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Replace # pytype: disable suppressions with # pyrefly: ignore #1332

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

Replace # pytype: disable suppressions with # pyrefly: ignore #1332

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14 changes: 4 additions & 10 deletions vizier/_src/algorithms/optimizers/eagle_strategy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -389,7 +389,6 @@ def __call__(
# This configuration updates all the fireflies in each iteration.
suggestion_batch_size = pool_size
# Use priors to populate Eagle state
# pytype: disable=wrong-arg-types # jnp-type
return VectorizedEagleStrategy(
n_feature_dimensions=feature_dimensions.n_feature_dimensions,
n_feature_dimensions_with_padding=(
Expand All @@ -402,9 +401,8 @@ def __call__(
pool_size=pool_size,
categorical_sizes=jnp.array(feature_dimensions.categorical_sizes),
max_categorical_size=feature_dimensions.max_categorical_size,
dtype=converter._impl.dtype,
dtype=converter._impl.dtype, # pyrefly: ignore[bad-argument-type]
)
# pytype: enable=wrong-arg-types


@struct.dataclass
Expand Down Expand Up @@ -555,15 +553,13 @@ def init_state(
n_parallel=n_parallel,
seed=seed,
)
# pytype: disable=wrong-arg-types # jnp-type
return VectorizedEagleStrategyState(
iterations=jnp.array(0),
features=init_features,
rewards=jnp.ones(self.pool_size) * -jnp.inf,
best_reward=-jnp.inf,
best_reward=-jnp.inf, # pyrefly: ignore[bad-argument-type]
perturbations=jnp.ones(self.pool_size) * self.config.perturbation,
)
# pytype: enable=wrong-arg-types

def _populate_pool_with_prior_trials(
self,
Expand Down Expand Up @@ -847,14 +843,12 @@ def _create_features(
if self.config.mutate_normalization_type == MutateNormalizationType.MEAN:
# Divide the push / pull forces by the number of participating fireflies.
# Also multiply by normalization_scale.
# pytype: disable=wrong-arg-types # jnp-type
norm_scaled_pulls = self.config.normalization_scale * jnp.nan_to_num(
scaled_pulls / jnp.sum(scaled_pulls > 0.0, axis=1, keepdims=True), 0
scaled_pulls / jnp.sum(scaled_pulls > 0.0, axis=1, keepdims=True), 0 # pyrefly: ignore[bad-argument-type]
)
norm_scaled_push = self.config.normalization_scale * jnp.nan_to_num(
scaled_push / jnp.sum(scaled_push < 0.0, axis=1, keepdims=True), 0
scaled_push / jnp.sum(scaled_push < 0.0, axis=1, keepdims=True), 0 # pyrefly: ignore[bad-argument-type]
)
# pytype: enable=wrong-arg-types
elif self.config.mutate_normalization_type == (
MutateNormalizationType.RANDOM
):
Expand Down
14 changes: 7 additions & 7 deletions vizier/_src/algorithms/optimizers/eagle_strategy_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -548,8 +548,8 @@ def test_optimize_with_eagle_padding(self):
converter = converters.TrialToModelInputConverter.from_problem(
problem,
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,
),
)
eagle_factory = eagle_strategy.VectorizedEagleStrategyFactory()
Expand All @@ -575,8 +575,8 @@ def test_singleton_constraints_are_respected_with_padding(self):
converter = converters.TrialToModelInputConverter.from_problem(
problem,
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,
),
)
eagle_factory = eagle_strategy.VectorizedEagleStrategyFactory()
Expand Down Expand Up @@ -618,8 +618,8 @@ def test_compute_feature_dimensions_from_converter(
converter = converters.TrialToModelInputConverter.from_problem(
problem,
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,
),
)
feature_dimensions = (
Expand Down Expand Up @@ -685,7 +685,7 @@ def score_fn(x, _):
)

