tensorflow / tensorflow/probability
Option to avoid bijector caching
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Description
The current behaviour for tensorflow_probability.bijectors.Bijector is to cache the input to be used if the inverse function is called. I would very much like a keyword being able to turn this caching off to ensure the inverse function of the bijector is always called. Whilst setting the property of _is_injective can accomplish this, you lose other features.
It would be nice to have a parameter for bijector which could avoid using caching and instead explicitly use the inverse function at all times.
Thanks!
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 with tensorflow_probability.bijectors.Bijector and trace how its inverse path uses cached inputs. Determine the appropriate parameter scope and verify that disabling caching always calls the inverse function while preserving the other features affected by _is_injective.
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Assessment
- Tech stack
- tensorflow
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100