// 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

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} {

// 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 ::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 {

    "/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 "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;

#include "tensorflow/compiler/mlir/lite/stablehlo/odml_converter/passes.h.inc"

constexpr float kOne = 1.0;
const float kOneOverRoot2 = kOne / std::sqrt(2);
constexpr float kHalf = kOne / 2.0;
constexpr float kTolerance = kOne / 1000.0;

// Gets the operation that uses the sole result of given operation
// if there is only one.
Operation* GetUserIfOnlyOne(Operation* op) {
  if (op->getNumResults() != 1) return nullptr;

    {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.

  // `auto_control_deps.py` where it is assumed that allocated resource values
  // NEVER alias. We should align our assumptions in the future.
  static constexpr int64_t kUnknownResourceId = -1;
  static constexpr int64_t kInvalidResourceId = -2;
  static constexpr int64_t kMaxResourceTypeId = 9999;
};

}  // namespace detail

// An analysis that runs on a module and maps each resource-type value to a