text: # dataset settings
  data_source = 'ImageNet'
  dataset_type = 'MultiViewDataset'
  img_norm_cfg = dict(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
  # The difference between mocov2 and mocov1 is the transforms in the pipeline
  train_pipeline = [
      dict(type='RandomResizedCrop', size=224, scale=(0.2, 1.)),
      dict(
          type='RandomAppliedTrans',
          transforms=[
              dict(
                  type='ColorJitter',
                  brightness=0.4,
                  contrast=0.4,
                  saturation=0.4,
                  hue=0.1)
          ],
          p=0.8),
      dict(type='RandomGrayscale', p=0.2),
      dict(type='GaussianBlur', sigma_min=0.1, sigma_max=2.0, p=0.5),
      dict(type='RandomHorizontalFlip'),
  ]
  
  # prefetch
  prefetch = False
  if not prefetch:
      train_pipeline.extend(
          [dict(type='ToTensor'),
           dict(type='Normalize', **img_norm_cfg)])
  
  # dataset summary
  data = dict(
      imgs_per_gpu=64,  # total 128 * 2=256
      workers_per_gpu=4,
      drop_last=True,
      train=dict(
          type=dataset_type,
          data_source=dict(
              type=data_source,
              data_prefix='../../scratch/dso/datasets/imagenet/images/train',
              ann_file='../../scratch/dso/datasets/imagenet/meta/train_IN300.txt',
          ),
          num_views=[2],
          pipelines=[train_pipeline],
          prefetch=prefetch,
      ))
  