using tpu::FunctionToHloArgs;
using tpu::MlirToHloArgs;
using tpu::ShardingAndIndex;
using tpu::TPUCompileMetadataProto;

static constexpr char kCompilationTimeStreamzName[] =
    "/tensorflow/core/tf2xla/api/v2/phase2_compilation_time";
static constexpr char kFullBridge[] = "full_bridge";
static constexpr char kCompilationStatusStreamzName[] =
    "/tensorflow/core/tf2xla/api/v2/phase2_compilation_status";

using ::testing::IsEmpty;
using ::testing::IsNull;
using ::testing::NotNull;
using ::testing::Optional;
using ::tsl::testing::StatusIs;

using AttrsAndConstraintsTest = ::mlir::quant::QuantizationTestBase;

constexpr absl::string_view kModuleStatic = R"mlir(
  module {
    func.func @main(%arg0: tensor<1x1024xf32>, %arg1: tensor<1024x3xf32>) -> tensor<1x3xf32> attributes {_from_xla_call_module} {

using ::testing::SizeIs;
using ::testing::StrEq;
using ::tsl::protobuf::util::MessageDifferencer;
using ::tsl::testing::IsOk;
using ::tsl::testing::StatusIs;

using LiftAsFunctionCallTest = QuantizationTestBase;

constexpr absl::string_view kModuleLifted = R"mlir(
  module {

    {tsl::monitoring::Buckets::Exponential(1, 1.5, 45)});

// There were no MLIR ops so the old bridge was called successfully.
constexpr char kOldBridgeNoMlirSuccess[] = "kOldBridgeNoMlirSuccess";
// There were no MLIR ops so the old bridge was called but it failed.
constexpr char kOldBridgeNoMlirFailure[] = "kOldBridgeNoMlirFailure";

namespace {

// Time the execution of kernels (in CPU cycles). Meant to be used as RAII.

// `tf.backend_config` is a DictionaryAttr, JAX2TF sets the value of its
// i64 attribute `called_index` to the TF function's name.
constexpr llvm::StringRef kTfBackendConfigAttrName = "tf.backend_config";
constexpr llvm::StringRef kCalledIndexAttrName = "called_index";
constexpr llvm::StringRef kCalledFuncAttrName = "called_func";

// Deserialize the StableHLO module embedded in XlaCallModuleOp's module
// attribute.

// Device coordinates are defined as (x, y, z, core), thus resulting in a rank 4
// topology.
constexpr int kTPUTopologyRank = 4;

constexpr char kDeviceTPUSystem[] = "TPU_SYSTEM";
constexpr char kDeviceTPU[] = "TPU";
constexpr char kTPUReplicatedCore[] = "TPU_REPLICATED_CORE";
constexpr char kTPUReplicatedHost[] = "TPU_REPLICATED_HOST";
constexpr char kBadIntArrayElementMsg[] =
    "bad '{0}' attribute at index {1}, not an int";

namespace tensorflow {
namespace internal {
namespace {

using ::tensorflow::quantization::PyFunctionLibrary;
using ::tflite::optimize::ReducedPrecisionSupport;

// Op def string for TFLite_Detection_PostProcess Op.
constexpr mlir::StringRef kDetectionPostProcessOp =
    "name: 'TFLite_Detection_PostProcess' input_arg: { name: "
    "'raw_outputs/box_encodings' type: DT_FLOAT } input_arg: { name: "

using ::tsl::protobuf::TextFormat;

// Default version number for native serialization.
constexpr int64_t kDefaultVersion = 9;
// Default platform for XlaCallModuleOp.
constexpr StringRef kPlatformCpu = "CPU";
// Name of `tf.XlaCallModule`'s dictionary attribute for keeping the
// deserialized stablehlo module's attributes.
constexpr StringRef kStablehloModuleAttrsAttrName = "_stablehlo_module_attrs";

using mlir::SymbolTable;
using mlir::Value;
using mlir::func::FuncOp;
using tsl::StatusOr;

namespace {

constexpr char kDeviceAttr[] = "tf.device";
constexpr char kResourceArgUniqueIdAttr[] = "tf._resource_arg_unique_id";
constexpr char kEntryFuncAttr[] = "tf.entry_function";
constexpr char kAliasingAttr[] = "tf.aliasing_output";

// OpOrArgLocNameMapper that legalizes the returned name.

    "optimization pass",
    /* metric field */ "status");

// The status metric field is used to record success/failure of mlir
// function/graph optimization passes.
constexpr char kSuccess[] = "kSuccess";
constexpr char kFailure[] = "kFailure";

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

// Dumps the MLIR module to disk.