[GENERAL SUPPORT]: Managing Objective Function Evaluation Failures in Ax for MOO

[Fa20]

Question

I'm using Ax to find the optimal solutions for a MOO problem. However, some suggested parameter values cause simulation failures, making it impossible to calculate the objective function. How can we avoid this in Ax? Specifically, how can we abandon these failed trials and obtain new suggestions? Can you provide an example of how to implement this?.

I did check and did not find ax_client.log_trial_failed(trial_index) (#2574)

Please provide any relevant code snippet if applicable.

No response

Code of Conduct

• I agree to follow this Ax's Code of Conduct

[Abrikosoff]

Question

I'm using Ax to find the optimal solutions for a MOO problem. However, some suggested parameter values cause simulation failures, making it impossible to calculate the objective function. How can we avoid this in Ax? Specifically, how can we abandon these failed trials and obtain new suggestions? Can you provide an example of how to implement this?.

I did check and did not find ax_client.log_trial_failed(trial_index) (#2574)

Please provide any relevant code snippet if applicable.

No response

Code of Conduct

* [x]  I agree to follow this Ax's Code of Conduct

I think the correct syntax for logging a trial as failed is ax_client.log_trial_failure(trial_index=trial_index). As to the difference between abandoning and logging trials (as failures), see this comment by Lena

[mpolson64]

Thanks so much @Abrikosoff -- this was indeed a mistake on my part. Please use log_trial_failure as defined here https://github.com/facebook/Ax/blob/main/ax/service/ax_client.py?fbclid=IwZXh0bgNhZW0CMTEAAR0-WRsxfT-7qlc-mKuNOLYftPFO7dB_y1uY75HHuLj8BTxXEWw8EQ979WE_aem_UAXI11RP1Nbkw-OG8XQxIw#L829

@Fa20 does this answer your question?

[mgarrard]

Closing due to inactivity, please feel free to reopen :)