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Set deprecation for sooner (warning has been around for a year) #2351

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Set deprecation for sooner (warning has been around for a year) #2351

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0923e56
Move `ei_or_nei` out of ALEBO and to `botorch_defaults` so LCE-A does…
Apr 11, 2024
007059b
Set deprecation for sooner (warning has been around for a year)
Apr 11, 2024
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78 changes: 11 additions & 67 deletions ax/models/torch/alebo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,14 +34,14 @@
from ax.core.types import TCandidateMetadata
from ax.models.random.alebo_initializer import ALEBOInitializer
from ax.models.torch.botorch import BotorchModel
from ax.models.torch.botorch_defaults import get_qLogNEI
from ax.models.torch.botorch_defaults import ei_or_nei
from ax.models.torch.utils import _datasets_to_legacy_inputs

from ax.models.torch_base import TorchGenResults, TorchModel, TorchOptConfig
from ax.utils.common.docutils import copy_doc
from ax.utils.common.logger import get_logger
from ax.utils.common.typeutils import checked_cast
from botorch.acquisition.acquisition import AcquisitionFunction
from botorch.acquisition.analytic import ExpectedImprovement
from botorch.acquisition.objective import PosteriorTransform
from botorch.models.gp_regression import SingleTaskGP
from botorch.models.gpytorch import GPyTorchModel
Expand Down Expand Up @@ -264,7 +264,7 @@ def __init__(self, B: Tensor, batch_shape: torch.Size) -> None:
has_lengthscale=False, ard_num_dims=None, eps=0.0, batch_shape=batch_shape
)
warn(
"ALEBOKernel is deprecated and should be removed in Ax 0.5.0.",
"ALEBOKernel is deprecated and should be removed in Ax 0.3.9.",
DeprecationWarning,
)
# pyre-fixme[4]: Attribute must be annotated.
Expand Down Expand Up @@ -337,7 +337,7 @@ def __init__(
self, B: Tensor, train_X: Tensor, train_Y: Tensor, train_Yvar: Tensor
) -> None:
warn(
"ALEBOGP is deprecated and should be removed in Ax 0.5.0. SAASBO "
"ALEBOGP is deprecated and should be removed in Ax 0.3.9. SAASBO "
"(Models.SAASBO from ax.modelbridge.registry) likely provides better "
"performance.",
DeprecationWarning,
Expand Down Expand Up @@ -433,7 +433,7 @@ def get_fitted_model(
"""
warn(
"`get_fitted_model` from ax.models.torch.alebo.py is deprecated and "
"should be removed in Ax 0.5.0.",
"should be removed in Ax 0.3.9.",
DeprecationWarning,
)
# Get MAP estimate.
Expand Down Expand Up @@ -484,7 +484,7 @@ def get_map_model(
"""
warn(
"`get_map_model` from ax.models.torch.alebo.py is deprecated and should "
"be removed in Ax 0.5.0.",
"be removed in Ax 0.3.9.",
DeprecationWarning,
)
f_best = 1e8
Expand Down Expand Up @@ -530,7 +530,7 @@ def laplace_sample_U(
and output scale.
"""
warn(
"laplace_sample_U is deprecated and should be removed in Ax 0.5.0.",
"laplace_sample_U is deprecated and should be removed in Ax 0.3.9.",
DeprecationWarning,
)
# Estimate diagonal of the Hessian
Expand Down Expand Up @@ -600,7 +600,7 @@ def get_batch_model(
"""
warn(
"`get_batch_model` from ax.models.torch.alebo.py is deprecated and "
"should be removed in Ax 0.5.0.",
"should be removed in Ax 0.3.9.",
DeprecationWarning,
)
b = Uvec_batch.size(0)
Expand Down Expand Up @@ -641,7 +641,7 @@ def extract_map_statedict(
"""
warn(
"`extract_map_statedict` from ax.models.torch.alebo.py is deprecated and "
"should be removed in Ax 0.5.0.",
"should be removed in Ax 0.3.9.",
DeprecationWarning,
)
is_modellist = num_outputs > 1
Expand All @@ -666,62 +666,6 @@ def extract_map_statedict(
return map_sds


def ei_or_nei(
model: Union[ALEBOGP, ModelListGP],
objective_weights: Tensor,
outcome_constraints: Optional[Tuple[Tensor, Tensor]],
X_observed: Tensor,
X_pending: Optional[Tensor],
q: int,
noiseless: bool,
) -> AcquisitionFunction:
"""Use analytic EI if appropriate, otherwise Monte Carlo NEI.

Analytic EI can be used if: Single outcome, no constraints, no pending
points, not batch, and no noise.

Args:
model: GP.
objective_weights: Weights on each outcome for the objective.
outcome_constraints: Outcome constraints.
X_observed: Observed points for NEI.
X_pending: Pending points.
q: Batch size.
noiseless: True if evaluations are noiseless.

