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Restore old MLL fit #320

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Jul 24, 2024
Merged

Restore old MLL fit #320

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9533cdb
Use torch fitting
Scienfitz Jul 22, 2024
7eeded9
Update CHANGELOG.md
Scienfitz Jul 22, 2024
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2 changes: 2 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -74,6 +74,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
are not passed on to the GPyTorch kernels
- Positive-valued kernel attributes are now correctly handled by validators
and hypothesis strategies
- Reverted `fit_gpytorch_mll` call back to old `fit_gpytorch_mll_torch` call until
finetuning is achieved

### Deprecations
- `SequentialGreedyRecommender` class replaced with `BotorchRecommender`
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3 changes: 2 additions & 1 deletion baybe/surrogates/gaussian_process/core.py
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Expand Up @@ -76,6 +76,7 @@ def _fit(self, searchspace: SearchSpace, train_x: Tensor, train_y: Tensor) -> No
import botorch
import gpytorch
import torch
from botorch.optim.fit import fit_gpytorch_mll_torch

# identify the indexes of the task and numeric dimensions
# TODO: generalize to multiple task parameters
Expand Down Expand Up @@ -138,4 +139,4 @@ def _fit(self, searchspace: SearchSpace, train_x: Tensor, train_y: Tensor) -> No
likelihood=likelihood,
)
mll = gpytorch.ExactMarginalLogLikelihood(self._model.likelihood, self._model)
botorch.fit_gpytorch_mll(mll)
fit_gpytorch_mll_torch(mll, step_limit=100)
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