tensorflow::AttrValue* attr_value, TF_Status* s);

// Returns a sorted vector of std::pair<function_name, gradient_func> from
// graph_def.library().gradient()
std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def);

// Returns a sorted vector of names contained in `grad_def`
std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def);

class CSession {
 public:

  ASSERT_EQ(0, GetGradDefs(gdef).size());

  // Make grad_func a gradient of func
  TF_GraphCopyFunction(host_graph_, func, grad_func, s_);
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

  // Verify that function and its grad are linked
  gdef.Clear();
  GetGraphDef(host_graph_, &gdef);
  std::vector<std::pair<string, string>> grads = GetGradDefs(gdef);
  ASSERT_EQ(1, grads.size());

  bool ret = TF_GetCode(s) == TF_OK;
  if (ret) ret = attr_value->ParseFromArray(buffer->data, buffer->length);
  TF_DeleteBuffer(buffer);
  return ret;
}

std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def) {
  std::vector<std::pair<string, string>> grads;
  for (const tensorflow::GradientDef& grad : graph_def.library().gradient()) {