d1eb8732e44fac136862125dc7811f153f720b29,tests/samplers_tests/tpe_tests/test_sampler.py,,test_sample_independent_pruned_state,#,675

Before Change

def test_sample_independent_pruned_state() -> None:
    Tests PRUNED state is treated differently from both FAIL and COMPLETE.

    study = optuna.create_study()
    dist = optuna.distributions.UniformDistribution(1.0, 100.0)

    suggestions = []
    for state in [
        optuna.trial.TrialState.COMPLETE,
        optuna.trial.TrialState.FAIL,
        optuna.trial.TrialState.PRUNED,
    ]:
        state_fn = build_state_fn(state)
        past_trials = [frozen_trial_factory(i, dist=dist, state_fn=state_fn) for i in range(1, 30)]
        trial = frozen_trial_factory(30)
        sampler = TPESampler(n_startup_trials=5, seed=0)
        with patch.object(study._storage, "get_all_trials", return_value=past_trials):
            suggestions.append(sampler.sample_independent(study, trial, "param-a", dist))

    assert len(set(suggestions)) == 3


def test_get_observation_pairs() -> None:

After Change

        optuna.trial.TrialState.FAIL,
        optuna.trial.TrialState.PRUNED,
    ]:
        study = optuna.create_study()
        state_fn = build_state_fn(state)
        for i in range(1, 30):
            trial = frozen_trial_factory(i, dist=dist, state_fn=state_fn)
            study._storage.create_new_trial(study._study_id, template_trial=trial)
        trial = frozen_trial_factory(30)
        sampler = TPESampler(n_startup_trials=5, seed=0)
        suggestions.append(sampler.sample_independent(study, trial, "param-a", dist))

    assert len(set(suggestions)) == 3

Instances