code: def accumulate_predictions_for_coco(
      coco_results, json_result_file, rm=False
  ):
      path = pathlib.Path(json_result_file)
      if rm and path.exists():
          path.unlink()
      with open(path, "a") as f:
          for s in coco_results:
              f.write(json.dumps(s))
              f.write("\n")
  
imports: import json
  import pathlib
  import zipfile
  import numpy
  from tinygrad.helpers import fetch
  import pycocotools._mask
  from examples.mask_rcnn import Masker
  from pycocotools.coco import COCO
  from pycocotools.cocoeval import COCOeval
label_desc: Use image node_id 8 for calling a global function with example usage: accumulate_predictions_for_coco(coco_results, json_result_file, rm) without return types