class_docstr: Base class for anchor optimizer.
  
  Args:
      dataset (obj:`Dataset`): Dataset object.
      input_shape (list[int]): Input image shape of the model.
          Format in [width, height].
      logger (obj:`logging.Logger`): The logger for logging.
      device (str, optional): Device used for calculating.
          Default: 'cuda:0'
      out_dir (str, optional): Path to save anchor optimize result.
          Default: None
class_docstr_tok: ["Base","class","for","anchor","optimizer",".","Args",":","dataset","(","obj",":","`","Dataset","`",")",":","Dataset","object",".","input_shape","(","list","[","int","]",")",":","Input","image","shape","of","the","model",".","Format","in","[","width",",","height","]",".","logger","(","obj",":","`","logging.Logger","`",")",":","The","logger","for","logging",".","device","(","str",",","optional",")",":","Device","used","for","calculating",".","Default",":","'cuda:0'","out_dir","(","str",",","optional",")",":","Path","to","save","anchor","optimize","result",".","Default",":","None"]
code: def optimize(self):
      raise NotImplementedError
  
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 4 for calling the BaseAnchorOptimizer obj's underlying member method code with example usage: obj.optimize() without return types