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Merged
copybara-service merged 1 commit into from
Oct 6, 2026
Merged

Replace # pytype: disable suppressions with # pyrefly: ignore #1334

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6 changes: 3 additions & 3 deletions vizier/_src/algorithms/designers/bocs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -318,7 +318,7 @@ def surrogate_model(self, x: np.ndarray) -> FloatType:
if self._X_inf.shape[0] != 0 and np.equal(x, self._X_inf).all(axis=1).any():
barrier = np.inf

return np.dot(x_all, self._alpha) + barrier # pyrefly: ignore[bad-argument-type, no-matching-overload]
return np.dot(x_all, self._alpha) + barrier # pyrefly: ignore[no-matching-overload]

def _order_effects(self, X: np.ndarray) -> np.ndarray:
"""Function computes data matrix for all coupling."""
Expand Down Expand Up @@ -498,9 +498,9 @@ def argmin(self) -> np.ndarray:

# Extract vectors and compute Cholesky.
try:
L = np.linalg.cholesky(X.value) # pyrefly: ignore[no-matching-overload]
L = np.linalg.cholesky(X.value)
except np.linalg.LinAlgError:
XpI = X.value + 1e-15 * np.eye(self._num_vars + 1) # pyrefly: ignore[unsupported-operation]
XpI = X.value + 1e-15 * np.eye(self._num_vars + 1)
L = np.linalg.cholesky(XpI)

suggest_vect = np.zeros((self._num_vars, self._num_repeats))
Expand Down
2 changes: 1 addition & 1 deletion vizier/_src/algorithms/designers/gp_bandit.py
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Expand Up @@ -638,4 +638,4 @@ def from_problem(
if seed is None
else jax.random.PRNGKey(seed)
)
return cls(problem, rng=rng, **kwargs) # pyrefly: ignore[unexpected-keyword]
return cls(problem, rng=rng, **kwargs)
128 changes: 64 additions & 64 deletions vizier/_src/algorithms/designers/gp_bandit_test.py
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Expand Up @@ -82,7 +82,7 @@ def _setup_lambda_search(
problem = vz.ProblemStatement(
search_space=search_space,
metric_information=vz.MetricsConfig(
metrics=[ # pyrefly: ignore[unexpected-keyword]
metrics=[
vz.MetricInformation('obj', goal=vz.ObjectiveMetricGoal.MAXIMIZE),
]
),
Expand All @@ -99,7 +99,7 @@ def _setup_lambda_search(
trial.complete(vz.Measurement(metrics={'obj': f(x)})) # pyrefly: ignore[bad-argument-type]
obs_trials.append(trial)

gp_designer = gp_bandit.VizierGPBandit(problem, ard_optimizer=ard_optimizer) # pyrefly: ignore[unexpected-keyword]
gp_designer = gp_bandit.VizierGPBandit(problem, ard_optimizer=ard_optimizer)
return gp_designer, obs_trials, problem


Expand Down Expand Up @@ -138,24 +138,24 @@ class GoogleGpBanditTest(parameterized.TestCase):
batch_size=5,
num_seed_trials=5,
padding_schedule=padding.PaddingSchedule(
num_trials=padding.PaddingType.MULTIPLES_OF_10, # pyrefly: ignore[unexpected-keyword]
num_features=padding.PaddingType.POWERS_OF_2, # pyrefly: ignore[unexpected-keyword]
num_trials=padding.PaddingType.MULTIPLES_OF_10,
num_features=padding.PaddingType.POWERS_OF_2,
),
),
dict(
iters=5,
batch_size=1,
num_seed_trials=3,
padding_schedule=padding.PaddingSchedule(
num_trials=padding.PaddingType.POWERS_OF_2, # pyrefly: ignore[unexpected-keyword]
num_features=padding.PaddingType.POWERS_OF_2, # pyrefly: ignore[unexpected-keyword]
num_trials=padding.PaddingType.POWERS_OF_2,
num_features=padding.PaddingType.POWERS_OF_2,
),
acquisition_optimizer_factory=lbfgsb_optimizer_factory,
),
dict(
padding_schedule=padding.PaddingSchedule(
num_trials=padding.PaddingType.POWERS_OF_2, # pyrefly: ignore[unexpected-keyword]
num_features=padding.PaddingType.POWERS_OF_2, # pyrefly: ignore[unexpected-keyword]
num_trials=padding.PaddingType.POWERS_OF_2,
num_features=padding.PaddingType.POWERS_OF_2,
),
ensemble_size=3,
),
Expand Down Expand Up @@ -184,18 +184,18 @@ def test_on_flat_continuous_space(
)
)

