[WIP] Equivalence tests #6
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rossviljoen
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Jul 6, 2021
test/equivalences.jl
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| @test all(isapprox.(mean(gpr_post, x), mean(svgp_post, x), atol=1e-3)) | ||
| @test all(isapprox.(cov(gpr_post, x), cov(svgp_post, x), atol=1e-3)) |
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The current state of this is:
Testing equivalence of the exact and sparse mean and cov works (with a fairly large tolerance of 1e-3) when only optimising the sparse variational posterior. Optimising kernel parameters at the same time does not give consistent enough behaviour - possibly need to use a different optimiser?
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Before investigating this further, how about one step simpler - set z=x and then we can determine analytically what we need to set q to for it to be exactly equivalent to GPR (then it should be equal within a very tight tolerance at most ~1e-8 or so in double precision).
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Merging into #9 to put everything in one PR |
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Adds tests which check the equivalence of certain models.
For example, sparse models with inducing inputs == training inputs should recover the exact GP posterior.