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docs(frontend): adding a section for most common errors #897

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merged 1 commit into from
Jun 20, 2024

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bcm-at-zama
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@bcm-at-zama bcm-at-zama commented Jun 17, 2024

Adding a list of most common errors with CP. If ever you have other issues you would like to add, don't hesitate to do it or ask me to do it

closes #https://github.com/zama-ai/concrete-internal/issues/719
closes #https://github.com/zama-ai/concrete-internal/issues/508

@cla-bot cla-bot bot added the cla-signed label Jun 17, 2024
@bcm-at-zama bcm-at-zama marked this pull request as draft June 17, 2024 16:01
@bcm-at-zama bcm-at-zama force-pushed the add_most_common_errors branch 7 times, most recently from cf06c1a to 7c4ea8c Compare June 18, 2024 12:00
@bcm-at-zama bcm-at-zama marked this pull request as ready for review June 18, 2024 12:14
@bcm-at-zama bcm-at-zama changed the title docs(frontend): adding a section for most common errors [WIP] docs(frontend): adding a section for most common errors Jun 18, 2024
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CC @umut-sahin and @youben11 , for when you're back. Certainly we'll have merged but it may be interesting to have your review when you are available

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Would be nice to merge that not too late, for Yuxi being able to review it

@bcm-at-zama bcm-at-zama force-pushed the add_most_common_errors branch from 7c4ea8c to 2577cc9 Compare June 18, 2024 16:21
@bcm-at-zama bcm-at-zama force-pushed the add_most_common_errors branch from 2577cc9 to 3a8208f Compare June 18, 2024 16:28
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@BourgerieQuentin BourgerieQuentin left a comment

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That's a great start. We must update it each time a user have an error.

@bcm-at-zama bcm-at-zama merged commit 107c60b into main Jun 20, 2024
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@bcm-at-zama bcm-at-zama deleted the add_most_common_errors branch June 20, 2024 10:20
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@umut-sahin @youben11 : as you are the people with the best knowledge of the frontend (no offense for the others!), could you have a look when you're back and maybe improve / add new typical errors, please?

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Nice start!

**Possible solutions**:
- Try to simplify your circuit
- Use smaller weights,
- Add intermediate PBS to reduce the noise, with identity function `fhe.univariate(lambda x: x)`
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We have fhe.identity(x) which is better in most cases (though it uses reinterpret so it wouldn't work on CRT)

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Maybe we could keep it like this: it's for non power users so let's keep something which is less optimized but works more often, ok?

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4 participants