std::unique_ptr<ParallelTensor> reduced_values =
      parallel_device.ScalarsFromSequence<float>({1.0, 2.0}, context.get(),
                                                 status.get());
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());
  std::unique_ptr<ParallelTensor> run_collective =
      parallel_device.ScalarsFromSequence<bool>({true, true}, context.get(),

  // Construct a parallel tensor consisting of the scalar values from `values`.
  template <typename DataType>
  std::unique_ptr<ParallelTensor> ScalarsFromSequence(
      absl::Span<const DataType> values, TFE_Context* context,
      TF_Status* status) const;

  // A parallel tensor with scalar integers numbering component devices.

  std::vector<int32_t> ids;
  ids.reserve(num_underlying_devices());
  for (int i = 0; i < num_underlying_devices(); ++i) {
    ids.push_back(i);
  }
  return ScalarsFromSequence<int32_t>(ids, context, status);
}

absl::optional<std::vector<std::unique_ptr<ParallelTensor>>>
ParallelDevice::Execute(TFE_Context* context,
                        const std::vector<ParallelTensor*>& inputs,