class_docstr: PicReader
class_docstr_tok: ["PicReader"]
docstr: Args:
      root_path:
      list_file:
      meta:
      transform:
      class_to_id_dict:
      cache_img:
      **kwargs:
docstr_tok: ["Args",":","root_path",":","list_file",":","meta",":","transform",":","class_to_id_dict",":","cache_img",":","*","*","kwargs",":"]
code: def __init__(
      self,
      root_path: str,
      list_file: str,
      meta: bool = False,
      transform: Optional[callable] = None,
      class_to_id_dict: Optional[dict] = None,
      cache_img: bool = False,
      **kwargs,
  ) -> None:
      """
  
      Args:
          root_path:
          list_file:
          meta:
          transform:
          class_to_id_dict:
          cache_img:
          **kwargs:
      """
  
      self.root_path = root_path
      self.list_file = list_file
      self.transform = transform
      self.meta = meta
      self.class_to_id_dict = class_to_id_dict
      self.train_type = kwargs["conf"].get("train_type", "single_label")
      self.class_num = kwargs["conf"].get("class_num", 0)
  
      self._parse_list(**kwargs)
      self.cache_img = cache_img
      self.cache_img_buff = dict()
      if self.cache_img:
          self._get_all_img(**kwargs)
  
imports: import re
  import numpy
  from typing import Dict, List, Optional, Union, Tuple
  import six
  import cv2
  import os
  import paddle
  import paddlehub.vision.transforms
  from PIL import ImageFile
  from auto_augment.autoaug.transform.autoaug_transform import AutoAugTransform
label_desc: Use image node_id 1 to create a new PicReader object from inherited base classes: paddle.io with example: obj = PicReader(root_path, list_file, meta, transform, class_to_id_dict, cache_img)