Fixed mean_cache data extraction for dKG
#2452
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Any idea why the unit test is failing when there is no code change? |
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Noticed main fails the same test so I'm assuming my code works and it's another problem. EDIT: Unit tests aren't passing but neither are the ones in main, so I'll assume this change is what's needed for now. |
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Any news on this PR? I confirm that there is interest in gradient-enabled GPs/BO for several application cases. |
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Issue: dKG in BoTorch no longer works since I last ran it a few months ago. It appears to be from the
mean_cachegoing from size[num_fantasies, 1, 1, num_data]to[num_fantasies, num_fantasies, num_fantasies, num_data]. What this change does is extract the relevant data ofmean_cachewhile keeping the expected shape for the rest of the code (ie.[num_fantasies, 1, num_data]).Not sure about a unit test for this since it depends on having BoTorch's
qKnowledgeGradientclass, among other dependencies.See meta-pytorch/botorch#2137