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[tune] Store sync config/checkpoint config in experiment, trial #29019
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krfricke
merged 10 commits into
ray-project:master
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krfricke:tune/checkpoint-retry-env
Oct 6, 2022
Merged
[tune] Store sync config/checkpoint config in experiment, trial #29019
krfricke
merged 10 commits into
ray-project:master
from
krfricke:tune/checkpoint-retry-env
Oct 6, 2022
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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]>
Signed-off-by: Kai Fricke <[email protected]>
Signed-off-by: Kai Fricke <[email protected]>
krfricke
requested review from
sven1977,
gjoliver,
avnishn,
ArturNiederfahrenhorst,
smorad,
maxpumperla and
kouroshHakha
as code owners
October 4, 2022 18:08
Overall looks good! Thanks for the cleanup. Just need to see the tests are passing.. |
Signed-off-by: Kai Fricke <[email protected]>
Signed-off-by: Kai Fricke <[email protected]>
…/checkpoint-retry-env
xwjiang2010
approved these changes
Oct 5, 2022
gjoliver
approved these changes
Oct 5, 2022
WeichenXu123
pushed a commit
to WeichenXu123/ray
that referenced
this pull request
Dec 19, 2022
…project#29019) This is some clean-up required for future changes to the syncing/checkpointing behavior. At the moment we pass single attributes of these configs to the Experiment class, and then subsequently to the Trial class, from which it is passed on to the trainable. If we extend the configurability in the future (e.g. provide fallback mechanisms in the checkpoint config, or make retry wait times configurable in the sync config), we would have to add more and more attributes to these intermediate classes. Instead, we should just pass and store the full config. As a next follow-up, we can pass these configs to the Trainable. Signed-off-by: Kai Fricke <[email protected]> Signed-off-by: Weichen Xu <[email protected]>
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Signed-off-by: Kai Fricke [email protected]
Why are these changes needed?
This is some clean-up required for future changes to the syncing/checkpointing behavior. At the moment we pass single attributes of these configs to the Experiment class, and then subsequently to the Trial class, from which it is passed on to the trainable. If we extend the configurability in the future (e.g. provide fallback mechanisms in the checkpoint config, or make retry wait times configurable in the sync config), we would have to add more and more attributes to these intermediate classes. Instead, we should just pass and store the full config.
As a next follow-up, we can pass these configs to the Trainable.
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