def test_creation_algorithms(self, benchmark):
"""Test study creation with all support algorithms input format"""
algorithms = [
{"algorithm": {"gridsearch": {"n_values": 1}}, "deterministic": True},
{"algorithm": "tpe"},
{"random": {"seed": 1}},
"asha",
]
study = Study(benchmark, algorithms, AverageResult(2), RosenBrock(25, dim=3))
assert study.algorithms[0].name == "gridsearch"
assert study.algorithms[0].experiment_algorithm == {
"gridsearch": {"n_values": 1}
}
assert study.algorithms[0].is_deterministic
assert study.algorithms[1].name == "tpe"
assert study.algorithms[1].experiment_algorithm == "tpe"
assert not study.algorithms[1].is_deterministic
assert study.algorithms[2].name == "random"
assert study.algorithms[2].experiment_algorithm == {"random": {"seed": 1}}
assert not study.algorithms[2].is_deterministic
assert study.algorithms[3].name == "asha"
assert study.algorithms[3].experiment_algorithm == "asha"
assert not study.algorithms[3].is_deterministic
def test_create_with_invalid_targets(self, benchmark_config_py):
"""Test creation with invalid Task and Assessment"""
with OrionState():
with pytest.raises(AttributeError) as exc:
config = copy.deepcopy(benchmark_config_py)
config["targets"] = [{
"assess": [AverageResult(2)],
"task": [DummyTask]
}]
get_or_create_benchmark(**config)
assert "type object '{}' has no attribute ".format(
"DummyTask") in str(exc.value)
with pytest.raises(AttributeError) as exc:
config = copy.deepcopy(benchmark_config_py)
config["targets"] = [{
"assess": [DummyAssess],
"task": [RosenBrock(25, dim=3)]
}]
get_or_create_benchmark(**config)
assert "type object '{}' has no attribute ".format(
"DummyAssess") in str(exc.value)
def test_create_with_different_configure(self, benchmark_config_py,
caplog):
"""Test creation with same name but different configure"""
with OrionState():
config = copy.deepcopy(benchmark_config_py)
bm1 = get_or_create_benchmark(**config)
config = copy.deepcopy(benchmark_config_py)
config["targets"][0]["assess"] = [AverageResult(2)]
with caplog.at_level(logging.WARNING,
logger="orion.benchmark.benchmark_client"):
bm2 = get_or_create_benchmark(**config)
assert bm2.configuration == bm1.configuration
assert (
"Benchmark with same name is found but has different configuration, "
"which will be used for this creation." in caplog.text)
caplog.clear()
config = copy.deepcopy(benchmark_config_py)
config["targets"][0]["task"] = [
RosenBrock(26, dim=3), CarromTable(20)
]
with caplog.at_level(logging.WARNING,
logger="orion.benchmark.benchmark_client"):
bm3 = get_or_create_benchmark(**config)
assert bm3.configuration == bm1.configuration
assert (
"Benchmark with same name is found but has different configuration, "
"which will be used for this creation." in caplog.text)
def test_call(self):
"""Test to get task function"""
rb = RosenBrock(2)
assert callable(rb)
objectives = rb([1, 2])
assert type(objectives[0]) == dict
def test_creation(self):
"""Test creation"""
branin = RosenBrock(max_trials=2, dim=3)
assert branin.max_trials == 2
assert branin.configuration == {
"RosenBrock": {
"dim": 3,
"max_trials": 2
}
}
def benchmark_config_py(benchmark_algorithms):
config = dict(
name="bm00001",
algorithms=benchmark_algorithms,
targets=[{
"assess": [AverageResult(2), AverageRank(2)],
"task": [RosenBrock(25, dim=3),
CarromTable(20)],
}],
)
return config
def benchmark(benchmark_algorithms):
"""Return a benchmark instance"""
return Benchmark(
name="benchmark007",
algorithms=benchmark_algorithms,
targets=[{
"assess": [AverageResult(2), AverageRank(2)],
"task": [RosenBrock(25, dim=3),
CarromTable(20)],
}],
)
def test_simple():
"""Test a end 2 end exucution of benchmark"""
task_num = 2
trial_num = 20
assessments = [AverageResult(task_num), AverageRank(task_num)]
tasks = [
RosenBrock(trial_num, dim=3),
EggHolder(trial_num, dim=4),
CarromTable(trial_num),
Branin(trial_num),
BirdLike(trial_num),
]
benchmark = get_or_create_benchmark(
name="bm001",
algorithms=algorithms,
targets=[{
"assess": assessments,
"task": tasks
}],
)
benchmark.process()
assert len(benchmark.studies) == len(assessments) * len(tasks)
status = benchmark.status()
experiments = benchmark.experiments()
assert len(experiments
) == len(algorithms) * task_num * len(assessments) * len(tasks)
assert len(status) == len(algorithms) * len(assessments) * len(tasks)
figures = benchmark.analysis()
assert len(figures) == len(benchmark.studies)
assert type(figures[0]) is plotly.graph_objects.Figure
benchmark = get_or_create_benchmark(name="bm001")
figures = benchmark.analysis()
assert len(figures) == len(benchmark.studies)
assert type(figures[0]) is plotly.graph_objects.Figure
def study(benchmark, benchmark_algorithms):
"""Return a study instance"""
with benchmark.executor:
yield Study(
benchmark, benchmark_algorithms, AverageResult(2), RosenBrock(25, dim=3)
)
def test_search_space(self):
"""Test to get task search space"""
rb = RosenBrock(2)
assert rb.get_search_space() == {"x": "uniform(-5, 10, shape=2)"}
def study(benchmark, benchmark_algorithms):
"""Return a study instance"""
return Study(
benchmark, benchmark_algorithms, AverageResult(2), RosenBrock(25, dim=3)
)