def test_basic(self):
num_runs = 3
total_iterations = 2
suite = BOBenchmarkingSuite()
runner = suite.run(
num_runs=num_runs,
total_iterations=total_iterations,
bo_strategies=BOStrategies,
bo_problems=BOProblems,
)
self.assertEqual(
len(runner._runs.items()), len(BOStrategies) * len(BOProblems) * num_runs
)
# If run_benchmarking_trial fails, corresponding trial in '_runs' is None.
self.assertTrue(all(x is not None for x in runner._runs.values()))
# Make sure no errors came up in running trials.
runner.aggregate_results()
# Also test that the suite works with batch trials.
BOBenchmarkingSuite().run(
num_runs=num_runs,
total_iterations=total_iterations,
bo_strategies=BOStrategies,
bo_problems=BOProblems,
batch_size=2,
)
report = suite.generate_report()
self.assertIsInstance(report, str)
def test_sobol(self):
suite = BOBenchmarkingSuite()
runner = suite.run(
num_runs=1,
total_iterations=5,
batch_size=2,
bo_strategies=[
GenerationStrategy(
[GenerationStep(model=Models.SOBOL, num_arms=10)])
],
bo_problems=[branin],
)
# If run_benchmarking_trial fails, corresponding trial in '_runs' is None.
self.assertTrue(all(x is not None for x in runner._runs.values()))
# Make sure no errors came up in running trials.
self.assertEqual(len(runner.errors), 0)
report = suite.generate_report()
self.assertIsInstance(report, str)
# Add a trial
setup = BenchmarkSetup(problem=branin,
total_iterations=10,
batch_size=1)
suite.add_run(setup=setup, strategy_name="strategy_name")
self.assertTrue(("Branin", "strategy_name", 0) in suite._runner._runs)
suite.add_run(setup=setup, strategy_name="strategy_name")
self.assertTrue(("Branin", "strategy_name", 1) in suite._runner._runs)
def testRelativeConstraint(self):
branin_rel = BenchmarkProblem(
name="constrained_branin",
fbest=0.397887,
optimization_config=OptimizationConfig(
objective=Objective(
metric=BraninMetric(name="branin_objective",
param_names=["x1", "x2"],
noise_sd=5.0),
minimize=True,
),
outcome_constraints=[
OutcomeConstraint(
metric=L2NormMetric(
name="branin_constraint",
param_names=["x1", "x2"],
noise_sd=5.0,
),
op=ComparisonOp.LEQ,
bound=5.0,
relative=True,
)
],
),
search_space=get_branin_search_space(),
)
suite = BOBenchmarkingSuite()
suite.run(
num_runs=1,
total_iterations=5,
bo_strategies=[
GenerationStrategy(
[GenerationStep(model=Models.SOBOL, num_arms=5)])
],
bo_problems=[branin_rel],
)
with self.assertRaises(ValueError):
suite.generate_report()
def testLowerBound(self):
branin_lb = BenchmarkProblem(
name="constrained_branin",
fbest=0.397887,
optimization_config=OptimizationConfig(
objective=Objective(
metric=BraninMetric(name="branin_objective",
param_names=["x1", "x2"],
noise_sd=5.0),
minimize=True,
),
outcome_constraints=[
OutcomeConstraint(
metric=L2NormMetric(
name="branin_constraint",
param_names=["x1", "x2"],
noise_sd=5.0,
),
op=ComparisonOp.GEQ,
bound=5.0,
relative=False,
)
],
),
search_space=get_branin_search_space(),
)
suite = BOBenchmarkingSuite()
suite.run(
num_runs=1,
batch_size=2,
total_iterations=4,
bo_strategies=[
GenerationStrategy(
[GenerationStep(model=Models.SOBOL, num_arms=5)])
],
bo_problems=[branin_lb],
)
suite.generate_report(include_individual=True)
def test_repeat_problem_method_combo(self):
suite = BOBenchmarkingSuite()
runner = suite.run(
num_runs=1,
total_iterations=1,
bo_strategies=[
GenerationStrategy([GenerationStep(model=Models.SOBOL, num_arms=5)])
]
* 2,
bo_problems=BOProblems,
)
self.assertRegex(runner.errors[0], r"^Run [0-9]* of .* on")
self.assertGreater(len(runner._runs), 0)
report = suite.generate_report()
self.assertIsInstance(report, str)