Add additional dataloaders
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enhancement
good first issue
- Dominant language
- Python
- Stars
- 3
- Forks
- 0
- PR merge metrics
- No merged PRs in 30d
Description
There are multiple baselines used in the paper.
- ImageNet
- CIFAR-100
- Oxford-IIIT
- Pets-Oxford
- Flowers-102
- VTAB
- Create a dataset loaders similar to
load_cifar10 - Make the traning script dynamic such that the
argparsetakes<model_name>as an additional argument - Note that the
img_sizein ViT model initialization at train.py is statically set as 32. You need to infer the dimensions at the data loader init. time.
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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 with data_setup.py and the existing load_cifar10 loader, then inspect train.py and its argparse configuration. Add loaders for ImageNet, CIFAR-100, Oxford-IIIT, Pets-Oxford, Flowers-102, and VTAB; done means the training script accepts model_name dynamically and ViT receives the image dimensions inferred during loader initialization.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100