code: def __init__(
      self,
      base_path,
      train_file=None,
      dev_file=None,
      test_file=None,
      predict_file=None,
      label_file=None,
      label_list=None,
      train_file_with_header=False,
      dev_file_with_header=False,
      test_file_with_header=False,
      predict_file_with_header=False,
  ):
      if not (train_file or dev_file or test_file):
          raise ValueError("At least one file should be assigned")
      self.base_path = base_path
      self.train_file = train_file
      self.dev_file = dev_file
      self.test_file = test_file
      self.predict_file = predict_file
      self.label_file = label_file
      self.label_list = label_list
  
      self.train_examples = []
      self.dev_examples = []
      self.test_examples = []
      self.predict_examples = []
  
      self.if_file_with_header = {
          "train": train_file_with_header,
          "dev": dev_file_with_header,
          "test": test_file_with_header,
          "predict": predict_file_with_header,
      }
  
      if train_file:
          self._load_train_examples()
      if dev_file:
          self._load_dev_examples()
      if test_file:
          self._load_test_examples()
      if predict_file:
          self._load_predict_examples()
      if self.label_file:
          if not self.label_list:
              self.label_list = self._load_label_data()
          else:
              logger.warning(
                  "As label_list has been assigned, label_file is noneffective"
              )
  
      if self.label_list:
          self.label_index = dict(
              zip(self.label_list, range(len(self.label_list)))
          )
  
imports: import os
  from paddlehub.utils.log import logger
label_desc: Use image node_id 1 to create a new BaseDataset object from inherited base classes: object with example: obj = BaseDataset(base_path, train_file, dev_file, test_file, predict_file, label_file, label_list, train_file_with_header, dev_file_with_header, test_file_with_header, predict_file_with_header)