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In-flight weight updates were proposed by PipelineRL and allow one to stay near on-policy without tanking throughput:
It was also validated in the ScaleRL paper, that adopting in-flight weight updates dramatically speeds up training by factors of 2-3x over conventional off-by-k training:
I poked around the torchforge codebase and did not see this implemented yet, but think it would be a high impact feature for the open source community to include :)
pbontrager, allenwang28, henripal, tseyde, casteryh and 1 more
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