botorch
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pytorch
Loss closures, fit_gpytorch_torch, fit_gyptorch_mll dispatch for ApproximateGPs
Summary: Changelog:
- Enable user-defined loss closures.
fit_gptorch_torchrewrite- Add
fit_gyptorch_mlldispatch for ApproximateGPs
Differential Revision: D39101211
This looks like a pretty reasonable solution to me! I actually like the ability to roll my own loss closures and optimizers here, and think it's worth the extra engineering. @nataliemaus has code that sometimes wants to train a GP end to end with a VAE included in the ELBO, and sometimes only wants to train the GP, so this should let us switch even more code into using BoTorch routines.
Codecov Report
Merging #1439 (4f6c4ef) into main (7613cd2) will not change coverage. The diff coverage is
100.00%.
@@ Coverage Diff @@
## main #1439 +/- ##
==========================================
Coverage 100.00% 100.00%
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Files 134 143 +9
Lines 12402 12755 +353
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+ Hits 12402 12755 +353
| Impacted Files | Coverage Δ | |
|---|---|---|
| botorch/models/pairwise_gp.py | 100.00% <ø> (ø) |
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| botorch/fit.py | 100.00% <100.00%> (ø) |
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| botorch/optim/__init__.py | 100.00% <100.00%> (ø) |
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| botorch/optim/closures/__init__.py | 100.00% <100.00%> (ø) |
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| botorch/optim/closures/core.py | 100.00% <100.00%> (ø) |
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| botorch/optim/closures/model_closures.py | 100.00% <100.00%> (ø) |
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| botorch/optim/core.py | 100.00% <100.00%> (ø) |
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| botorch/optim/fit.py | 100.00% <100.00%> (ø) |
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| botorch/optim/numpy_converter.py | 100.00% <100.00%> (ø) |
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| botorch/optim/stopping.py | 100.00% <100.00%> (ø) |
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| ... and 7 more |
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