Source code for botorch.exceptions.warnings
#!/usr/bin/env python3
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
r"""
Botorch Warnings.
"""
import warnings
[docs]
class BotorchWarning(Warning):
r"""Base botorch warning."""
pass
[docs]
class BadInitialCandidatesWarning(BotorchWarning):
r"""Warning issued if set of initial candidates for optimziation is bad."""
pass
[docs]
class CostAwareWarning(BotorchWarning):
r"""Warning raised in the context of cost-aware acquisition strategies."""
pass
[docs]
class OptimizationWarning(BotorchWarning):
r"""Optimization-related warnings."""
pass
[docs]
class SamplingWarning(BotorchWarning):
r"""Sampling related warnings."""
pass
[docs]
class BotorchTensorDimensionWarning(BotorchWarning):
r"""Warning raised when a tensor possibly violates a botorch convention."""
pass
[docs]
class NumericsWarning(BotorchWarning):
r"""Warning raised when numerical issues are detected."""
pass
[docs]
def legacy_ei_numerics_warning(legacy_name: str) -> None:
"""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.
Args:
legacy_name: The name of the legacy EI acquisition function.
logei_name: The name of the associated LogEI acquisition function.
"""
legacy_to_logei = {
"ExpectedImprovement": "LogExpectedImprovement",
"ConstrainedExpectedImprovement": "LogConstrainedExpectedImprovement",
"NoisyExpectedImprovement": "LogNoisyExpectedImprovement",
"qExpectedImprovement": "qLogExpectedImprovement",
"qNoisyExpectedImprovement": "qLogNoisyExpectedImprovement",
"qExpectedHypervolumeImprovement": "qLogExpectedHypervolumeImprovement",
"qNoisyExpectedHypervolumeImprovement": (
"qLogNoisyExpectedHypervolumeImprovement"
),
}
# Only raise the warning if the legacy name is in the mapping. It can fail to be in
# the mapping if the legacy acquisition function derives from a legacy EI class,
# e.g. MOMF, which derives from qEHVI, but there is not corresponding LogMOMF yet.
if legacy_name in legacy_to_logei:
logei_name = legacy_to_logei[legacy_name]
msg = (
f"{legacy_name} has known numerical issues that lead to suboptimal "
"optimization performance. It is strongly recommended to simply replace"
f"\n\n\t {legacy_name} \t --> \t {logei_name} \n\n"
"instead, which fixes the issues and has the same "
"API. See https://arxiv.org/abs/2310.20708 for details."
)
warnings.warn(msg, NumericsWarning, stacklevel=2)
def _get_single_precision_warning(dtype_str: str) -> str:
msg = (
f"The model inputs are of type {dtype_str}. It is strongly recommended "
"to use double precision in BoTorch, as this improves both "
"precision and stability and can help avoid numerical errors. "
"See https://github.com/pytorch/botorch/discussions/1444"
)
return msg
