StringRef device;
  if (auto attr = op->getAttrOfType<StringAttr>("device")) {
    device = attr.getValue();
  }

  StringRef container;
  if (auto attr = op->getAttrOfType<StringAttr>("container")) {
    container = attr.getValue();
  }

  StringRef shared_name;
  if (auto attr = op->getAttrOfType<StringAttr>("shared_name")) {
    shared_name = attr.getValue();
  }

  return non_const_arg->template hasAttrOfType<StringAttr>(name) &&
         ExplainMatchResult(
             value_matcher,
             non_const_arg->template getAttrOfType<StringAttr>(name).str(),
             result_listener);
}

// Matches an operation that has a FlatSymbolRefAttr whose name is `name` and
// value matches `value_matcher`.
MATCHER_P2(HasSymNameAttr, name, value_matcher,

  auto device = op->getAttrOfType<StringAttr>(kDevice);
  if (device == nullptr || device.getValue().empty()) return std::nullopt;

  return GetCanonicalHardwareName(device.getValue().str());
}

// Get inference type attribute from the operation if available.
inline std::optional<InferenceType> GetInferenceTypeAnnotation(Operation* op) {
  auto inference_type = op->getAttrOfType<StringAttr>(kInferenceType);

  auto result = convert.RewriteFunc();
  EXPECT_FALSE(failed(result));
  fused_lstm_func_.dump();

  // verify transpose
  EXPECT_EQ(
      fused_lstm_func_->getAttrOfType<StringAttr>(kTFImplements).getValue(),
      convert.GetCompositeOpName());
  EXPECT_EQ(fused_lstm_func_.getNumArguments(), 5);
  EXPECT_EQ(fused_lstm_func_.getFunctionType().getNumResults(), 1);

  WalkResult result = module.walk([&](stablehlo::CustomCallOp op) {
    if (!IsTfFuncCustomCall(op)) {
      return WalkResult::advance();
    }

    auto backend_config =
        op->getAttrOfType<DictionaryAttr>(kTfBackendConfigAttrName);
    if (!backend_config) {
      op->emitOpError() << "is missing attribute '" << kTfBackendConfigAttrName
                        << "'";
      return WalkResult::interrupt();

  auto num_cores_per_replica_attr = cluster->getAttrOfType<mlir::IntegerAttr>(
      tensorflow::kNumCoresPerReplicaAttr);
  if (!num_cores_per_replica_attr)
    return cluster.emitOpError(
        CreateMissingAttributeMsg(tensorflow::kNumCoresPerReplicaAttr));
  int num_cores_per_replica = num_cores_per_replica_attr.getInt();

  auto topology_attr = cluster->getAttrOfType<StringAttr>("topology");
  if (!topology_attr)

// anyways.
void UnmarkChildren(ModuleOp module) {
  module->walk([&](Operation* op) {
    if (!op->getAttrOfType<StringAttr>(kXlaOutsideCompilationAttr)) return;
    Operation* iter_op = op;
    bool remove_attr = false;
    while (auto* parent_op = iter_op->getParentOp()) {
      if (parent_op->getAttrOfType<StringAttr>(kXlaOutsideCompilationAttr)) {
        remove_attr = true;
        break;
      }

  op->setAttr(kCost, builder->getF32FloatAttr(cost));
}

// Get the cost annotated with kCost.
inline bool GetCostOnOp(Operation* op, float* cost) {
  auto cost_type = op->getAttrOfType<FloatAttr>(kCost);
  if (cost_type == nullptr) {
    return false;
  }

  *cost = cost_type.getValueAsDouble();
  return true;
}

}  // namespace tac
}  // namespace TFL
}  // namespace mlir

// propagated through.
bool IsSupportedExecutorOp(Operation& op) {
  auto ops_have_same_device = [](Operation* lhs, Operation* rhs) {
    auto lhs_device_attr = lhs->getAttrOfType<StringAttr>(kDeviceAttr);
    auto rhs_device_attr = rhs->getAttrOfType<StringAttr>(kDeviceAttr);
    return (!lhs_device_attr && !rhs_device_attr) ||
           (lhs_device_attr && rhs_device_attr &&

// attribute on the CallOp means what it actually looks for.
constexpr char kInterfaceNameAttr[] = "tac.interface_name";

inline std::optional<std::string> GetInterFaceName(Operation* op) {
  auto name_attr = op->getAttrOfType<StringAttr>(kInterfaceNameAttr);
  if (!name_attr) return std::nullopt;
  return name_attr.getValue().str();
}

}  // namespace tac
}  // namespace TFL
}  // namespace mlir