namespace tensorflow {
namespace tracing {
namespace graph {
GraphFunction::GraphFunction(FunctionDef fdef)
    : AbstractFunction(kGraph),
      func_record_(new FunctionRecord(std::move(fdef), {}, true)) {}
GraphFunction::~GraphFunction() {}
absl::Status GraphFunction::GetFunctionDef(const FunctionDef **fdef) {
  *fdef = &(func_record_->fdef());
  return absl::OkStatus();
}
}  // namespace graph

  }
  return v;
}

// Specification for an expected edge.
// src is either:
// - input name (as it appears in FunctionDef)
// - name of output tensor (in nested "add:z:0" format)
// dst is either:
// - output name (as it appears in FunctionDef)
// - <name_of_node>:<index_of_this_input_into_node> (this looks the same as
//      output tensor naming, but it the index is actually an input index)

  // Block until all pending nodes are finished.
  virtual absl::Status AsyncWait() = 0;

  // Add a function (serialized FunctionDef protocol buffer) so that it can
  // be executed as an op. Return error if the function with the same name
  // already exists.
  virtual absl::Status AddFunctionDef(const FunctionDef& fdef) = 0;

  // Notifies about the function removal.
  virtual absl::Status AddRemoveFunctionNotifier(

TF_Function* TF_FunctionImportFunctionDef(const void* proto, size_t proto_len,
                                          TF_Status* status) {
  tensorflow::FunctionDef fdef;
  bool success = fdef.ParseFromArray(proto, proto_len);
  if (!success) {
    status->status = InvalidArgument(
        "Invalid FunctionDef given to TF_FunctionImportFunctionDef");
    return nullptr;
  }

  TF_Function* func = new TF_Function();

//
// If `mutate_proto_func` is non-NULL, run it over each FunctionDef proto,
// before creating a TF_Function out of the possibly mutated proto.
static std::vector<UniqueFuncPtr> CreateFunctionsFromTextProto(
    const char* text_proto,
    std::function<void(FunctionDef*)>* mutate_proto_func, TF_Status* status) {
  tensorflow::GraphDef gdef;

  // available to be called/referenced by its name in this context.
  virtual absl::Status RegisterFunction(AbstractFunction*) = 0;
  // Remove a function. 'func' argument is the name of a previously added
  // FunctionDef. The name is in fdef.signature.name.
  virtual absl::Status RemoveFunction(const string& func) = 0;

 private:
  const AbstractContextKind kind_;
};

namespace internal {
struct AbstractContextDeleter {

bool GetGraphDef(TF_Graph* graph, tensorflow::GraphDef* graph_def);

bool GetNodeDef(TF_Operation* oper, tensorflow::NodeDef* node_def);

bool GetFunctionDef(TF_Function* func, tensorflow::FunctionDef* func_def);

bool GetAttrValue(TF_Operation* oper, const char* attr_name,
                  tensorflow::AttrValue* attr_value, TF_Status* s);

// Returns a sorted vector of std::pair<function_name, gradient_func> from

#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

namespace {

using ::tensorflow::string;

// Add the values of three variables on three different tasks.
string AddVariablesFunction() {
  tensorflow::FunctionDef def;
  CHECK(tensorflow::protobuf::TextFormat::ParseFromString(
      "    signature {"
      "      name: 'AddVariablesFunction'"
      "      input_arg {"
      "        name: 'var'"
      "        type: DT_RESOURCE"

#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

using ::tensorflow::string;

string MatMulFunction(const string& matmul_device) {
  tensorflow::FunctionDef def;
  CHECK(tensorflow::protobuf::TextFormat::ParseFromString(
      absl::StrCat("    signature {"
                   "      name: 'MatMulFunction'"
                   "      input_arg {"

  if (ret) ret = node_def->ParseFromArray(buffer->data, buffer->length);
  TF_DeleteBuffer(buffer);
  TF_DeleteStatus(s);
  return ret;
}

bool GetFunctionDef(TF_Function* func, tensorflow::FunctionDef* func_def) {
  TF_Status* s = TF_NewStatus();
  TF_Buffer* buffer = TF_NewBuffer();
  TF_FunctionToFunctionDef(func, buffer, s);
  bool ret = TF_GetCode(s) == TF_OK;
  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);