return nullptr;
#else
  mutex_lock l(api_def_map->lock);
  if (!api_def_map->update_docs_called) {
    api_def_map->api_def_map.UpdateDocs();
    api_def_map->update_docs_called = true;
  }
  string name_str(name, name_len);
  const auto* api_def = api_def_map->api_def_map.GetApiDef(name_str);
  if (api_def == nullptr) {
    return nullptr;
  }

  for (const FunctionDef& fdef : fdef_lib.function()) {
    // Make a copy so that we can mutate it.
    FunctionDef fdef_to_load = fdef;
    if (mutate_proto_func) {
      (*mutate_proto_func)(&fdef_to_load);
    }
    VLOG(1) << "Adding func to graph: " << fdef_to_load.DebugString();
    std::vector<char> binary_proto_buf(fdef_to_load.ByteSizeLong());
    fdef_to_load.SerializeToArray(binary_proto_buf.data(),

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

    grad_inputs[0] = grad_outputs[0];
    if (grad_inputs[0]) {
      grad_inputs[0]->Ref();
    }
    return absl::OkStatus();
  }
};

// Computes:
//
// @tf.custom_gradient
// def f(input):
//   def grad(grads):
//     return grads[0]
//   return tf.exp(input), grad
// outputs = [f(inputs[0])]
Status ExpWithPassThroughGrad(AbstractContext* ctx,

  tensorflow::GradientDef gdef;
  gdef.set_function_name(func->record->fdef().signature().name());
  gdef.set_gradient_func(grad->record->fdef().signature().name());
  status->status = g->graph.AddGradientDef(std::move(gdef));
}

int TF_GraphNumFunctions(TF_Graph* g) {
  tensorflow::mutex_lock l(g->mu);
  return g->graph.flib_def().num_functions();
}

int TF_GraphGetFunctions(TF_Graph* g, TF_Function** funcs, int max_func,

}

void TFE_ContextAddFunction(TFE_Context* ctx, TF_Function* function,
                            TF_Status* status) {
  auto fdef_or = function->record->mutable_fdef();
  if (!fdef_or.ok()) {
    status->status = fdef_or.status();
    return;
  }

  AnnotateEagerRuntimeConstructionContext(*fdef_or.value());
  status->status = tensorflow::unwrap(ctx)->AddFunctionDefWithStackTraces(

                               TF_Buffer* buf, TF_Status* status) {
  auto* function_def = tensorflow::unwrap(ctx)->FindFunctionDef(function_name);
  if (function_def == nullptr) {
    status->status = tensorflow::errors::NotFound(
        "Unable to find FunctionDef with name: ", function_name);
    return;
  }
  string str = function_def->SerializeAsString();
  void* data = tensorflow::port::Malloc(str.length());

                                   graph_outputs.size(), graph_outputs.data(),
                                   nullptr, nullptr, name_.data(), s);
    *f = new GraphFunction(std::move(func->record->fdef()));
    TF_DeleteFunction(func);
    TF_RETURN_IF_ERROR(StatusFromTF_Status(s));
    TF_DeleteStatus(s);
    return absl::OkStatus();
  }

  Status RegisterFunction(AbstractFunction* func) override {

  tensorflow::GraphDef graph_def_proto;
  ASSERT_TRUE(tensorflow::ParseProtoUnlimited(&graph_def_proto, graph_def->data,
                                              graph_def->length));
  TF_Buffer graph_def_buffer;
  graph_def_buffer.data = reinterpret_cast<const void*>(&graph_def_proto);
  graph_def_buffer.length = sizeof(tensorflow::GraphDef*);
  TF_ImportGraphDefResults* results =