ray.tune.Trainable.default_resource_request
ray.tune.Trainable.default_resource_request#
- classmethod Trainable.default_resource_request(config: Dict[str, Any]) Optional[ray.tune.execution.placement_groups.PlacementGroupFactory] [source]#
Provides a static resource requirement for the given configuration.
This can be overridden by sub-classes to set the correct trial resource allocation, so the user does not need to.
@classmethod def default_resource_request(cls, config): return PlacementGroupFactory([{"CPU": 1}, {"CPU": 1}]])
- Parameters
config[Dict[str – The Trainable’s config dict.
Any]] – The Trainable’s config dict.
- Returns
- A PlacementGroupFactory consumed by Tune
for queueing.
- Return type