PascalVOC `trainaug` and `test` dataset

In the DeepLabv3+ paper the authors state the following:

The proposed models are evaluated on the PASCAL VOC 2012 semantic segmentation benchmark [1] which contains 20 foreground object classes and one background class. The original dataset contains 1, 464 (train), 1, 449 (val), and 1, 456 (test) pixel-level annotated images. We augment the dataset by the extra annotations provided by [76], resulting in 10, 582 (trainaug) training images.

  1. What’s the exact PyTorch code to retrieve the trainaug dataset?
  2. The size of trainaug considers also the 1464 images of the PASCAL VOC 2012 dataset?
  3. What’s the exact code to retrieve the test dataset?