class_docstr: A wrapper of repeated dataset.
  
  The length of repeated dataset will be `times` larger than the original
  dataset. This is useful when the data loading time is long but the dataset
  is small. Using RepeatDataset can reduce the data loading time between
  epochs.
  
  Args:
      dataset (:obj:`Dataset`): The dataset to be repeated.
      times (int): Repeat times.
docstr: Length after repetition.
docstr_tok: ["Length","after","repetition","."]
code: def __len__(self):
      """Length after repetition."""
      return self.times * self._ori_len
  
imports: import bisect
  import math
  from collections import defaultdict
  import numpy
  from mmcv.utils import print_log
  from torch.utils.data.dataset import ConcatDataset
  from .builder import DATASETS
  from .coco import CocoDataset
label_desc: Use image node_id 4 for calling the RepeatDataset obj's underlying member method code with example usage: obj.__len__() and returns: unknown