designer = gp_bandit.VizierGPBandit( # pyrefly: ignore[missing-argument]
problem=problem, # pyrefly: ignore[unexpected-keyword]
acquisition_optimizer_factory=acquisition_optimizer_factory, # pyrefly: ignore[bad-argument-type, unexpected-keyword]
ard_optimizer=optimizers.JaxoptLbfgsB( # pyrefly: ignore[bad-argument-type, unexpected-keyword]
designer = gp_bandit.VizierGPBandit(
problem=problem,
acquisition_optimizer_factory=acquisition_optimizer_factory, # pyrefly: ignore[bad-argument-type]
ard_optimizer=optimizers.JaxoptLbfgsB(
optimizers.LbfgsBOptions(maxiter=5, num_line_search_steps=5)
),
num_seed_trials=num_seed_trials, # pyrefly: ignore[unexpected-keyword]
ensemble_size=ensemble_size, # pyrefly: ignore[unexpected-keyword]
padding_schedule=padding_schedule, # pyrefly: ignore[unexpected-keyword]
use_trust_region=use_trust_region, # pyrefly: ignore[unexpected-keyword]
rng=jax.random.PRNGKey(0), # pyrefly: ignore[unexpected-keyword]
linear_coef=0.1, # pyrefly: ignore[unexpected-keyword]
num_seed_trials=num_seed_trials,
ensemble_size=ensemble_size,
padding_schedule=padding_schedule,
use_trust_region=use_trust_region,
rng=jax.random.PRNGKey(0),
linear_coef=0.1,
)
with profiler.collect_events() as events:
self.assertLen(
Expand Down Expand Up @@ -241,8 +241,8 @@ def test_on_flat_continuous_space(
batch_size=5,
num_seed_trials=5,
padding_schedule=padding.PaddingSchedule(
num_trials=padding.PaddingType.MULTIPLES_OF_10, # pyrefly: ignore[unexpected-keyword]
num_features=padding.PaddingType.POWERS_OF_2, # pyrefly: ignore[unexpected-keyword]
num_trials=padding.PaddingType.MULTIPLES_OF_10,
num_features=padding.PaddingType.POWERS_OF_2,
),
),
)
Expand All @@ -260,12 +260,12 @@ def test_on_flat_mixed_space(
name='metric', goal=vz.ObjectiveMetricGoal.MAXIMIZE
)
)
designer = gp_bandit.VizierGPBandit( # pyrefly: ignore[missing-argument]
problem=problem, # pyrefly: ignore[unexpected-keyword]
acquisition_optimizer_factory=vectorized_optimizer_factory, # pyrefly: ignore[unexpected-keyword]
num_seed_trials=num_seed_trials, # pyrefly: ignore[unexpected-keyword]
padding_schedule=padding_schedule, # pyrefly: ignore[unexpected-keyword]
use_trust_region=use_trust_region, # pyrefly: ignore[unexpected-keyword]
designer = gp_bandit.VizierGPBandit(
problem=problem,
acquisition_optimizer_factory=vectorized_optimizer_factory,
num_seed_trials=num_seed_trials,
padding_schedule=padding_schedule,
use_trust_region=use_trust_region,
)
self.assertLen(
test_runners.RandomMetricsRunner(
Expand Down Expand Up @@ -318,22 +318,22 @@ def test_invariance_to_trials_padding_on_flat_mixed_space(
# on ARD again.
noop_ard_optimizer = optimizers.default_optimizer(maxiter=0)
desinger_rng = jax.random.PRNGKey(0)
designer = gp_bandit.VizierGPBandit( # pyrefly: ignore[missing-argument]
problem=problem, # pyrefly: ignore[unexpected-keyword]
acquisition_optimizer_factory=acquisition_optimizer_factory, # pyrefly: ignore[unexpected-keyword]
ard_optimizer=noop_ard_optimizer, # pyrefly: ignore[unexpected-keyword]
num_seed_trials=num_seed_trials, # pyrefly: ignore[unexpected-keyword]
rng=desinger_rng, # pyrefly: ignore[unexpected-keyword]
designer = gp_bandit.VizierGPBandit(
problem=problem,
acquisition_optimizer_factory=acquisition_optimizer_factory,
ard_optimizer=noop_ard_optimizer,
num_seed_trials=num_seed_trials,
rng=desinger_rng,
)
padding_designer = gp_bandit.VizierGPBandit( # pyrefly: ignore[missing-argument]
problem=problem, # pyrefly: ignore[unexpected-keyword]
acquisition_optimizer_factory=acquisition_optimizer_factory, # pyrefly: ignore[unexpected-keyword]
ard_optimizer=noop_ard_optimizer, # pyrefly: ignore[unexpected-keyword]
num_seed_trials=num_seed_trials, # pyrefly: ignore[unexpected-keyword]
padding_schedule=padding.PaddingSchedule( # pyrefly: ignore[unexpected-keyword]
num_trials=padding.PaddingType.MULTIPLES_OF_10, # pyrefly: ignore[unexpected-keyword]
padding_designer = gp_bandit.VizierGPBandit(
problem=problem,
acquisition_optimizer_factory=acquisition_optimizer_factory,
ard_optimizer=noop_ard_optimizer,
num_seed_trials=num_seed_trials,
padding_schedule=padding.PaddingSchedule(
num_trials=padding.PaddingType.MULTIPLES_OF_10,
),
rng=desinger_rng, # pyrefly: ignore[unexpected-keyword]
rng=desinger_rng,
)
metrics_runner_seed = 1
designer_suggestions = test_runners.RandomMetricsRunner(
Expand Down Expand Up @@ -392,14 +392,14 @@ def test_jit_once(self, *args):
)

