8000 Modify the Harmonica algorithm to work with discrete, integer and categorical parameters with two values. by copybara-service[bot] · Pull Request #1253 · google/vizier · GitHub
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Modify the Harmonica algorithm to work with discrete, integer and categorical parameters with two values. #1253

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Modify the Harmonica algorithm to work with discrete, integer and categorical parameters with two values. #1253

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18 changes: 15 additions & 3 deletions vizier/_src/algorithms/designers/harmonica.py
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Original file line number Diff line number Diff line change
Expand Up @@ -272,8 +272,14 @@ def __init__(
f'This designer {self} does not support conditional search.'
)
for p_config in problem_statement.search_space.parameters:
if p_config.external_type != vz.ExternalType.BOOLEAN:
raise ValueError('Only boolean search spaces are supported.')
if p_config.external_type != vz.ExternalType.BOOLEAN and (
p_config.type == vz.ParameterType.DOUBLE
or len(p_config.feasible_values) != 2
):
raise ValueError(
'Only boolean search spaces are supported, bot got parameter'
f' config: f{p_config}'
)

self._problem_statement = problem_statement
self._metric_name = self._problem_statement.metric_information.item().name
Expand Down Expand Up @@ -345,5 +351,11 @@ def suggest(

parameters = vz.ParameterDict()
for i, p in enumerate(self._search_space.parameters):
parameters[p.name] = 'True' if x_new[i] == 1.0 else 'False'
if p.external_type == vz.ExternalType.BOOLEAN:
parameters[p.name] = 'True' if x_new[i] == 1.0 else 'False'
else:
parameters[p.name] = (
p.feasible_values[1] if x_new[i] == 1.0 else p.feasible_values[0]
)

return [vz.TrialSuggestion(parameters=parameters)]
85 changes: 85 additions & 0 deletions vizier/_src/algorithms/designers/harmonica_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,9 +15,11 @@
from __future__ import annotations

"""Tests for bocs."""
from vizier import pyvizier as vz
from vizier._src.algorithms.designers import harmonica
from vizier._src.algorithms.testing import test_runners
from vizier._src.benchmarks.experimenters import combo_experimenter
from vizier.testing import test_studies

from absl.testing import absltest

Expand All @@ -39,6 +41,89 @@ def test_make_suggestions(self):
validate_parameters=True)
self.assertLen(trials, num_trials)

def test_make_suggestions_with_two_values(self):
space = vz.SearchSpace()
root = space.root
root.add_int_param('integer_0', 11, 12)
root.add_discrete_param('discrete_0', feasible_values=[1001, 2034])
root.add_categorical_param('categorical_0', feasible_values=['a', 'b'])
root.add_bool_param('bool_0')
problem_statement = vz.ProblemStatement(space)
problem_statement.metric_information.append(
vz.MetricInformation(
name='main_objective', goal=vz.ObjectiveMetricGoal.MAXIMIZE
)
)
designer = harmonica.HarmonicaDesigner(
problem_statement, num_init_samples=1
)
num_trials = 10
trials = test_runners.run_with_random_metrics(
designer,
problem_statement,
iters=num_trials,
batch_size=1,
verbose=1,
validate_parameters=True,
)
self.assertLen(trials, num_trials)

def test_categorical_search_space_with_more_than_two_values_raises_error(
self,
):
experimenter = combo_experimenter.CentroidExperimenter(centroid_n_choice=3)
with self.assertRaisesRegex(
ValueError, 'Only boolean search spaces are supported'
):
_ = harmonica.HarmonicaDesigner(
experimenter.problem_statement(), num_init_samples=1
)

def test_integer_search_space_with_more_than_two_values_raises_error(
self,
):
space = vz.SearchSpace()
root = space.root
root.add_int_param('integer_0', 11, 13)
problem_statement = vz.ProblemStatement(space)
problem_statement.metric_information.append(
vz.MetricInformation(
name='main_objective', goal=vz.ObjectiveMetricGoal.MAXIMIZE
)
)
with self.assertRaisesRegex(
ValueError, 'Only boolean search spaces are supported'
):
_ = harmonica.HarmonicaDesigner(problem_statement, num_init_samples=1)

def test_discrete_search_space_with_more_than_two_values_raises_error(
self,
):
space = vz.SearchSpace()
root = space.root
root.add_discrete_param('discrete_0', feasible_values=[1001, 2034, 3000])
problem_statement = vz.ProblemStatement(space)
problem_statement.metric_information.append(
vz.MetricInformation(
name='main_objective', goal=vz.ObjectiveMetricGoal.MAXIMIZE
)
)
with self.assertRaisesRegex(
ValueError, 'Only boolean search spaces are supported'
):
_ = harmonica.HarmonicaDesigner(problem_statement, num_init_samples=1)

def test_continuous_search_space_raises_error(self):
with self.assertRaisesRegex(
ValueError, 'Only boolean search spaces are supported'
):
_ = harmonica.HarmonicaDesigner(
vz.ProblemStatement(
test_studies.flat_continuous_space_with_scaling()
),
num_init_samples=1,
)


if __name__ == '__main__':
absltest.main()
0