This PR solves #97 by adding a single entrypoint so that one can run any experiment simply with python sheeprl.py exp=... fabric=.... Now the @register_algorithm(decoupled: bool)-decorated entrypoint will always receive the Fabric object and the hydra cfg to be used later in the specific implementation.
With these changes there's no more the need to run an experiment with lightning run model sheeprl.py ..., instead if one wants to modify the Fabric parameters then he/she can override them through the cli with python sheeprl.py ecp=... fabric.devices=2 fabric.accelerator=gpu fabric.num_nodes=2 or modify them directly in the configs under sheeprl/configs/fabric/.
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Summary
This PR solves #97 by adding a single entrypoint so that one can run any experiment simply with
python sheeprl.py exp=... fabric=...
. Now the@register_algorithm(decoupled: bool)
-decorated entrypoint will always receive theFabric
object and the hydracfg
to be used later in the specific implementation.With these changes there's no more the need to run an experiment with
lightning run model sheeprl.py ...
, instead if one wants to modify theFabric
parameters then he/she can override them through the cli withpython sheeprl.py ecp=... fabric.devices=2 fabric.accelerator=gpu fabric.num_nodes=2
or modify them directly in the configs undersheeprl/configs/fabric/
.Type of Change
Please select the one relevant option below:
Checklist
Please confirm that the following tasks have been completed:
Thank you for your contribution! Once you have filled out this template, please ensure that you have assigned the appropriate reviewers and that all tests have passed.