botorch.exceptions

Errors

Botorch Errors.

exception botorch.exceptions.errors.BotorchError[source]

Bases: Exception

Base botorch exception.

exception botorch.exceptions.errors.CandidateGenerationError[source]

Bases: BotorchError

Exception raised during generating candidates.

exception botorch.exceptions.errors.DeprecationError[source]

Bases: BotorchError

Exception raised due to deprecations

exception botorch.exceptions.errors.InputDataError[source]

Bases: BotorchError

Exception raised when input data does not comply with conventions.

exception botorch.exceptions.errors.UnsupportedError[source]

Bases: BotorchError

Currently unsupported feature.

exception botorch.exceptions.errors.BotorchTensorDimensionError[source]

Bases: BotorchError

Exception raised when a tensor violates a botorch convention.

exception botorch.exceptions.errors.ModelFittingError[source]

Bases: Exception

Exception raised when attempts to fit a model terminate unsuccessfully.

exception botorch.exceptions.errors.OptimizationTimeoutError(*args, current_x, runtime, **kwargs)[source]

Bases: BotorchError

Exception raised when optimization times out.

Parameters:

*args (Any) – Standard args to BotorchError.
current_x (ndarray[tuple[Any, ...], dtype[_ScalarT]]) – A numpy array representing the current iterate.
runtime (float) – The total runtime in seconds after which the optimization timed out.
**kwargs (Any) – Standard kwargs to BotorchError.

Return type:

None

exception botorch.exceptions.errors.OptimizationGradientError(*args, current_x, **kwargs)[source]

Bases: BotorchError, RuntimeError

Exception raised when gradient array gradf contains NaNs.

Parameters:

*args (Any) – Standard args to BotorchError.
current_x (ndarray[tuple[Any, ...], dtype[_ScalarT]]) – A numpy array representing the current iterate.
**kwargs (Any) – Standard kwargs to BotorchError.

Return type:

None

exception botorch.exceptions.errors.InfeasibilityError[source]

Bases: BotorchError, ValueError

Exception raised when infeasibility occurs.

Warnings

Botorch Warnings.

exception botorch.exceptions.warnings.BotorchWarning[source]

Bases: Warning

Base botorch warning.

exception botorch.exceptions.warnings.BadInitialCandidatesWarning[source]

Bases: BotorchWarning

Warning issued if set of initial candidates for optimization is bad.

exception botorch.exceptions.warnings.InputDataWarning[source]

Bases: BotorchWarning

Warning raised when input data does not comply with conventions.

exception botorch.exceptions.warnings.CostAwareWarning[source]

Bases: BotorchWarning

Warning raised in the context of cost-aware acquisition strategies.

exception botorch.exceptions.warnings.OptimizationWarning[source]

Bases: BotorchWarning

Optimization-related warnings.

exception botorch.exceptions.warnings.SamplingWarning[source]

Bases: BotorchWarning

Sampling related warnings.

exception botorch.exceptions.warnings.BotorchTensorDimensionWarning[source]

Bases: BotorchWarning

Warning raised when a tensor possibly violates a botorch convention.

exception botorch.exceptions.warnings.UserInputWarning[source]

Bases: BotorchWarning

Warning raised when a potential issue is detected with user provided inputs.

exception botorch.exceptions.warnings.NumericsWarning[source]

Bases: BotorchWarning

Warning raised when numerical issues are detected.

botorch.exceptions.warnings.legacy_ei_numerics_warning(legacy_name)[source]

Raises a warning for legacy EI acquisition functions that are known to have numerical issues and should be replaced with the LogEI version for virtually all use-cases except for explicit benchmarking of the numerical issues of legacy EI.

Parameters:: legacy_name (str) – The name of the legacy EI acquisition function.
Return type:: None