Per-stream processing
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 1.6k
- Forks
- 206
- PR merge metrics
- No merged PRs in 30d
Description
🚀 Feature Request
When I use multiple Streams to create a StreamingDataset, I want to be able to use a different pre-processing function to process the data in each Stream. For example, Stream A needs special label masking while Stream B doesn't.
Motivation
This is commonly needed for multi-task training, for example, UL2 training. Currently, my workaround is to insert a task / source column to those streams and use my own StreamingDataset class to produce labels differently based on the task / source column. However, this requires changes to the materialized datasets.
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 at StreamingDataset and the multi-Stream construction path, then trace how preprocessing is currently applied. Define how each Stream can supply a distinct preprocessing function without changing materialized datasets, and add coverage showing that Stream A and Stream B process their data differently.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100