Staged process mode
Open
enhancement
priority: low
- Dominant language
- Python
- Stars
- 253
- Forks
- 59
- PR merge metrics
- No merged PRs in 30d
Description
The resource requirement to run a whole project is often huge, such as loading two or three pytorch models in the GPU. When resource is unavailable, one approach is to always process one engine at a time (and serialize the data on disk). We can support this staged processing mode later.
Contributor guide
Research direction
No files, tests, or entry points are named. Start by examining how Forte runs engines and handles intermediate data, then clarify the staged mode's serialization, resource, and completion behavior. Done criteria would need to specify one-engine-at-a-time execution and how data is persisted between engines.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100