server_def_0.mutable_default_session_config()->set_isolate_session_state(
      false);
  tensorflow::ServerDef server_def_1 =
      ReplaceTaskInServerDef(server_def_0, /*task_index=*/0);

  // These server defs have task index set to 0.
  string serialized_server_def_0 = server_def_0.SerializeAsString();
  string serialized_server_def_1 = server_def_1.SerializeAsString();

    TF_DeleteAbstractTensor(add_output1);
    TF_DeleteAbstractTensor(add_output2);
    TF_DeleteOutputList(func_outputs);
  }

  /**
   * We traced so far this function:
   *
   *   def two_adds(a, b):
   *     my_add1 = a + b
   *     my_add2 = b + b
   *     return my_add1, my_add2
   *
   * Now we will execute this function with an eager context:
   *

      }
    }
  }
  return found_t && found_n;
}

bool IsNeg(const tensorflow::NodeDef& node_def, const string& input) {
  return node_def.op() == "Neg" && node_def.name() == "neg" &&
         node_def.input_size() == 1 && node_def.input(0) == input;
}

bool GetGraphDef(TF_Graph* graph, tensorflow::GraphDef* graph_def) {
  TF_Status* s = TF_NewStatus();
  TF_Buffer* buffer = TF_NewBuffer();

// Add a function (serialized FunctionDef protocol buffer) to ctx so
// that it can be invoked using TFE_Execute.
TF_CAPI_EXPORT extern void TFE_ContextAddFunctionDef(
    TFE_Context* ctx, const char* serialized_function_def, size_t size,
    TF_Status* status);

// Adds a function (created from TF_GraphToFunction or
// TF_FunctionImportFunctionDef) to the context, allowing it to be executed with

}

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(

    TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len,
    int64_t init_timeout_in_ms, TF_Status* status,
    bool clear_existing_contexts);

// Set server def with retries and timeout. This is helpful for fault-tolerant
// initial connection in high-preemption environments, such as
// ParameterServerStrategy training.
// This API is for experimental usage and may be subject to change.

  // 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 Status AddFunctionDef(const FunctionDef& fdef) = 0;

  // Notifies about the function removal.
  virtual Status AddRemoveFunctionNotifier(const string& func,
                                           std::function<void()> notifier) = 0;

tensorflow::ServerDef GetServerDef(const string& job_name, int num_tasks) {
  tensorflow::ServerDef server_def;
  server_def.set_protocol("grpc");
  server_def.set_job_name(job_name);
  server_def.set_task_index(0);
  tensorflow::ClusterDef* cluster_def = server_def.mutable_cluster();
  tensorflow::JobDef* job_def = cluster_def->add_job();
  job_def->set_name(job_name);
  for (int i = 0; i < num_tasks; i++) {

                               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 {