Returns: An AcquisitionFunction, either analytic EI or MC NEI.
"""
warn(
"`ei_or_nei` from ax.models.torch.alebo.py is deprecated and should be "
"removed in Ax 0.5.0.",
DeprecationWarning,
)
if (
len(objective_weights) == 1
and outcome_constraints is None
and X_pending is None
and q == 1
and noiseless
):
maximize = objective_weights[0] > 0
if maximize:
best_f = model.train_targets.max()
else:
best_f = model.train_targets.min()
# pyre-fixme[6]: For 3rd param expected `bool` but got `Tensor`.
return ExpectedImprovement(model=model, best_f=best_f, maximize=maximize)
else:
with gpytorch.settings.max_cholesky_size(2000):
acq = get_qLogNEI(
model=model,
objective_weights=objective_weights,
outcome_constraints=outcome_constraints,
X_observed=X_observed,
X_pending=X_pending,
)
return acq


def alebo_acqf_optimizer(
acq_function: AcquisitionFunction,
bounds: Tensor,
Expand All @@ -741,7 +685,7 @@ def alebo_acqf_optimizer(
lie within that polytope.
"""
warn(
"`alebo_acqf_optimizer` is deprecated and should be removed in Ax 0.5.0.",
"`alebo_acqf_optimizer` is deprecated and should be removed in Ax 0.3.9.",
DeprecationWarning,
)
candidate_list, acq_value_list = [], []
Expand Down Expand Up @@ -819,7 +763,7 @@ def __init__(
self, B: Tensor, laplace_nsamp: int = 25, fit_restarts: int = 10
) -> None:
warn(
"ALEBO is deprecated and should be removed in Ax 0.5.0.",
"ALEBO is deprecated and should be removed in Ax 0.3.9.",
DeprecationWarning,
)
self.B = B
Expand Down
60 changes: 60 additions & 0 deletions ax/models/torch/botorch_defaults.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,9 @@
from copy import deepcopy
from random import randint
from typing import Any, Callable, Dict, List, Optional, Protocol, Tuple, Type, Union
from warnings import warn

import gpytorch

import torch
from ax.models.model_utils import best_observed_point, get_observed
Expand All @@ -18,6 +21,7 @@
from ax.models.types import TConfig
from botorch.acquisition import get_acquisition_function
from botorch.acquisition.acquisition import AcquisitionFunction
from botorch.acquisition.analytic import ExpectedImprovement
from botorch.acquisition.fixed_feature import FixedFeatureAcquisitionFunction
from botorch.acquisition.objective import ConstrainedMCObjective, GenericMCObjective
from botorch.acquisition.utils import get_infeasible_cost
Expand Down Expand Up @@ -892,3 +896,59 @@ def get_warping_transform(
batch_shape=batch_shape,
)
return tf


def ei_or_nei(
model: ModelListGP,
objective_weights: Tensor,
outcome_constraints: Optional[Tuple[Tensor, Tensor]],
X_observed: Tensor,
X_pending: Optional[Tensor],
q: int,
noiseless: bool,
) -> AcquisitionFunction:
"""Use analytic EI if appropriate, otherwise Monte Carlo NEI.

Analytic EI can be used if: Single outcome, no constraints, no pending
points, not batch, and no noise.

Args:
model: GP.
objective_weights: Weights on each outcome for the objective.
outcome_constraints: Outcome constraints.
X_observed: Observed points for NEI.
X_pending: Pending points.
q: Batch size.
noiseless: True if evaluations are noiseless.

Returns: An AcquisitionFunction, either analytic EI or MC NEI.
"""
warn(
"`ei_or_nei` from ax.models.torch.alebo.py is deprecated and should be "
"removed in Ax 0.3.9.",
DeprecationWarning,
)
if (
len(objective_weights) == 1
and outcome_constraints is None
and X_pending is None
and q == 1
and noiseless
):
# TODO: Check if this is correct @no-commit
maximize = bool(objective_weights[0] > 0)
if maximize:
best_f = model.train_targets.max()
else:
best_f = model.train_targets.min()
return ExpectedImprovement(model=model, best_f=best_f, maximize=maximize)
else:
with gpytorch.settings.max_cholesky_size(2000):
acq = get_qLogNEI(
model=model,
objective_weights=objective_weights,
outcome_constraints=outcome_constraints,
X_observed=X_observed,
X_pending=X_pending,
)
return acq
2 changes: 1 addition & 1 deletion ax/models/torch/cbo_lcea.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,8 +11,8 @@

from ax.core.search_space import SearchSpaceDigest
from ax.core.types import TCandidateMetadata
from ax.models.torch.alebo import ei_or_nei
from ax.models.torch.botorch import BotorchModel
from ax.models.torch.botorch_defaults import ei_or_nei
from ax.models.torch.cbo_sac import generate_model_space_decomposition
from ax.models.torch_base import TorchModel, TorchOptConfig
from ax.utils.common.docutils import copy_doc
Expand Down
2 changes: 1 addition & 1 deletion ax/models/torch/rembo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -49,7 +49,7 @@ def __init__(
) -> None:
warn(
"REMBO is deprecated and does not guarantee correctness. "
"It will be removed in Ax 0.5.0.",
"It will be removed in Ax 0.3.9.",
DeprecationWarning,
)
self.A = A
Expand Down