Fix SIR predict() use of reparameterizers #2431
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fritzo
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Apr 22, 2020
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| if args.dct: # Apply the same reparameterizer as during inference. | ||
| rep = DiscreteCosineReparam() | ||
| model = poutine.reparam(model, {"S_aux": rep, "I_aux": rep}) |
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This was the bug: S_aux was being sampled from the prior because the inferred samples only provided S_aux_dct.
fritzo
commented
Apr 22, 2020
| 'sir_hmc.py -t=2 -w=2 -n=4 -d=2 -m=1 --enum', | ||
| 'sir_hmc.py -t=2 -w=2 -n=4 -d=2 -p=10000 --sequential', | ||
| 'sir_hmc.py -t=2 -w=2 -n=4 -d=100 -p=10000 -f 2', | ||
| 'sir_hmc.py -t=2 -w=2 -n=4 -d=100 -p=10000 -f 2 --dct', |
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this is the regression test: -f fails before this PR
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martinjankowiak
approved these changes
Apr 22, 2020
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Addresses #2426
This fixes a bug whereby forecasting failed when using reparameterizers like
--dct. It's still unclear whether DCT reparam will be useful here, but this bug fix might also be helpful for other reparameterizers we try to use.This PR also:
predict(), andmax_tree_depthTested