EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  }
  TF_DeleteDeviceList(devices);
  TF_DeleteStatus(status);
}

TEST(CAPI, TensorHandle) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);
  TFE_ContextOptions* opts = TFE_NewContextOptions();
  TFE_Context* ctx = TFE_NewContext(opts, status.get());

  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_DeleteExecutor(executor);
  TFE_ContextRemoveFunction(ctx, "AddVariablesFunction", status);
  TFE_DeleteContext(ctx);

  TF_DeleteStatus(status);

  // TODO(b/136478427): Figure out how to correctly shut the server down.
  worker_server1.release();
  worker_server2.release();
}

TEST(CAPI, TestLocalFunctionWithPackedInput) {

// there are more than one), or "" otherwise.
string GPUDeviceName(TF_Session* session) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);
  TF_Status* s = status.get();
  std::unique_ptr<TF_DeviceList, decltype(&TF_DeleteDeviceList)> list(
      TF_SessionListDevices(session, s), TF_DeleteDeviceList);

                             const char* second_device) {
  // Register the custom device
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);
  const char* device_name = "/job:localhost/replica:0/task:0/device:CUSTOM:0";
  std::array<const char*, 2> underlying_devices{first_device, second_device};

  auto result = Join(expected_output_shapes, status);
  if (TF_GetCode(status) != TF_OK) {
    std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> await_status(
        TF_NewStatus(), TF_DeleteStatus);
    // Wait until all pending nodes have completed since they may have a
    // reference to default_cancellation_manager_. We ignore the status return

    std::string bucket, object;
    TF_Status* status = TF_NewStatus();
    ParseGCSPath(test_dir, true, &bucket, &object, status);
    if (TF_GetCode(status) != TF_OK) {
      TF_DeleteStatus(status);
      return "";
    }
    TF_DeleteStatus(status);

    // We add a random value into `test_dir` to ensures that two consecutive
    // runs are unlikely to clash.
    std::random_device rd;
    std::mt19937 gen(rd());

  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);

  TF_Operation* feed = Placeholder(func_graph.get(), s.get());
  TF_Operation* neg = Neg(feed, func_graph.get(), s.get());

      return errors::InvalidArgument("AbstractOp is incomplete.");
    }
    TF_Status* s = TF_NewStatus();
    auto* operation = TF_FinishOperation(tf_opdesc, s);
    TF_RETURN_IF_ERROR(StatusFromTF_Status(s));
    TF_DeleteStatus(s);
    *num_retvals = TF_OperationNumOutputs(operation);
    for (int i = 0; i < *num_retvals; ++i) {
      retvals[i] = new GraphTensor({operation, i}, g_);
    }
    return absl::OkStatus();
  }

  ASSERT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);
  TFE_DeleteExecutor(executor);
  if (func) {
    TFE_ContextRemoveFunction(ctx, "MatMulFunction", status);
  }
  TFE_DeleteContext(ctx);

  TF_DeleteStatus(status);

  // TODO(b/136478427): Figure out how to correctly shut the server down.
  worker_server1.release();
  worker_server2.release();

  TF_Status* c_status = TF_NewStatus();
  Status status = OkStatus();
  core_filesystem_ops->init(filesystem.get(), c_status);
  status = Status(c_status->status);
  TF_DeleteStatus(c_status);
  if (!status.ok()) return status;

  // Step 3: Actual registration
  return Env::Default()->RegisterFileSystem(
      info->ops[index].scheme,
      std::make_unique<tensorflow::ModularFileSystem>(