CSession::~CSession() {
  TF_Status* s = TF_NewStatus();
  CloseAndDelete(s);
  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_DeleteStatus(s);
}

void CSession::SetInputs(
    std::vector<std::pair<TF_Operation*, TF_Tensor*>> inputs) {
  DeleteInputValues();
  inputs_.clear();
  for (const auto& p : inputs) {
    inputs_.emplace_back(TF_Output{p.first, 0});

		}
	case *matcher.Matcher_OnMatch_Matcher:
		ms, f := recurse(name, v.Matcher)
		if !f {
			return []string{"NONE"}, true
		}
		return ms, true
	}
	// TODO support list
	n := match.GetMatcherTree().GetInput().GetName()

	var m map[string]*matcher.Matcher_OnMatch
	equality := "="
	switch v := match.GetMatcherTree().GetTreeType().(type) {
	case *matcher.Matcher_MatcherTree_ExactMatchMap:
		m = v.ExactMatchMap.Map

  // Create a session for this graph.
  CSession csession(graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Run the graph.
  csession.SetInputs({{feed, Int32Tensor(3)}});
  csession.SetOutputs({add});
  csession.Run(s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);
  TF_Tensor* out = csession.output_tensor(0);
  ASSERT_TRUE(out != nullptr);

    // Create a session for this graph
    CSession csession(host_graph_, s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

    // Run
    csession.SetInputs(inputs);
    csession.SetOutputs(outputs);
    csession.Run(s_);
    ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

    // Check results
    for (int i = 0; i < expected_results.size(); ++i) {