if (p != nullptr) {
      p->Unref();
    }
  }
};
}  // namespace internal

// TODO(b/185908092): Make AbstractTensorHandlePtr an IntrusivePtr.
using AbstractTensorHandlePtr =
    std::unique_ptr<AbstractTensorHandle,
                    internal::AbstractTensorHandleDeleter>;

}  // namespace tensorflow

}

absl::Status SetPjRtCBufferToTensor(PJRT_Buffer* c_buffer,
                                    xla::PjRtCApiClient* c_api_client,
                                    Tensor* tensor) {
  auto buffer = std::make_unique<xla::PjRtCApiBuffer>(c_api_client, c_buffer);
  tensorflow::AsyncValueTensor* av_tensor =
      tensorflow::AsyncValueTensor::FromTensor(tensor);
  if (av_tensor == nullptr) {
    TF_ASSIGN_OR_RETURN(

    return nullptr;
  }
  std::vector<std::unique_ptr<tensorflow::Device>> devices;
  status->status = tensorflow::DeviceFactory::AddDevices(
      opts->session_options.options, "/job:localhost/replica:0/task:0",
      &devices);
  if (!status->status.ok()) return nullptr;
  std::unique_ptr<tensorflow::DeviceMgr> device_mgr(
      new tensorflow::DynamicDeviceMgr(std::move(devices)));

struct TracingOperationDeleter {
  void operator()(TracingOperation* p) const {
    if (p != nullptr) {
      p->Release();
    }
  }
};
}  // namespace internal

using TracingOperationPtr =
    std::unique_ptr<TracingOperation, internal::TracingOperationDeleter>;

// This holds the context for the execution: dispatching operations either to an
// MLIR implementation or to a graph implementation.

void DefineFunction(const char* name, TF_Function** func,
                    const char* description = nullptr,
                    bool append_hash = false) {
  std::unique_ptr<TF_Graph, decltype(&TF_DeleteGraph)> func_graph(
      TF_NewGraph(), TF_DeleteGraph);
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> s(TF_NewStatus(),
                                                           TF_DeleteStatus);

  file_block_cache = std::make_unique<RamFileBlockCache>(
      block_size, max_bytes, max_staleness,
      [this](const std::string& filename, size_t offset, size_t buffer_size,
             char* buffer, TF_Status* status) {
        return LoadBufferFromGCS(filename, offset, buffer_size, buffer, this,
                                 status);
      });
  stat_cache = std::make_unique<ExpiringLRUCache<GcsFileStat>>(

  /// cache size accordingly.
  void RemoveBlock(BlockMap::iterator entry) ABSL_EXCLUSIVE_LOCKS_REQUIRED(mu_);

  /// The cache pruning thread that removes files with expired blocks.
  std::unique_ptr<TF_Thread, std::function<void(TF_Thread*)>> pruning_thread_;

  /// Notification for stopping the cache pruning thread.
  absl::Notification stop_pruning_thread_;

  };
  status->status = absl::OkStatus();
}

void TFE_SetLogicalCpuDevices(TFE_Context* ctx, int num_cpus,
                              const char* prefix, TF_Status* status) {
  std::vector<std::unique_ptr<tensorflow::Device>> devices;

  if (prefix == nullptr || strlen(prefix) == 0)
    prefix = "/job:localhost/replica:0/task:0";

  tensorflow::SessionOptions sess_options;

    *   Promoting `tf.data.experimental.ThreadingOptions` API to
        `tf.data.ThreadingOptions` and deprecating the experimental endpoint.
    *   Promoting `tf.data.experimental.unique` API to `tf.data.Dataset.unique`
        and deprecating the experimental endpoint.
    *   Added `stop_on_empty_dataset` parameter to `sample_from_datasets` and
        `choose_from_datasets`. Setting `stop_on_empty_dataset=True` will stop

using ::testing::HasSubstr;

TEST(PARALLEL_DEVICE_LIB, TestOpWithError) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);
  std::unique_ptr<TFE_ContextOptions, decltype(&TFE_DeleteContextOptions)> opts(
      TFE_NewContextOptions(), TFE_DeleteContextOptions);
  std::unique_ptr<TF_Buffer, decltype(&TF_DeleteBuffer)> config(
      TF_CreateConfig(
          /*xla*/ false,