpr int64_t kResultsSizeThreshold = (1 << 23);  // 1 MB
#endif
  constexpr int64_t kOperandsSizeThreshold = (1 << 30);  // 128 MB

    "/tensorflow/core/tf2xla/api/v2/tf_dialect_to_executor_dialect_status",
    "Counts how often a successful export from TF Dialect to Executor Dialect "
    "is",
    "status");

constexpr char kExportSuccess[] = "success";
constexpr char kExportFailed[] = "failed";

namespace {

void AddTfDialectToExecutorPasses(OpPassManager &pm) {
  pm.addPass(mlir::TF::CreateTFRegionControlFlowToFunctional());

#include "tensorflow/compiler/mlir/lite/ir/tfl_ops.h"

namespace mlir {
namespace TFL {

constexpr char kTFImplements[] = "tf._implements";
constexpr char kLstmCellSimple[] = "LSTMCellSimple";
constexpr char kLayerNormalizedLstmCellSimple[] =
    "LayerNormalizedLstmCellSimple";
constexpr char kCoupleInputForgetGates[] = "CoupleInputForgetGates";

    "/tensorflow/core/tf2xla/api/v1/tf_dialect_to_executor_dialect_status",
    "Counts how often a successful export from TF Dialect to Executor Dialect "
    "is",
    "status");

constexpr char kExportSuccess[] = "success";
constexpr char kExportFailed[] = "failed";

namespace {

void AddTfDialectToExecutorPasses(OpPassManager &pm) {
  auto add_pass = [&](std::unique_ptr<Pass> pass) {

#include "tsl/lib/core/status_test_util.h"

namespace tensorflow {
namespace tf2xla {
namespace v2 {
namespace {

constexpr char kExportStreamzName[] =
    "/tensorflow/core/tf2xla/api/v2/tf_dialect_to_executor_dialect_status";
constexpr char kExportSuccess[] = "success";
constexpr char kExportFailed[] = "failed";

using mlir::DialectRegistry;
using mlir::MLIRContext;
using mlir::ModuleOp;
using mlir::OwningOpRef;