def test_update(self, _mock_update, _mock_gen):
exp = get_experiment_for_value()
exp.optimization_config = get_optimization_config_no_constraints()
ss = get_search_space_for_range_values()
exp.search_space = ss
modelbridge = ModelBridge(
search_space=ss, model=Model(), transforms=[Log], experiment=exp
)
exp.new_trial(generator_run=modelbridge.gen(1))
modelbridge._set_training_data(
observations_from_data(
data=Data(
pd.DataFrame(
[
{
"arm_name": "0_0",
"metric_name": "m1",
"mean": 3.0,
"sem": 1.0,
}
]
)
),
experiment=exp,
),
ss,
)
exp.new_trial(generator_run=modelbridge.gen(1))
modelbridge.update(
new_data=Data(
pd.DataFrame(
[{"arm_name": "1_0", "metric_name": "m1", "mean": 5.0, "sem": 0.0}]
)
),
experiment=exp,
)
exp.new_trial(generator_run=modelbridge.gen(1))
# Trying to update with unrecognised metric should error.
with self.assertRaisesRegex(ValueError, "Unrecognised metric"):
modelbridge.update(
new_data=Data(
pd.DataFrame(
[
{
"arm_name": "1_0",
"metric_name": "m2",
"mean": 5.0,
"sem": 0.0,
}
]
)
),
experiment=exp,
)
def test_gen_on_experiment_with_imm_ss_and_opt_conf(self, _, __):
exp = get_experiment_for_value()
exp._properties[Keys.IMMUTABLE_SEARCH_SPACE_AND_OPT_CONF] = True
exp.optimization_config = get_optimization_config_no_constraints()
ss = get_search_space_for_range_value()
modelbridge = ModelBridge(search_space=ss,
model=Model(),
transforms=[],
experiment=exp)
self.assertTrue(
modelbridge._experiment_has_immutable_search_space_and_opt_config)
gr = modelbridge.gen(1)
self.assertIsNone(gr.optimization_config)
self.assertIsNone(gr.search_space)
def testGenWithDefaults(self, _, mock_gen):
exp = get_experiment_for_value()
exp.optimization_config = get_optimization_config_no_constraints()
ss = get_search_space_for_range_value()
modelbridge = ModelBridge(ss, None, [], exp)
modelbridge.gen(1)
mock_gen.assert_called_with(
modelbridge,
n=1,
search_space=ss,
fixed_features=ObservationFeatures(parameters={}),
model_gen_options=None,
optimization_config=OptimizationConfig(
objective=Objective(metric=Metric("test_metric"),
minimize=False),
outcome_constraints=[],
),
pending_observations={},
)
