botorch.fit

Utilities for model fitting.

botorch.fit.fit_gpytorch_model(mll, optimizer=<function fit_gpytorch_scipy>, **kwargs)[source]

Fit hyperparameters of a GPyTorch model.

On optimizer failures, a new initial condition is sampled from the hyperparameter priors and optimization is retried. The maximum number of retries can be passed in as a max_retries kwarg (default is 5).

Optimizer functions are in botorch.optim.fit.

Parameters:
  • mll (MarginalLogLikelihood) – MarginalLogLikelihood to be maximized.
  • optimizer (Callable) – The optimizer function.
  • kwargs (Any) – Arguments passed along to the optimizer function, including max_retries and sequential (controls the fitting of ModelListGP and BatchedMultiOutputGPyTorchModel models).
Return type:

MarginalLogLikelihood
Returns:

MarginalLogLikelihood with optimized parameters.

Example

>>> gp = SingleTaskGP(train_X, train_Y)
>>> mll = ExactMarginalLogLikelihood(gp.likelihood, gp)
>>> fit_gpytorch_model(mll)