Apply DALI operations (e.g. pad, normalize) to the entire dataset instead of per batch / per image
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- Dominant language
- C++
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Description
Is it possible to apply DALI operations to the entire dataset instead of per batch / per image? For example, I want to apply the same padding operation all the images in a dataset to increase their size from 32x32 to 40x40 and then train a model using the padded dataset. In this use case, I think repeatedly performing the same operation to all images in a dataset for a high number of epochs may generate unnecessary overhead. Thank you.
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Research direction
Start by tracing how DALI operations are executed per batch or per image and how a dataset is represented across epochs; the issue names no files or tests to begin with. Determine whether dataset-wide padding or normalization can be supported without changing existing per-batch behavior, and define completion around avoiding repeated work while preserving training results.
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Assessment
- Tech stack
- cpp
- 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