Increase DALI adoption by providing a PyTorch dataset wrapper
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Description
Hi DALI team,
Thank you for a wonderfully performant library! I think there is a way to dramatically boost DALI adoption with a couple of pull requests.
PyTorch TorchVision provides many dataset loaders here:
https://pytorch.org/docs/stable/torchvision/datasets.html
TorchVision ImageFolder dataset is the closest to DALI interface. Creating "DALI" loader through a pull request will make this library much easier to use for the PyTorch ecosystem.
ImageFolder code begins here:
https://github.com/pytorch/vision/blob/2f1399e86309fa3c286771176c017fdfaf3ce00e/torchvision/datasets/__init__.py
How do you feel about this idea? Thanks for the feedback!
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the TorchVision ImageFolder dataset documentation and the linked ImageFolder implementation, then compare it with DALI's existing Python dataset interfaces. The work would be complete when DALI provides a PyTorch-facing dataset wrapper with behavior and usage suitable for the ImageFolder ecosystem, but the issue does not define the API or implementation scope.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100