target: patch_flow.dataloader.WebDataModuleFromConfig
params:
  tar_base: ...   # TODO: add path to tar files: path/to/tars
  batch_size: 8
  num_workers: 8
  val_batch_size: 16
  val_num_workers: 1
  multinode: True

  train:
    shards: ...   # TODO: add shards like this: 'train/{000000..999999}.tar'
    shuffle: 100
    image_key: jpg
    rename:
      image: jpg
    dataset_transforms:
      target: patch_flow.data_utils.TransformComposer
      params:
        transforms:
          # crop-size conditioning via RoPE
          - target: patch_flow.data_utils.ResizeCropWithMetaInfo
            params:
              size: 256
              img_key: image
              meta_key: img_meta
          # if available, caption sampling with probs per caption type/length
          - target: patch_flow.data_utils.CaptionSampler
            params:
              out_txt_key: txt
              txt_sampling_cfg:
                txt: 1
                long: 2
                medium: 3
                short: 4
                keywords: 2

  validation:
    shards: ...   # TODO: validation shards:'val/{000000..000100}.tar'
    image_key: jpg
    rename:
      image: jpg
      txt: medium  # use medium caption for val
    image_transforms:
      - target: torchvision.transforms.Resize
        params:
          size: 256
          interpolation: 2
          antialias: True
      - target: torchvision.transforms.CenterCrop
        params:
          size: 256