if (otherDevice->device_) {
      return SetDevice(otherDevice->device_);
    }
    return ChangeResult::NoChange;
  }

  void print(raw_ostream &os) const override {
    if (device_) {
      os << "<" << device_ << ">";
    } else {
      os << "<no device>";
    }
  }

  ChangeResult SetDevice(mlir::StringAttr device) {
    bool changed = (device != device_);

  tensorflow::GetXlaDeviceFlags()->tf_xla_enable_xla_devices = true;
  return true;
}();

class DeviceContextTest : public ::testing::Test {
 public:
  void SetDevice(const string& device_type) {
    auto& rollout_config = GetXlaOpsCommonFlags()->tf_xla_use_device_api;
    rollout_config.AllowForDeviceInXlaLaunch(DeviceType(device_type));

#include "tensorflow/core/framework/tensor_testutil.h"
#include "tsl/lib/core/status_test_util.h"

namespace tensorflow {
namespace {

class XlaHostSendRecvDeviceContextTest : public ::testing::Test {
 public:
  void SetDevice(const string& device_type) {
    auto device_factory = DeviceFactory::GetFactory(device_type);
    SessionOptions options;
    std::vector<std::unique_ptr<Device>> devices;
    Status s = device_factory->CreateDevices(

TEST(PjrtCompileUtilTest, CompileToPjRtLoadedExecutable) {
  DeviceSetup device_setup;
  TF_ASSERT_OK_AND_ASSIGN(auto fdef, SampleFuntionAddXY("foo"));
  device_setup.AddDevicesAndSetUp({DEVICE_GPU}, fdef);

  Device* device = device_setup.GetDevice(DEVICE_GPU);
  const XlaPlatformInfo platform_info = XlaPlatformInfoFromDevice(device);

  NameAttrList function;
  function.set_name("foo");

  ResourceMgr resource_mgr("");

        return WalkResult::advance();
      } else if (device_str_attr.getValue() != launch.getDevice()) {
        return launch.emitOpError()
               << "inner op has conflicting 'device' attribute, "
                  "got '"
               << device_str_attr.getValue() << "' but expected '"
               << launch.getDevice() << "'";
      }
    } else {
      return launch.emitOpError()

  // 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;