}

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

// 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

// 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
         [ {

          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>,