8000 Additional shape check for the features and labels for DefaultTrialConverter. by copybara-service[bot] · Pull Request #559 · google/vizier · GitHub
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Additional shape check for the features and labels for DefaultTrialConverter. #559

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Merged
copybara-service merged 1 commit into from
Mar 11, 2023
Merged

Additional shape check for the features and labels for DefaultTrialConverter. #559

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8000
29 changes: 26 additions & 3 deletions vizier/pyvizier/converters/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -895,17 +895,40 @@ def to_trials(
Args:
features: A dictionary where keys correspond to parameter names in the
returned Trial and values correspond to parameter values and have shape
(num_obs, ) or (num_obs, 1).
(num_obs, 1).
labels: A dictionary of labels where each key corresponds to a metric name
and its value is an array of shape (num_obs,) or (num_obs, 1) of oberved
metric values.
and its value is an array of shape (num_obs, 1) of observed metric
values.

Returns:
A list of pyvizier trials created with parameters corresponding to
`features` and final measurements corresponding to `labels`.
NOTE: All final measurements have steps=1. If 'labels' is not passed, the
output trials include `final_measurement=None` and `measurements=[]`.
"""
invalid_features = [
(k, v.shape)
for k, v in features.items()
if len(v.shape) != 2 or (len(v.shape) == 2 and v.shape[1] != 1)
]
if invalid_features:
raise ValueError(
'Features need to contain 2d arrays with shape (num_obs, 1). Invalid'
f' feature shapes: {invalid_features}'
)

if labels:
invalid_labels = [
(k, v.shape)
for k, v in labels.items()
if len(v.shape) != 2 or (len(v.shape) == 2 and v.shape[1] != 1)
]
if invalid_labels:
raise ValueError(
'Labels need to contain 2d arrays with shape (num_obs, 1). Invalid'
f' label shapes: {invalid_labels}'
)

if labels is None:
return [
pyvizier.Trial(parameters=p) for p in self.to_parameters(features)
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57 changes: 57 additions & 0 deletions vizier/pyvizier/converters/core_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -399,6 +399,63 @@ def test_infeasible_trials(self):
if np.isnan(label):
self.assertEmpty(t.final_measurement.metrics)

def test_parameters_and_labels_shape(self):
study_config = pyvizier.ProblemStatement()
root = study_config.search_space.root
root.add_float_param('x1', 0.0, 10.0)

study_config.metric_information.extend([
pyvizier.MetricInformation(
name='y1', goal=pyvizier.ObjectiveMetricGoal.MAXIMIZE
),
pyvizier.MetricInformation(
name='y2', goal=pyvizier.ObjectiveMetricGoal.MINIMIZE
),
])
converter = core.DefaultTrialConverter.from_study_config(study_config)
features_1d = {
'x1': np.array([1.0, 3.0]),
'x2': np.array([2.0, 4.0]),
}

with self.assertRaisesRegex(
ValueError,
'Features need to contain 2d arrays with shape (num_obs, 1)*',
):
converter.to_trials(features_1d)

features_right_shape = {
'x1': np.array([[1.0, 3.0]]).T,
'x2': np.array([[2.0, 4.0]]).T,
}
labels_1d = {
'y1': np.array([10.0, 40.0]),
'y2': np.array([20.0, 50.0]),
}
with self.assertRaisesRegex(
ValueError, 'Labels need to contain 2d arrays with shape (num_obs, 1)*'
):
converter.to_trials(features_right_shape, labels_1d)

features_2d_reverse_shape = {
'x1': np.array([[1.0, 3.0]]),
'x2': np.array([[2.0, 4.0]]),
}
with self.assertRaisesRegex(
ValueError,
'Features need to contain 2d arrays with shape (num_obs, 1)*',
):
converter.to_trials(features_2d_reverse_shape)

labels_2d_reverse_shape = {
'y1': np.array([[10.0, 40.0]]),
'y2': np.array([[20.0, 50.0]]),
}
with self.assertRaisesRegex(
ValueError, 'Labels need to contain 2d arrays with shape (num_obs, 1)*'
):
converter.to_trials(features_right_shape, labels_2d_reverse_shape)

def test_metrics(self):
converter = core.DefaultTrialConverter.from_study_configs(
[],
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0