def create_designer(problem):
return gp_bandit.VizierGPBandit( # pyrefly: ignore[missing-argument]
problem=problem, # pyrefly: ignore[unexpected-keyword]
acquisition_optimizer_factory=vectorized_optimizer_factory, # pyrefly: ignore[unexpected-keyword]
num_seed_trials=3, # pyrefly: ignore[unexpected-keyword]
ensemble_size=2, # pyrefly: ignore[unexpected-keyword]
padding_schedule=padding.PaddingSchedule( # pyrefly: ignore[unexpected-keyword]
num_trials=padding.PaddingType.MULTIPLES_OF_10, # pyrefly: ignore[unexpected-keyword]
num_features=padding.PaddingType.MULTIPLES_OF_10, # pyrefly: ignore[unexpected-keyword]
return gp_bandit.VizierGPBandit(
problem=problem,
acquisition_optimizer_factory=vectorized_optimizer_factory,
num_seed_trials=3,
ensemble_size=2,
padding_schedule=padding.PaddingSchedule(
num_trials=padding.PaddingType.MULTIPLES_OF_10,
num_features=padding.PaddingType.MULTIPLES_OF_10,
),
)

Expand Down Expand Up @@ -445,19 +445,19 @@ def _qei_factory(data: types.ModelData) -> acquisitions.AcquisitionFunction:

