if operation_id in operation_ids:
        message = (
            f"Duplicate Operation ID {operation_id} for function "
            + f"{route.endpoint.__name__}"
        )
        file_name = getattr(route.endpoint, "__globals__", {}).get("__file__")
        if file_name:
            message += f" at {file_name}"
        warnings.warn(message, stacklevel=1)
    operation_ids.add(operation_id)

  EXPECT_TRUE(isa<TF::XlaCallModuleOp>(lifted_op));
  EXPECT_EQ(
      mlir::cast<StringAttr>(lifted_op->getAttr("_original_entry_function")),
      "composite_dot_general_fn_1");
  EXPECT_EQ(
      mlir::cast<ArrayAttr>(lifted_dot_general_op->getAttr("precision_config")),
      builder_.getArrayAttr(SmallVector<Attribute>(
          1, mlir::stablehlo::PrecisionAttr::get(

      return false;
    }
    // FusedMatMul kernel does not support grad_a/grad_b attrs
    if ((matmul->hasAttr("grad_a") &&
         mlir::cast<BoolAttr>(matmul->getAttr("grad_a")).getValue()) ||
        (matmul->hasAttr("grad_b") &&
         mlir::cast<BoolAttr>(matmul->getAttr("grad_b")).getValue())) {
      (void)rewriter.notifyMatchFailure(matmul, [&](Diagnostic &diag) {
        diag << "FusedMatMul kernel does not support grad_a/grad_b attrs";

	}
}

func newSecretStore(fakeClient clientset.Interface, clock clock.Clock, getTTL GetObjectTTLFunc, ttl time.Duration) *objectStore {
	return &objectStore{
		getObject:  getSecret(fakeClient),
		clock:      clock,
		items:      make(map[objectKey]*objectStoreItem),
		defaultTTL: ttl,
		getTTL:     getTTL,
	}
}

func getSecretNames(pod *v1.Pod) sets.Set[string] {
	result := sets.New[string]()

                       absl::StrCat("module_", module_name));
  auto parent_module = entry_func->getParentOfType<ModuleOp>();
  auto versions_attr = parent_module->getAttr(kVersionsAttr);
  if (!versions_attr)
    return parent_module.emitError(CreateMissingAttributeMsg(kVersionsAttr));

  module_for_func.get().getOperation()->setAttr(kVersionsAttr, versions_attr);

    cc_type v;                                                           \
    auto* cc_ctx = reinterpret_cast<InferenceContext*>(ctx);             \
    Status s = cc_ctx->GetAttr(attr_name, &v);                           \
    Set_TF_Status_from_Status(status, s);                                \
    if (s.ok()) {                                                        \

    auto range = llvm::make_filter_range(op->getUsers(), [&](Operation *user) {
      bool same_block = user->getBlock() == op->getBlock();
      bool same_device = op->getAttr(kDeviceAttr) == user->getAttr(kDeviceAttr);
      return same_block && same_device && state.IsMember(user);
    });
    return {range.begin(), range.end()};
  }

  // Users of block argument must be in the same block.

mlir::Attribute GetDeviceOfResource(mlir::func::FuncOp func,
                                    mlir::Value resource) {
  if (auto* resource_op = resource.getDefiningOp()) {
    return resource_op->getAttr(kDeviceAttr);
  } else {
    const auto resource_arg = resource.dyn_cast_or_null<BlockArgument>();
    if (resource_arg && (resource_arg.getOwner() == &(func.front()))) {
      return func.getArgAttrOfType<mlir::StringAttr>(

        exclude = set(exclude)
    if isinstance(obj, BaseModel):
        # TODO: remove when deprecating Pydantic v1
        encoders: Dict[Any, Any] = {}
        if not PYDANTIC_V2:
            encoders = getattr(obj.__config__, "json_encoders", {})  # type: ignore[attr-defined]
            if custom_encoder:
                encoders.update(custom_encoder)
        obj_dict = _model_dump(
            obj,
            mode="json",

  auto* defining_op = op->getOperand(operand_index).getDefiningOp();
  for (auto attr : kQuantizationAxisAttrs) {
    if (defining_op->hasAttr(attr)) {
      return defining_op->getAttr(attr);
    }
  }
  // Not found.
  return rewriter.getI64IntegerAttr(-1);
}

LogicalResult CheckIfAttrIs8Bit(const std::string& attr, Operation* op,
                                bool& is_8_bit) {