// least one input of the op is watched and has trainable dtype.
  //
  // op_type is used to decide which of the incoming gradients can be left as
  // nullptr instead of building zeros when build_default_zeros_grads == true.
  void RecordOperation(
      const string& op_type, const std::vector<TapeTensor>& output_tensors,
      absl::Span<const int64_t> input_tensor_id,

// variables.
//
// The returned TF_WhileParams will have all fields initialized except
// `cond_output`, `body_outputs`, and `name`. The `body_outputs` buffer will be
// allocated to size `ninputs`. The caller should build `cond_graph` and
// `body_graph` starting from the inputs, and store the final outputs in
// `cond_output` and `body_outputs`.
//
// If `status` is OK, the caller must call either TF_FinishWhile or

  // "out_tensor".
  void GetTensor(const string& name,
                 std::unique_ptr<tensorflow::Tensor>* out_tensor,
                 TF_Status* out_status) const;

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.
  // REQUIRES: "v2_reader_ != nullptr && v2_reader_.status().ok()".
  std::pair<std::unique_ptr<TensorSliceReader::VarToShapeMap>,