code: def setup_task(cls, cfg):
      run_cfg = cfg.run_cfg
  
      num_beams = run_cfg.get("num_beams", 5)
      max_len = run_cfg.get("max_len", 30)
      min_len = run_cfg.get("min_len", 1)
      repetition_penalty = run_cfg.get("repetition_penalty", 1.15)
      length_penalty = run_cfg.get("length_penalty", 0.0)
      top_p = run_cfg.get("top_p", 0.9)
      temperature = run_cfg.get("temperature", 1.0)
      evaluate = run_cfg.evaluate
  
      report_metric = run_cfg.get("report_metric", True)
      annotation_file = run_cfg.get("annotation_file", None)
      sample_id_key = run_cfg.get("sample_id_key", "image_id")
      caption_key = run_cfg.get("caption_key", "caption")
      load_gt_from_file = run_cfg.get("load_gt_from_file", False)
      split = run_cfg.get("valid_splits", ["val"])
      img_ids = run_cfg.get(
          "img_ids", []
      )  # evaluate only subset of imgs
  
      return cls(
          num_beams=num_beams,
          max_len=max_len,
          min_len=min_len,
          repetition_penalty=repetition_penalty,
          length_penalty=length_penalty,
          top_p=top_p,
          temperature=temperature,
          evaluate=evaluate,
          report_metric=report_metric,
          annotation_file=annotation_file,
          sample_id_key=sample_id_key,
          caption_key=caption_key,
          split=split,
          load_gt_from_file=load_gt_from_file,
          img_ids=img_ids,
      )
  
imports: import json
  import os
  import pandas
  from tqdm import tqdm
  from lavis.common.dist_utils import main_process, get_rank
  from lavis.common.registry import registry
  from lavis.tasks.base_task import BaseTask
  from lavis.common.utils import is_convertible_to_int, is_url, cache_url
  from pycocoevalcap.eval import COCOEvalCap
  from pycocotools.coco import COCO
  from torchvision.datasets.utils import download_url
label_desc: Use image node_id 2 for calling the CaptionTask obj's underlying member method code with example usage: obj.setup_task(cls, cfg) and returns: cls