def eval_on_holdout(args, action_selection, reg_and_traj_transferer, lfd_env, sim):
    """TODO
    
    Args:
        action_selection: ActionSelection
        reg_and_traj_transferer: RegistrationAndTrajectoryTransferer
        lfd_env: LfdEnvironment
        sim: DynamicSimulation
    """
    holdoutfile = h5py.File(args.eval.holdoutfile, 'r')
    holdout_items = eval_util.get_indexed_items(holdoutfile, task_list=args.tasks, task_file=args.taskfile, i_start=args.i_start, i_end=args.i_end)

    rope_params = sim_util.RopeParams()
    if args.eval.rope_param_radius is not None:
        rope_params.radius = args.eval.rope_param_radius
    if args.eval.rope_param_angStiffness is not None:
        rope_params.angStiffness = args.eval.rope_param_angStiffness

    num_successes = 0
    num_total = 0

    for i_task, demo_id_rope_nodes in holdout_items:
        redprint("task %s" % i_task)
        init_rope_nodes = demo_id_rope_nodes["rope_nodes"][:]
        rope = RopeSimulationObject("rope", init_rope_nodes, rope_params)

        sim.add_objects([rope])
        sim.settle(step_viewer=args.animation)
        
        for i_step in range(args.eval.num_steps):
            redprint("task %s step %i" % (i_task, i_step))
            
            sim_util.reset_arms_to_side(sim)
            if args.animation:
                sim.viewer.Step()
            sim_state = sim.get_state()
            sim.set_state(sim_state)
            scene_state = lfd_env.observe_scene()

            # plot cloud of the test scene
            handles = []
            if args.plotting:
                handles.append(sim.env.plot3(scene_state.cloud[:,:3], 2, scene_state.color if scene_state.color is not None else (0,0,1)))
                sim.viewer.Step()
            
            eval_stats = eval_util.EvalStats()
            
            start_time = time.time()

            if len(scene_state.cloud) == 0:
                redprint("Detected 0 points in scene")
                break

            try:
                (agenda, q_values_root), goal_found = action_selection.plan_agenda(scene_state, i_step)
            except ValueError: #e.g. if cloud is empty - any action is hopeless
                redprint("**Raised Value Error during action selection")
                break
            eval_stats.action_elapsed_time += time.time() - start_time
            
            eval_stats.generalized = True
            num_actions_to_try = MAX_ACTIONS_TO_TRY if args.eval.search_until_feasible else 1
            for i_choice in range(num_actions_to_try):
                if q_values_root[i_choice] == -np.inf: # none of the demonstrations generalize
                    eval_stats.generalized = False
                    break
                redprint("TRYING %s"%agenda[i_choice])

                best_root_action = str(agenda[i_choice])

                start_time = time.time()
                try:
                    test_aug_traj = reg_and_traj_transferer.transfer(GlobalVars.demos[best_root_action], scene_state, plotting=args.plotting)
                except ValueError: # If something is cloud/traj is empty or something
                    redprint("**Raised value error during traj transfer")
                    break
                eval_stats.feasible, eval_stats.misgrasp = lfd_env.execute_augmented_trajectory(test_aug_traj, step_viewer=args.animation, interactive=args.interactive, check_feasible=args.eval.check_feasible)
                eval_stats.exec_elapsed_time += time.time() - start_time
                
                if not args.eval.check_feasible or eval_stats.feasible:  # try next action if TrajOpt cannot find feasible action and we care about feasibility
                     break
                else:
                     sim.set_state(sim_state)

            knot = is_knot(rope.rope.GetControlPoints())
            results = {'scene_state':scene_state, 'best_action':best_root_action, 'values':q_values_root, 'aug_traj':test_aug_traj, 'eval_stats':eval_stats, 'sim_state':sim_state, 'knot':knot, 'goal_found': goal_found}
            eval_util.save_task_results_step(args.resultfile, i_task, i_step, results)
            
            if not eval_stats.generalized:
                assert not knot
                break
            
            if args.eval.check_feasible and not eval_stats.feasible:
                # Skip to next knot tie if the action is infeasible -- since
                # that means all future steps (up to 5) will have infeasible trajectories
                assert not knot
                break
            
            if knot:
                num_successes += 1
                break;
        
        sim.remove_objects([rope])
        
        num_total += 1
        redprint('Eval Successes / Total: ' + str(num_successes) + '/' + str(num_total))
        redprint('Success Rate: ' + str(num_total/float(num_successes)))
dataset/ETHPy150Open rll/lfd/scripts/eval.py/eval_on_holdout/swapped operands of `/`