[tune] Introduce tune.with_resources() to specify function trainable resources #26830
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added 4 commits
July 21, 2022 14:42
Signed-off-by: Kai Fricke <[email protected]>
Signed-off-by: Kai Fricke <[email protected]>
Signed-off-by: Kai Fricke <[email protected]>
Signed-off-by: Kai Fricke <[email protected]>
xwjiang2010
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Jul 21, 2022
| def with_resources( | ||
| trainable, | ||
| resources: Union[ | ||
| Dict[str, float], PlacementGroupFactory, Callable[[dict], PlacementGroupFactory] |
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I am a little hesitant about adding PlacementGroupFactory actually.
We need a better API. How about just plain resources dict for now? Until someone yells at us?
it covers most simple cases.
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We use it for resources_per_trial so it would be a bit odd to leave it out imo.
We could add ScalingConfig here... :-D
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I think we should keep the placement group factory for now - it's a tune concept, it's advanced, but it's the same as in resources_per_trial. I'm happy to deprecate this once we have a good alternative, but then we can deprecate it in all places. Does that sound good?
Signed-off-by: Kai Fricke <[email protected]>
krfricke
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xwjiang2010
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Jul 22, 2022
krfricke
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Signed-off-by: Kai Fricke <[email protected]>
Rohan138
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Jul 28, 2022
…resources (ray-project#26830) We don't have a way to specify resource requirements with the Tuner() API. This PR introduces tune.with_resources() to attach a resource request to class and function trainables. In class trainables, it will override potential existing default resource requests. Signed-off-by: Kai Fricke <[email protected]> Signed-off-by: Rohan138 <[email protected]>
Stefan-1313
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Aug 18, 2022
…resources (ray-project#26830) We don't have a way to specify resource requirements with the Tuner() API. This PR introduces tune.with_resources() to attach a resource request to class and function trainables. In class trainables, it will override potential existing default resource requests. Signed-off-by: Kai Fricke <[email protected]> Signed-off-by: Stefan van der Kleij <[email protected]>
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Why are these changes needed?
We don't have a way to specify resource requirements with the Tuner() API. This PR introduces
tune.with_resources()to attach a resource request to class and function trainables. In class trainables, it will override potential existing default resource requests.Related issue number
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