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[feature] Support log-uniform scale in search space definition

Open gaocegege opened this issue 5 years ago • 12 comments

/kind feature

Describe the solution you'd like [A clear and concise description of what you want to happen.]

https://github.com/kubeflow/katib/pull/1205#issuecomment-639200522

Anything else you would like to add: [Miscellaneous information that will assist in solving the issue.]

gaocegege avatar Jun 05 '20 01:06 gaocegege

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issue-label-bot[bot] avatar Jun 05 '20 01:06 issue-label-bot[bot]

/cc @sperlingxx @andreyvelich

gaocegege avatar Jun 05 '20 01:06 gaocegege

@gaocegege In my opinion, we need to add additional field Distribution in FeasibleSpace. The FeasibleSpace definition could be changed to:

type ParameterDistribution string

const (
	Uniform    ParameterDistribution = "uniform"
	LogUniform ParameterDistribution = "log_uniform"
	Normal     ParameterDistribution = "normal"
	LogNormal  ParameterDistribution = "log_normal"
	Discrete   ParameterDistribution = "discrete"
)

type FeasibleSpace struct {
	Max          string                `json:"max,omitempty"`
	Min          string                `json:"min,omitempty"`
	List         []string              `json:"list,omitempty"`
	Step         string                `json:"step,omitempty"`
	Distribution ParameterDistribution `json:"distribution,omitempty"`
}

sperlingxx avatar Jun 05 '20 05:06 sperlingxx

SGTM. I think it is one possible approach.

gaocegege avatar Jun 05 '20 05:06 gaocegege

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

stale[bot] avatar Nov 24 '20 03:11 stale[bot]

/lifecycle frozen

andreyvelich avatar Nov 24 '20 11:11 andreyvelich

/assign

I will submit a small proposal for this feature.

tenzen-y avatar Dec 02 '22 20:12 tenzen-y

Any updates on this? Would love to be able to search over a log-uniform scale for tuning learning rates

yanwu2014 avatar May 12 '23 23:05 yanwu2014

[WIP] Add enhancement for Parameter Distribution #2059

@yanwu2014 Thank you for being interested in this feature. I'm writing the proposal. But we need to cut a new Experiment API version (v1beta2) since we need to introduce significant and breaking changes.

So it will take a little bit of time to release.

tenzen-y avatar May 15 '23 06:05 tenzen-y

That's great, thanks so much :)!

yanwu2014 avatar May 15 '23 17:05 yanwu2014

/area gsoc

andreyvelich avatar Feb 22 '24 14:02 andreyvelich