f81184a1a925ec6afaa7388b306398252f7fa45f,tests/multi_objective/samplers_tests/test_nsga2.py,,test_population_size,#,11

Before Change

    study = multi_objective.create_study(["minimize"], sampler=sampler)
    study.optimize(lambda t: [t.suggest_uniform("x", 0, 9)], n_trials=40)

    generations = defaultdict(int)
    for t in study.trials:
        generations[t.system_attrs[multi_objective.samplers._nsga2._GENERATION_KEY]] += 1
    assert dict(generations) == {0: 10, 1: 10, 2: 10, 3: 10}

    // Set `population_size` to 2.
    sampler = multi_objective.samplers.NSGAIIMultiObjectiveSampler(population_size=2)

After Change

    study.optimize(lambda t: [t.suggest_uniform("x", 0, 9)], n_trials=40)

    generations = Counter(
        [t.system_attrs[multi_objective.samplers._nsga2._GENERATION_KEY] for t in study.trials]
    )
    assert generations == {0: 10, 1: 10, 2: 10, 3: 10}

    // Set `population_size` to 2.

Instances