text: # Copyright (c) OpenMMLab. All rights reserved.
  from mmocr.datasets import UniformConcatDataset
  from mmocr.utils import list_from_file
  
  
  def test_dataset_warpper():
      pipeline1 = [dict(type='LoadImageFromFile')]
      pipeline2 = [dict(type='LoadImageFromFile'), dict(type='ColorJitter')]
  
      img_prefix = 'tests/data/ocr_toy_dataset/imgs'
      ann_file = 'tests/data/ocr_toy_dataset/label.txt'
      train1 = dict(
          type='OCRDataset',
          img_prefix=img_prefix,
          ann_file=ann_file,
          loader=dict(
              type='HardDiskLoader',
              repeat=1,
              parser=dict(
                  type='LineStrParser',
                  keys=['filename', 'text'],
                  keys_idx=[0, 1],
                  separator=' ')),
          pipeline=None,
          test_mode=False)
  
      train2 = {key: value for key, value in train1.items()}
      train2['pipeline'] = pipeline2
  
      uniform_concat_dataset = UniformConcatDataset(
          datasets=[train1, train2], pipeline=pipeline1)
  
      assert len(uniform_concat_dataset) == 2 * len(list_from_file(ann_file))
      assert len(uniform_concat_dataset.datasets[0].pipeline.transforms) != len(
          uniform_concat_dataset.datasets[1].pipeline.transforms)
  