text: # dataset settings
  dataset_type = 'CIFAR10'
  img_norm_cfg = dict(
      mean=[125.307, 122.961, 113.8575],
      std=[51.5865, 50.847, 51.255],
      to_rgb=True)
  train_pipeline = [
      dict(type='RandomCrop', size=32, padding=4),
      dict(type='RandomFlip', flip_prob=0.5, direction='horizontal'),
      dict(type='Normalize', **img_norm_cfg),
      dict(type='ImageToTensor', keys=['img']),
      dict(type='ToTensor', keys=['gt_label']),
      dict(type='Collect', keys=['img', 'gt_label'])
  ]
  test_pipeline = [
      dict(type='Normalize', **img_norm_cfg),
      dict(type='ImageToTensor', keys=['img']),
      dict(type='Collect', keys=['img'])
  ]
  data = dict(
      samples_per_gpu=16,
      workers_per_gpu=2,
      train=dict(
          type=dataset_type, data_prefix='data/cifar10',
          pipeline=train_pipeline),
      val=dict(
          type=dataset_type,
          data_prefix='data/cifar10',
          pipeline=test_pipeline,
          test_mode=True),
      test=dict(
          type=dataset_type,
          data_prefix='data/cifar10',
          pipeline=test_pipeline,
          test_mode=True))
  