Comments (4)
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See Also #732
from mlos.
Thanks for compiling a list of tasks/features @bpkroth
Iād also love support for users to be able to
- be able to configure benchmarks from a gui
- Error logs should show the end x lines and parse out potential error lines (user preference)
- be able to monitor active experiments and see which launched experiments have quit before hitting the needed trial repeat number, this can be used as a tracking method
- automated correlation detection / validation between Params and a target metric would be a heaven sent
- for a experiment grid showing pie chart for each part where user can see pending, failed, and success metrics
Essentially if we can map out everything we do into a web ui with no code I think this will be a far better costumer experience for those who may want to create their own benchmarks and their own tuning teams
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I think creating a validation system where controls and optimized configs are done automatically on some level will be super valuable for a webpage
instead on launching many experiments manually we might want to create a system to find and validate a number of configs given a estimated monetary budget
along with this we also need to consider detection of when param selection is ineffective in changing a target metric
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Related Issues (20)
- Add tests for trial scheduling and time resolution granularity
- Storing `is_defaults` causing storage column length issues when too many tunables
- Investigate test breakage with recent asyncssh version
- Resume experiments fail when trying to bulk register previous metrics to the optimizer
- Mlos parallelization: storage schema initialization fails when attempted by many processes concurrently HOT 1
- mlos_bench: if a result.___ value is -1 register trial as FAILED HOT 2
- mlos_bench: add a flag for "deploy if not exists" for Azure ARM templates
- Implement quantization for ConfigSpace >= 1.0
- Split registering multiple configs into a seperate function HOT 3
- LlamaTune inverse_trainsform() produces invalid configuration HOT 1
- mlos_viz: add PCA API
- Add quantized tunable + llamatune tests
- Debug logging hiding real Azure Compute API errors in AzureDeploymentService HOT 2
- Fix issues in AzureFileShareService introduced by #779 HOT 1
- Update mlos_viz to support matplotlib >= 3.9.* HOT 1
- bulk_register can fail when existing trials are all Failed and do not have result columns yet
- Enable Python 3.12 for Linux CI HOT 6
- Latest version of FLAML changes optimization behavior
- Multi-objective optimization configs no longer allow overrides via globals HOT 2
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