// Ensure that users of the launch op's results appear after the launch op
  // in order to preserve the dominance property.
  TF::ReorderOpResultUses(launch_op);
}

std::string GetDevice(Operation* op) {
  auto device_attr = op->getAttrOfType<StringAttr>("device");
  return device_attr ? device_attr.getValue().str() : "";
}

bool CanBeIgnoredInCluster(Operation* op) {

  OwningOpRef<ModuleOp> mlir_module;
  auto status =
      tensorflow::DeserializeMlirModule(string, context, &mlir_module);
  if (!status.ok()) {
    return status;
  }
  return mlir_module;
}

std::string GetDevice(Operation* op) {
  auto device_attr = op->getAttrOfType<StringAttr>("device");
  return device_attr ? device_attr.getValue().str() : "";
}

bool CanBeIgnoredInCluster(Operation* op) {

namespace tensorflow {
namespace {

TEST(PjRtTensorBufferUtilTest, MakeTensorFromPjRtBuffer) {
  DeviceSetup device_setup;
  device_setup.AddDevicesAndSetUp({DEVICE_GPU});
  Device* device = device_setup.GetDevice(DEVICE_GPU);
  std::vector<int64_t> dimensions = {2, 3};
  Tensor dest_cpu_tensor(cpu_allocator(), tensorflow::DT_INT32,
                         tensorflow::TensorShape(dimensions));

// Helps set up devices for unit tests.
class DeviceSetup {
 public:
  void AddDevicesAndSetUp(
      const std::vector<std::string>& device_names,
      const std::optional<FunctionDef>& fdef = std::nullopt);
  Device* GetDevice(const string& device_name);
  FunctionLibraryRuntime* flr() { return flr_; }

 private:
  FunctionLibraryRuntime* flr_;
  std::unique_ptr<DeviceMgr> device_mgr_;
  std::unique_ptr<FunctionLibraryDefinition> lib_def_;

      TF_GRAPH_DEF_VERSION, lib_def_.get(), opts,
      /*default_thread_pool=*/nullptr, /*cluster_flr=*/nullptr);
  flr_ = pflr_->GetFLR("/job:localhost/replica:0/task:0/cpu:0");
}

Device* DeviceSetup::GetDevice(const string& device_name) {
  if (device_mgr_ == nullptr) {
    return nullptr;
  }

  string full_device_name = absl::StrCat(
      "/job:localhost/replica:0/task:0/device:", device_name, ":0");
  Device* device;

	err := ioctlPtr(fd, _HIDIOCGRAWUNIQ, unsafe.Pointer(&value[0]))
	return ByteSliceToString(value[:]), err
}

// IoctlIfreq performs an ioctl using an Ifreq structure for input and/or
// output. See the netdevice(7) man page for details.
func IoctlIfreq(fd int, req uint, value *Ifreq) error {
	// It is possible we will add more fields to *Ifreq itself later to prevent
	// misuse, so pass the raw *ifreq directly.

// Name returns the interface name associated with the Ifreq.
func (ifr *Ifreq) Name() string {
	return ByteSliceToString(ifr.raw.Ifrn[:])
}

// According to netdevice(7), only AF_INET addresses are returned for numerous
// sockaddr ioctls. For convenience, we expose these as Inet4Addr since the Port
// field and other data is always empty.

    rewriter.replaceOp(op_to_replace, ValueRange({fused_op}));
    return success();
  }
};

const char kDeviceAttr[] = "device";
const char kDeviceGpu[] = "GPU";

std::optional<std::string> GetDevice(mlir::Operation *op) {
  mlir::StringAttr device = op->getAttrOfType<mlir::StringAttr>(kDeviceAttr);
  if (!device || device.getValue().empty()) {
    return std::nullopt;
  }

      execute_launch.getLoc(), llvm::ArrayRef<Type>{}, reformat_operands);
  WrapOpInLaunch(&builder, execute_launch.getLoc(), reformat_op,
                 execute_launch.getDevice());

  // Build the replicated unformat op after the loop. First prepare building the
  // replicate op.
  llvm::SmallVector<std::pair<ValueRange, Type>, 8> unformat_replicate_operands;

                            entry.value().get(), &builder);

    auto device_list = mlir::cast<ArrayAttr>(
        replicate.getDevices().value().get(execute_launch.getDevice()));
    copy_with_layout->setAttr(kDeviceAttr,
                              device_list.getValue()[entry.index()]);

    entry.value().set(copy_with_layout);
  }
  return true;
}