code: def update(self, predictions):
      img_ids = list(np.unique(list(predictions.keys())))
      self.img_ids.extend(img_ids)
  
      results = self.prepare_for_lvis_detection(predictions)
      self.predictions.extend(results)
  
imports: import copy
  import itertools
  import logging
  from typing import List
  import numpy
  import pycocotools.mask
  import torch
  import torch.distributed
  from lvis import LVISEval, LVISResults, LVIS
label_desc: Use image node_id 2 for calling the LvisEvaluator obj's underlying member method code with example usage: obj.update(predictions) without return types