GPU-friendly + vectorized pareto ranking #32
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## master #32 +/- ##
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- Coverage 53.28% 52.97% -0.31%
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Higgcz
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Nov 23, 2022
…hat it is now vectorized along the pareto front and uses torch tensors only - Add _compute_pareto_ranks to evotorch.core that computes the rank tensor previously returned by the _pareto_sort_np function, but in a vectorized and GPU-friendly manner - Update _pareto_sort function of evotorch.core so that it uses the new _compute_pareto_ranks function - Update SolutionBatch.arg_pareto_sort() so that it complies with the update _pareto_sort function (crowdsort_upto argument no longer in use) - Add SolutionBatch.compute_pareto_ranks() function which skips the sparse computation of the fronts (useful when not needed) - Update SolutionBatch.take_best() function to use SolutionBatch.compute_pareto_ranks() rather than SolutionBatch.arg_pareto_sort() - Update evotorch.operators.base.CrossOver._do_tournament so that it uses SolutionBatch.compute_pareto_ranks() rather than SolutionBatch.arg_pareto_sort()
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A variety of QOL + performance changes for pareto-ranking related functionality. Together, I've observed performance speedups when running SteadStateGA (NSGA-II) with very large populations (e.g. 3,200), in the order of 20x faster training. In theory, the speedup should be even better on the GPU, which wasn't possible before, but that hasn't been tried out yet.
An overview of the changes:
_compute_pareto_rankstoevotorch.corethat computes the rank tensor previously returned by the_pareto_sort_npfunction, but in a vectorized and GPU-friendly manner_pareto_sortfunction ofevotorch.coreso that it uses the new_compute_pareto_ranksfunctionSolutionBatch.arg_pareto_sort()so that it complies with the update_pareto_sortfunction (crowdsort_uptoargument no longer in use)SolutionBatch.compute_pareto_ranks()function which skips the sparse computation of the fronts (useful when not needed)SolutionBatch.take_best()function to useSolutionBatch.compute_pareto_ranks()rather thanSolutionBatch.arg_pareto_sort()evotorch.operators.base.CrossOver._do_tournamentso that it usesSolutionBatch.compute_pareto_ranks()rather thanSolutionBatch.arg_pareto_sort()