pytorch / pytorch/vision

Standardisation of Dataset API split argument name

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enhancement module: datasets needs discussion
Dominant language
Python
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Description

I've noticed some naming inconsistencies across the torchvision datasets when it comes to specifying how to split the dataset (train/val/test). We currently have:

The rest are unspecified - but you can effectively choose the split in them by choosing the root folder (e.g. for COCO).

Is there a reason for different naming conventions for each? If not, is there a case for standardising the argument name to one of the above so it's consistent?

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Research direction

Compare the dataset constructors in lsun.py, sbd.py, voc.py, celeba.py, cityscapes.py, imagenet.py, stl10.py, svhn.py, cifar.py, mnist.py, and usps.py. First determine the preferred split argument and any compatibility implications, then standardize the affected APIs so equivalent dataset splits use one name without changing their behavior.

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Assessment

Tech stack
python
Domain
computer-vision
Issue type
Refactor
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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