padding_schedule = padding.PaddingSchedule(
num_trials=padding.PaddingType.MULTIPLES_OF_10, # pyrefly: ignore[unexpected-keyword]
num_trials=padding.PaddingType.MULTIPLES_OF_10,
)
padding_converter = converters.TrialToModelInputConverter.from_problem(
problem,
Expand Down
2 changes: 1 addition & 1 deletion vizier/_src/algorithms/optimizers/vectorized_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -313,7 +313,7 @@ class VectorizedOptimizer(Generic[_S]):
max_evaluations: int = struct.field(pytree_node=False, default=75_000)
dtype: types.ContinuousAndCategorical[jnp.dtype] = struct.field(
pytree_node=False,
default=types.ContinuousAndCategorical[jnp.dtype]( # pytype: disable=wrong-arg-types # jnp-type
default=types.ContinuousAndCategorical[jnp.dtype](
jnp.float64, types.INT_DTYPE # pyrefly: ignore[bad-argument-type]
),
)
Expand Down
88 changes: 44 additions & 44 deletions vizier/_src/benchmarks/analyzers/convergence_curve.py
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Original file line number Diff line number Diff line change
Expand Up @@ -811,16 +811,16 @@ def score(self) -> float:
extended_compared = ConvergenceCurve.extrapolate_ys(
compared_curve, extend_steps
)
baseline_comparator = LogEfficiencyConvergenceCurveComparator( # pyrefly: ignore[missing-argument]
baseline_curve=combined_curve, # pyrefly: ignore[unexpected-keyword]
compared_curve=extended_baseline, # pyrefly: ignore[unexpected-keyword]
compared_quantile=self._baseline_quantile, # pyrefly: ignore[unexpected-keyword]
baseline_comparator = LogEfficiencyConvergenceCurveComparator(
baseline_curve=combined_curve,
compared_curve=extended_baseline,
compared_quantile=self._baseline_quantile,
)
efficiency_baseline = baseline_comparator.curve()
compared_comparator = LogEfficiencyConvergenceCurveComparator( # pyrefly: ignore[missing-argument]
baseline_curve=combined_curve, # pyrefly: ignore[unexpected-keyword]
compared_curve=extended_compared, # pyrefly: ignore[unexpected-keyword]
compared_quantile=self._compared_quantile, # pyrefly: ignore[unexpected-keyword]
compared_comparator = LogEfficiencyConvergenceCurveComparator(
baseline_curve=combined_curve,
compared_curve=extended_compared,
compared_quantile=self._compared_quantile,
)
efficiency_compared = compared_comparator.curve()

Expand Down Expand Up @@ -878,7 +878,7 @@ def _compute_directional_score(
(len(compared) - i) / len(compared) if i != float('inf') else 0
for i in convergence_curve
]
return np.mean(pct_baseline_compared) # pyrefly: ignore[bad-return]
return np.mean(pct_baseline_compared)

def score(self) -> float:
"""Computes the percentage better score.
Expand Down Expand Up @@ -1003,13 +1003,13 @@ def __call__( # pyrefly: ignore[bad-override]
compared_quantile: float = 0.5,
steps_cutoff: Optional[int] = None,
) -> ConvergenceComparator:
return OptimalityGapWinRateComparator( # pyrefly: ignore[missing-argument]
baseline_curve=baseline_curve, # pyrefly: ignore[unexpected-keyword]
compared_curve=compared_curve, # pyrefly: ignore[unexpected-keyword]
baseline_quantile=baseline_quantile, # pyrefly: ignore[unexpected-keyword]
compared_quantile=compared_quantile, # pyrefly: ignore[unexpected-keyword]
name='optimality_gap_win_rate', # pyrefly: ignore[unexpected-keyword]
steps_cutoff=steps_cutoff, # pyrefly: ignore[unexpected-keyword]
return OptimalityGapWinRateComparator(
baseline_curve=baseline_curve,
compared_curve=compared_curve,
baseline_quantile=baseline_quantile,
compared_quantile=compared_quantile,
name='optimality_gap_win_rate',
steps_cutoff=steps_cutoff,
)


