class_docstr: Meta info class for dict
      
code: def __init__(self, input_element):
      self.type = type(input_element)
      # normal dict or custom class
      random_key = list(input_element.keys())[0]
      if hasattr(input_element, random_key):
          # has attr, is custom class
          # fake a dataclass
          self.class_fn = CustomDict
      else:
          # normal dict
          self.class_fn = dict
      self.length = len(input_element)
      self.keys = list(input_element.keys())
      self.infos = []
      for k in self.keys:
          v = input_element[k]
          info = get_meta_info_from_input(v)
          if isinstance(info, ListMetaDataInfo):
              # list inside dict requires reconstruction
              info.need_reconstruct = True
          self.infos.append(info)
      self.need_reconstruct = True
  
imports: import torch
label_desc: Use image node_id 1 to create a new DictMetaDataInfo object from inherited base classes: object with example: obj = DictMetaDataInfo(input_element)