From d4a53a70086b90fa974adcd0c378ae46189afdd8 Mon Sep 17 00:00:00 2001 From: Kevin Stone Date: Fri, 9 Aug 2024 12:12:21 -0400 Subject: [PATCH] Improved docstring for surrogate options --- obsidian/surrogates/botorch.py | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/obsidian/surrogates/botorch.py b/obsidian/surrogates/botorch.py index c6e21ce..ab0778e 100644 --- a/obsidian/surrogates/botorch.py +++ b/obsidian/surrogates/botorch.py @@ -25,6 +25,22 @@ class SurrogateBoTorch(SurrogateModel): BoTorch GP model, subclass of the obsidian SurrogateModel Attributes: + model_type (str): The type of model to be used. + + Defaults to ``'GP'``. Options are as follows: + + - ``'GP'``: Gaussian Process with default settings (Matern Kernel, Gamma covariance priors) + - ``'MixedGP'``: GP with mixed parameter types (continuous, categorical). Will be re-selected + by default if 'GP' is selected and input space is mixed. + - ``'DKL'``: GP with a NN feature-extractor (deep kernel learning) + - ``'GPflat'``: GP without priors. May result in optimization instability, but removes bias + for special situations. + - ``'GPprior'``: GP with custom priors on the mean, likelihood, and covariance + - ``'MTGP'``: Multi-task GP for multi-output optimization. Will be re-selected by default + if 'GP' is selected and the input space contains Task parameters. + - ``'DNN'``: Dropout neural network. Uses MC sampling to mask neurons during training and + to estimate uncertainty. + device (str): The device on which the model is run. hps (dict): Optional surrogate function hyperparameters. mll (ExactMarginalLogLikelihood): The marginal log likelihood of the model.