Expand All @@ -1024,13 +1024,13 @@ def __call__( # pyrefly: ignore[bad-override]
compared_quantile: float = 0.5,
steps_cutoff: Optional[int] = None,
) -> ConvergenceComparator:
return OptimalityGapGainComparator( # pyrefly: ignore[missing-argument]
baseline_curve=baseline_curve, # pyrefly: ignore[unexpected-keyword]
compared_curve=compared_curve, # pyrefly: ignore[unexpected-keyword]
baseline_quantile=baseline_quantile, # pyrefly: ignore[unexpected-keyword]
compared_quantile=compared_quantile, # pyrefly: ignore[unexpected-keyword]
name='optimality_gap_gain', # pyrefly: ignore[unexpected-keyword]
steps_cutoff=steps_cutoff, # pyrefly: ignore[unexpected-keyword]
return OptimalityGapGainComparator(
baseline_curve=baseline_curve,
compared_curve=compared_curve,
baseline_quantile=baseline_quantile,
compared_quantile=compared_quantile,
name='optimality_gap_gain',
steps_cutoff=steps_cutoff,
)


Expand All @@ -1048,14 +1048,14 @@ def __call__( # pyrefly: ignore[bad-override]
compared_quantile: float = 0.5,
steps_cutoff: Optional[int] = None,
) -> ConvergenceComparator:
return WinRateConvergenceCurveComparator( # pyrefly: ignore[missing-argument]
baseline_curve=baseline_curve, # pyrefly: ignore[unexpected-keyword]
compared_curve=compared_curve, # pyrefly: ignore[unexpected-keyword]
baseline_quantile=baseline_quantile, # pyrefly: ignore[unexpected-keyword]
compared_quantile=compared_quantile, # pyrefly: ignore[unexpected-keyword]
name='convergence_curve_win_rate', # pyrefly: ignore[unexpected-keyword]
return WinRateConvergenceCurveComparator(
baseline_curve=baseline_curve,
compared_curve=compared_curve,
baseline_quantile=baseline_quantile,
compared_quantile=compared_quantile,
name='convergence_curve_win_rate',
comparison_mode=self.comparison_mode,
steps_cutoff=steps_cutoff, # pyrefly: ignore[unexpected-keyword]
steps_cutoff=steps_cutoff,
)


Expand All @@ -1072,13 +1072,13 @@ def __call__( # pyrefly: ignore[bad-override]
compared_quantile: float = 0.5,
steps_cutoff: Optional[int] = None,
) -> ConvergenceComparator:
return LogEfficiencyConvergenceCurveComparator( # pyrefly: ignore[missing-argument]
baseline_curve=baseline_curve, # pyrefly: ignore[unexpected-keyword]
compared_curve=compared_curve, # pyrefly: ignore[unexpected-keyword]
baseline_quantile=baseline_quantile, # pyrefly: ignore[unexpected-keyword]
compared_quantile=compared_quantile, # pyrefly: ignore[unexpected-keyword]
name='log_eff', # pyrefly: ignore[unexpected-keyword]
steps_cutoff=steps_cutoff, # pyrefly: ignore[unexpected-keyword]
return LogEfficiencyConvergenceCurveComparator(
baseline_curve=baseline_curve,
compared_curve=compared_curve,
baseline_quantile=baseline_quantile,
compared_quantile=compared_quantile,
name='log_eff',
steps_cutoff=steps_cutoff,
)


Expand All @@ -1095,13 +1095,13 @@ def __call__( # pyrefly: ignore[bad-override]
compared_quantile: float = 0.5,
steps_cutoff: Optional[int] = None,
) -> ConvergenceComparator:
return PercentageBetterConvergenceCurveComparator( # pyrefly: ignore[missing-argument]
baseline_curve=baseline_curve, # pyrefly: ignore[unexpected-keyword]
compared_curve=compared_curve, # pyrefly: ignore[unexpected-keyword]
baseline_quantile=baseline_quantile, # pyrefly: ignore[unexpected-keyword]
compared_quantile=compared_quantile, # pyrefly: ignore[unexpected-keyword]
name='pct_better', # pyrefly: ignore[unexpected-keyword]
steps_cutoff=steps_cutoff, # pyrefly: ignore[unexpected-keyword]
return PercentageBetterConvergenceCurveComparator(
baseline_curve=baseline_curve,
compared_curve=compared_curve,
baseline_quantile=baseline_quantile,
compared_quantile=compared_quantile,
name='pct_better',
steps_cutoff=steps_cutoff,
)


Expand Down
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