[train] Fix ScalingConfig(accelerator_type) to request a small fraction of the accelerator label
#44225
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Signed-off-by: Justin Yu <[email protected]>
Signed-off-by: Justin Yu <[email protected]>
matthewdeng
reviewed
Mar 21, 2024
| @@ -206,7 +206,7 @@ def _resources_per_worker_not_none(self): | |||
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| if self.accelerator_type: | |||
| accelerator = f"{RESOURCE_CONSTRAINT_PREFIX}{self.accelerator_type}" | |||
| resources_per_worker.setdefault(accelerator, 1) | |||
| resources_per_worker.setdefault(accelerator, 0.001) | |||
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Can we make this a constant (or use an existing one if it already exists)?
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ray/python/ray/_private/utils.py
Lines 389 to 392 in 2747c80
Seems core team directly use 0.001 here.
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@jjyao cool if we extract this into a constant? Gives it some concrete meaning 🙂
stephanie-wang
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Mar 27, 2024
…tion of the accelerator label (ray-project#44225) Make Ray Train's accelerator type resource request match Ray Core by setting it to a fractional value (0.001). This is needed to fix autoscaling behavior to request the correct number of GPUs. Signed-off-by: Justin Yu <[email protected]>
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Why are these changes needed?
accelerator_typeis currently implemented as a custom resource with a quantity of 1 if an instance has an accelerator of that type. For example, both a machine with 1 A10G GPU and a machine with 4 A10G GPUs will have{"accelerator_type:A10G": 1.0}. This label is just an indicator of whether the machine contains the accelerator, rather than a count of the number of accelerators of that type.This PR makes our accelerator type resource request match Ray Core by setting it to a fractional value (0.001). This is needed to fix autoscaling behavior to request the correct number of GPUs.
Related issue number
Checks
git commit -s) in this PR.scripts/format.shto lint the changes in this PR.method in Tune, I've added it in
doc/source/tune/api/under thecorresponding
.rstfile.