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Migrate Alebo from code deprecated in closures refactor #1906

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Migrate Alebo from code deprecated in closures refactor #1906

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6fee7cc
Deprecate ALEBO
esantorella Oct 12, 2023
568f572
Migrate Alebo from code deprecated in closures refactor (#1906)
esantorella Oct 12, 2023
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2 changes: 2 additions & 0 deletions ax/models/random/alebo_initializer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@
# LICENSE file in the root directory of this source tree.

from typing import Callable, Dict, List, Optional, Tuple
from warnings import warn

import numpy as np
from ax.models.random.uniform import UniformGenerator
Expand Down Expand Up @@ -43,6 +44,7 @@ def __init__(
init_bound: int = 16,
seed: Optional[int] = None,
) -> None:
warn("ALEBOInitializer is deprecated.", DeprecationWarning)
# pyre-fixme[4]: Attribute must be annotated.
self.Q = np.linalg.pinv(B) @ B # Projects down to B and then back up
self.nsamp = nsamp
Expand Down
48 changes: 29 additions & 19 deletions ax/models/tests/test_alebo.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,7 +36,8 @@ def test_ALEBOKernel(self) -> None:
B = torch.tensor(
[[1.0, 2.0, 3.0, 4.0, 5.0], [2.0, 3.0, 4.0, 5.0, 6.0]], dtype=torch.double
)
k = ALEBOKernel(B=B, batch_shape=torch.Size([]))
with self.assertWarnsRegex(DeprecationWarning, "ALEBOKernel is deprecated"):
k = ALEBOKernel(B=B, batch_shape=torch.Size([]))

self.assertEqual(k.d, 2)
self.assertTrue(torch.equal(B, k.B))
Expand Down Expand Up @@ -72,14 +73,18 @@ def test_ALEBOGP(self) -> None:
train_Y = torch.tensor([[1.0], [2.0], [3.0]], dtype=torch.double)
train_Yvar = 0.1 * torch.ones(3, 1, dtype=torch.double)

mll = get_map_model(
B=B,
train_X=train_X,
train_Y=train_Y,
train_Yvar=train_Yvar,
restarts=1,
init_state_dict=None,
)
with self.assertWarnsRegex(
DeprecationWarning,
"`get_map_model` from ax.models.torch.alebo.py is deprecated",
):
mll = get_map_model(
B=B,
train_X=train_X,
train_Y=train_Y,
train_Yvar=train_Yvar,
restarts=1,
init_state_dict=None,
)
m = mll.model
m.eval()
self.assertIsInstance(m, ALEBOGP)
Expand Down Expand Up @@ -116,15 +121,19 @@ def test_ALEBOGP(self) -> None:

# The whole process in get_fitted_model
init_state_dict = m.state_dict()
m_b2 = get_fitted_model(
B=B,
train_X=train_X,
train_Y=train_Y,
train_Yvar=train_Yvar,
restarts=1,
nsamp=5,
init_state_dict=init_state_dict,
)
with self.assertWarnsRegex(
DeprecationWarning,
"`get_fitted_model` from ax.models.torch.alebo.py is deprecated",
):
m_b2 = get_fitted_model(
B=B,
train_X=train_X,
train_Y=train_Y,
train_Yvar=train_Yvar,
restarts=1,
nsamp=5,
init_state_dict=init_state_dict,
)
self.assertEqual(m_b2._aug_batch_shape, torch.Size([5]))

# Test extract_map_statedict
Expand Down Expand Up @@ -171,7 +180,8 @@ def test_Acq(self) -> None:
train_X = torch.tensor([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=torch.double)
train_Y = torch.tensor([[1.0], [2.0], [3.0]], dtype=torch.double)
train_Yvar = 0.1 * torch.ones(3, 1, dtype=torch.double)
m = ALEBOGP(B=B, train_X=train_X, train_Y=train_Y, train_Yvar=train_Yvar)
with self.assertWarnsRegex(DeprecationWarning, "ALEBOGP is deprecated"):
m = ALEBOGP(B=B, train_X=train_X, train_Y=train_Y, train_Yvar=train_Yvar)
m.eval()

objective_weights = torch.tensor([1.0], dtype=torch.double)
Expand Down
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