opts->tensor_id_data.push_back(src_name);
  const string& src_name_str = opts->tensor_id_data.back();
  // We don't need to store dst's name in tensor_id_data, since `dst` must
  // outlive the ImportGraphDef call.
  opts->opts.input_map[TensorId(src_name_str, src_index)] = ToTensorId(dst);
}

void TF_ImportGraphDefOptionsRemapControlDependency(

        multiple input batches should be computed in parallel. With
        `num_parallel_calls` set, `deterministic` is used to indicate that
        outputs can be obtained in the non-deterministic order.
    *   Options returned by `tf.data.Dataset.options()` are no longer mutable.
    *   tf.data input pipelines can now be executed in debug mode, which

struct TF_AttrBuilder : public tensorflow::AttrBuilder {
  using tensorflow::AttrBuilder::AttrBuilder;
  // The string buffers to make sure that any `attr_name` we pass into
  // `builder->Set()` will outlive the subsequent
  // `TF_AttrBuilderCheckCanRunOnDevice()` call(s) on the same `builder`.
  std::set<std::string> attr_names;
};

TF_AttrBuilder* TF_NewAttrBuilder(const char* op_name) {

//
// Not thread-safe.
template <typename Gradient, typename BackwardFunction, typename TapeTensor>
class ForwardAccumulator {
 public:
  // Does not take ownership of `vspace`, which must outlive the
  // ForwardAccumulator.
  explicit ForwardAccumulator(
      const VSpace<Gradient, BackwardFunction, TapeTensor>& vspace,
      bool use_batch)
      : vspace_(vspace), use_batch_(use_batch) {