pytorch / pytorch/vision

standardize dataset naming conventions

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module: datasets
Dominant language
Python
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Description

Please standardize at least the naming convention for all datasets when using DataLoader so that data are in loader.dataset.data and labels in loader.dataset.targets.
MWE:

loader_cifar = torch.utils.DataLoader("CIFAR10")
loader_cifar.dataset.data <-- contains the data
loader_cifar.dataset.targets <-- contains targets

loader_svhn = torch.utils.DataLoader("SVHN")
loader_svhn.dataset.data <-- contains the data
loader_svhn.dataset.labels <-- contains targets

This can be really confusing and error prone when developing code to run on multiple datasets.

cc @pmeier

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Research direction

Start by locating the dataset implementations used with torch.utils.DataLoader and inventory whether they expose data with targets or labels. Standardize the dataset attributes so data uses data and labels use targets, then verify the affected datasets and their existing tests consistently use the new names.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
computer-vision, data
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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