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From "Ngin Yun Chuan (JIRA)" <>
Subject [jira] [Commented] (SINGA-443) Rafiki--How to debug rafiki efficiently.
Date Sun, 21 Apr 2019 12:45:00 GMT


Ngin Yun Chuan commented on SINGA-443:

Hi Liu Hui,

Sorry for the delayed response.

You can check out the documentation in
In particular, you can the method `rafiki.model.test_model_class()` that is supposed to help
simulate a full train-inference flow in Python & check for any errors, before submitting
it to Rafiki proper. 

Still, I think we could make the debugging process more efficient, ideally establishing an
efficient local model testing/debugging/development environment, and that will be something
we'll be working on in the future. In the meantime, will appreciate if you can let us know
the headaches you face during model development right now, and we'll be sure to account for
these headaches when we roll out such a feature to assist model developers.

Yun Chuan

> Rafiki--How to debug rafiki efficiently.
> ----------------------------------------
>                 Key: SINGA-443
>                 URL:
>             Project: Singa
>          Issue Type: Wish
>            Reporter: Liu Hui
>            Priority: Major
> Recently,I try to add a model in Rafiki,such as task of image classification or image
> I just type the code as example's, but some error came out and confused me.
> I upload the model to Rafiki, start a train job, and then check the log file to fix these
errors, or enter a worker's docker to debug program with adding print.
> This method would be so inefficient.
> Are there any tutorials about how to debug Rafiki with IDE or any other methods which
can improve efficiency of debugging.   

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