Which time ratios are supported?
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Description
Hey, I see that in inference image by default you use powers of 2 for interpolation, but also support passing arbitrary "ratio". I'm trying to understand how RIFE is being trained and what are the actual possible inference timestamps.
Do you use random [0, 1] during training or only use powers of 2 as possible options? If powers of 2, what is the largest i can use? The reason i ask is because generally models don't work well for values outside of their training domain, so i'm being very cautious here
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Research direction
No file, test, or entry point is named. Start by locating the inference ratio handling and the training timestamp sampling, then compare the supported values with the powers-of-two defaults. Done means documenting whether arbitrary timestamps are trained, the supported range, and any maximum ratio.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100