import pytest
from optuna.testing.pytest_samplers import SamplerTestCase

class TestTurboSampler(SamplerTestCase):
    @pytest.fixture
    def sampler_class(self):
        return TuRBOSampler()

    @pytest.fixture
    def relative_sampler_class(self):
        pytest.skip("Relative Sampler cannot be tested since TuRBOSampler requires startup trials.")
    
    @pytest.fixture
    def multi_objective_sampler_class(self):
        pytest.skip("TurboSampler does not support multi-objective optimization.")

    @pytest.fixture
    def single_only_sampler_class(self):
        return TuRBOSampler()
    

import pytest
from optuna.testing.pytest_samplers import SamplerTestCase

@pytest.fixture
def sampler():
    return TurboSampler(...)

class TestTurboSampler(SamplerTestCase):
    SUPPORTS_RELATIVE = False 
    SUPPORTS_MULTI_OBJECTIVE = False
    SUPPORTS_SINGLE_ONLY = True

from collections.abc import Callable
import pytest

import optuna
from optuna.samplers import BaseSampler
from optuna.testing.pytest_samplers import BasicSamplerTestCase
from optuna.testing.pytest_samplers import MultiObjectiveSamplerTestCase
from optuna.testing.pytest_samplers import RelativeSamplerTestCase
from optuna.testing.pytest_samplers import SingleOnlySamplerTestCase

# Example 1
class TestSampler1(BasicSamplerTestCase, MultiObjectiveSamplerTestCase):
    @pytest.fixture
    def sampler(self) -> Callable[[], BaseSampler]:
        return optuna.samplers.TPESampler

# Example 2
class TestSampler2(RelativeSamplerTestCase):
    @pytest.fixture
    def sampler(self) -> Callable[[], BaseSampler]:
        return lambda: optuna.samplers.TPESampler(multivariate=True, n_startup_trials=0)

# Example 3
class TestSampler3(SingleOnlySamplerTestCase):
    @pytest.fixture
    def sampler(self) -> Callable[[], BaseSampler]:
        return optuna.samplers.CmaEsSampler

    def test_user_defined(self, sampler) -> None:
        # Additional test can be defined if necessary.
        assert sampler.__name__ == "CmaEsSampler"