void CSession::Run(TF_Status* s) {
  if (inputs_.size() != input_values_.size()) {
    ADD_FAILURE() << "Call SetInputs() before Run()";
    return;
  }
  ResetOutputValues();
  output_values_.resize(outputs_.size(), nullptr);

  const TF_Output* inputs_ptr = inputs_.empty() ? nullptr : &inputs_[0];
  TF_Tensor* const* input_values_ptr =
      input_values_.empty() ? nullptr : &input_values_[0];

 private:
  void DeleteInputValues();
  void ResetOutputValues();

  TF_Session* session_;
  std::vector<TF_Output> inputs_;
  std::vector<TF_Tensor*> input_values_;
  std::vector<TF_Output> outputs_;
  std::vector<TF_Tensor*> output_values_;
  std::vector<TF_Operation*> targets_;
};

  TF_Output output{dequeue_op, 0};
  TF_Tensor* ret;
  TF_SessionRun(session, /*run_options*/ nullptr,
                // input related parameters
                /*inputs*/ nullptr, /*input_values*/ nullptr, /*ninputs*/ 0,
                // output related parameters
                /*outputs*/ &output, /*output_values*/ &ret,
                /*noutputs*/ 1,
                /*targets*/ nullptr, /*ntargets*/ 0,

TF_CAPI_EXPORT extern void TF_DeleteSession(TF_Session*, TF_Status* status);

// Run the graph associated with the session starting with the supplied inputs
// (inputs[0,ninputs-1] with corresponding values in input_values[0,ninputs-1]).
//
// Any NULL and non-NULL value combinations for (`run_options`,
// `run_metadata`) are valid.
//
//    - `run_options` may be NULL, in which case it will be ignored; or

      }
      session->graph->mu.unlock();
      status->status = session->session->Extend(std::move(graph_def));
      if (!status->status.ok()) {
        // Contract is we always delete input_values[i].
        return false;
      }
      // Note: session->session is not modified if Extend() fails, so
      // we only set last_num_graph_nodes if it succeeds.
      session->last_num_graph_nodes = num_nodes;