n_parallel = 4
iters = 3
designer = gp_bandit.VizierGPBandit( # pyrefly: ignore[missing-argument]
problem=problem, # pyrefly: ignore[unexpected-keyword]
acquisition_optimizer_factory=vectorized_optimizer_factory, # pyrefly: ignore[unexpected-keyword]
ard_optimizer=optimizers.JaxoptLbfgsB( # pyrefly: ignore[bad-argument-type, unexpected-keyword]
designer = gp_bandit.VizierGPBandit(
problem=problem,
acquisition_optimizer_factory=vectorized_optimizer_factory,
ard_optimizer=optimizers.JaxoptLbfgsB(
optimizers.LbfgsBOptions(maxiter=5, num_line_search_steps=5)
),
scoring_function_factory=scoring_fn_factory, # pyrefly: ignore[unexpected-keyword]
scoring_function_is_parallel=True, # pyrefly: ignore[unexpected-keyword]
use_trust_region=False, # pyrefly: ignore[unexpected-keyword]
num_seed_trials=n_parallel, # pyrefly: ignore[unexpected-keyword]
ensemble_size=3, # pyrefly: ignore[unexpected-keyword]
rng=jax.random.PRNGKey(0), # pyrefly: ignore[unexpected-keyword]
linear_coef=0.1, # pyrefly: ignore[unexpected-keyword]
scoring_function_factory=scoring_fn_factory,
scoring_function_is_parallel=True,
use_trust_region=False,
num_seed_trials=n_parallel,
ensemble_size=3,
rng=jax.random.PRNGKey(0),
linear_coef=0.1,
)
self.assertLen(
test_runners.RandomMetricsRunner(
Expand All @@ -483,7 +483,7 @@ def test_multi_metrics(self, multitask_type: mt_type):
problem = vz.ProblemStatement(
search_space=search_space,
metric_information=vz.MetricsConfig(
metrics=[ # pyrefly: ignore[unexpected-keyword]
metrics=[
vz.MetricInformation(
'obj1', goal=vz.ObjectiveMetricGoal.MAXIMIZE
),
Expand All @@ -495,7 +495,7 @@ def test_multi_metrics(self, multitask_type: mt_type):
)

iters = 2
designer = gp_bandit.VizierGPBandit(problem, multitask_type=multitask_type) # pyrefly: ignore[unexpected-keyword]
designer = gp_bandit.VizierGPBandit(problem, multitask_type=multitask_type)
self.assertLen(
test_runners.RandomMetricsRunner(
problem,
Expand Down Expand Up @@ -528,9 +528,9 @@ def test_convergence(
# pylint: disable=g-long-lambda
lambda problem, seed: gp_bandit.VizierGPBandit( # pyrefly: ignore[bad-argument-type]
problem,
rng=jax.random.PRNGKey(seed), # pyrefly: ignore[unexpected-keyword]
padding_schedule=padding.PaddingSchedule( # pyrefly: ignore[unexpected-keyword]
num_trials=padding.PaddingType.MULTIPLES_OF_10 # pyrefly: ignore[unexpected-keyword]
rng=jax.random.PRNGKey(seed),
padding_schedule=padding.PaddingSchedule(
num_trials=padding.PaddingType.MULTIPLES_OF_10
),
)
),
Expand Down
10 changes: 5 additions & 5 deletions vizier/_src/algorithms/designers/gp_ucb_pe.py
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Expand Up @@ -600,13 +600,13 @@ def score_with_aux(


def default_ard_optimizer() -> optimizers.Optimizer[types.ParameterDict]:
return optimizers.JaxoptScipyLbfgsB( # pyrefly: ignore[bad-return]
options=optimizers.LbfgsBOptions( # pyrefly: ignore[unexpected-keyword]
return optimizers.JaxoptScipyLbfgsB(
options=optimizers.LbfgsBOptions(
num_line_search_steps=20,
tol=1e-5,
maxiter=500,
),
max_duration=datetime.timedelta(minutes=40), # pyrefly: ignore[unexpected-keyword]
max_duration=datetime.timedelta(minutes=40),
)


Expand Down Expand Up @@ -660,7 +660,7 @@ class method that takes `ModelInput` and returns a
kw_only=True,
factory=lambda: VizierGPUCBPEBandit.default_acquisition_optimizer_factory,
)
_gp_model_class: GPModelClass = attr.field( # pyrefly: ignore[bad-assignment]
_gp_model_class: GPModelClass = attr.field(
kw_only=True,
factory=lambda: tuned_gp_models.VizierGaussianProcess,
)
Expand All @@ -677,7 +677,7 @@ class method that takes `ModelInput` and returns a
_ard_random_restarts: int = attr.field(default=4, kw_only=True)
_use_trust_region: bool = attr.field(default=True, kw_only=True)
_num_seed_trials: int = attr.field(default=1, kw_only=True)
_config: UCBPEConfig = attr.field( # pyrefly: ignore[bad-assignment]
_config: UCBPEConfig = attr.field(
factory=UCBPEConfig, # pyrefly: ignore[bad-assignment]
kw_only=True,
)
Expand Down
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