code: def main():
      logger = MMLogger.get_current_instance()
      args = parse_args()
      cfg = args.config
      cfg = Config.fromfile(cfg)
      init_default_scope(cfg.get("default_scope", "mmdet"))
  
      # replace the ${key} with the value of cfg.key
      cfg = replace_cfg_vals(cfg)
  
      # update data root according to MMDET_DATASETS
      update_data_root(cfg)
  
      input_shape = args.input_shape
      assert len(input_shape) == 2
  
      anchor_type = cfg.model.bbox_head.anchor_generator.type
      assert (
          anchor_type == "YOLOAnchorGenerator"
      ), f"Only support optimize YOLOAnchor, but get {anchor_type}."
  
      base_sizes = cfg.model.bbox_head.anchor_generator.base_sizes
      num_anchors = sum([len(sizes) for sizes in base_sizes])
  
      train_data_cfg = cfg.train_dataloader
      while "dataset" in train_data_cfg:
          train_data_cfg = train_data_cfg["dataset"]
      dataset = DATASETS.build(train_data_cfg)
  
      if args.algorithm == "k-means":
          optimizer = YOLOKMeansAnchorOptimizer(
              dataset=dataset,
              input_shape=input_shape,
              device=args.device,
              num_anchors=num_anchors,
              iters=args.iters,
              logger=logger,
              out_dir=args.output_dir,
          )
      elif args.algorithm == "differential_evolution":
          optimizer = YOLODEAnchorOptimizer(
              dataset=dataset,
              input_shape=input_shape,
              device=args.device,
              num_anchors=num_anchors,
              iters=args.iters,
              logger=logger,
              out_dir=args.output_dir,
          )
      else:
          raise NotImplementedError(
              f"Only support k-means and differential_evolution, "
              f"but get {args.algorithm}"
          )
  
      optimizer.optimize()
  
imports: import argparse
  import os.path
  import numpy
  import torch
  from mmengine.config import Config
  from mmengine.fileio import dump
  from mmengine.logging import MMLogger
  from mmengine.registry import init_default_scope
  from mmengine.utils import ProgressBar
  from scipy.optimize import differential_evolution
  from mmdet.registry import DATASETS
  from mmdet.structures.bbox import bbox_cxcywh_to_xyxy, bbox_overlaps, bbox_xyxy_to_cxcywh
  from mmdet.utils import replace_cfg_vals, update_data_root
label_desc: Use image node_id 2 for calling a global function with example usage: main() without return types