[RLlib; PyTorch] - Add kwargs to torch.nn.parallel.DistributedDataParallel.
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Signed-off-by: simonsays1980 <simon.zehnder@gmail.com>
simonsays1980
requested review from
sven1977 and
ArturNiederfahrenhorst
as code owners
sven1977
reviewed
Aug 22, 2024
| @@ -312,6 +312,8 @@ def __init__(self, algo_class: Optional[type] = None): | |||
| "aot_eager" if sys.platform == "darwin" else "onnxrt" | |||
| ) | |||
| self.torch_compile_worker_dynamo_mode = None | |||
| # Default kwargs for `torch.nn.parallel.DistributedDataParallel`. | |||
| self.torch_ddp_kwargs = {} | |||
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Nice! Thanks for making this generic and not hard-code e.g. the find_unused_parameters flag! :)
sven1977
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Aug 22, 2024
Signed-off-by: simonsays1980 <simon.zehnder@gmail.com>
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Why are these changes needed?
For multi-learner setups we use
torch.nn.parallel.DistributedDataParallelto wrapTorchRLModules. This torch-native class has constructor arguments which so far have not been considered in RLlib's code. These arguments can help users to tune distributed executions (e.g. buffering, static graphs, etc.) and investigate inconsistencies with their custom modules (e.g.find_unused_parameters, etc.).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.