def test_bo_gp_mcmc_model(): domain = Domain({"x": [-1., 6.]}) bayes_opt = bo.BayesianOptimization(domain=domain, seed=7) test_utils.evaluate_continuous_1d(bayes_opt, batch_size=1, n_steps=7, model="GP_MCMC", evaluator_type="sequential")
def test_bo_simple_mixed(): domain = Domain({"x": [-5., 6.], "y": {"sin", "sqr"}, "z": set(range(4))}) bayes_opt = bo.BayesianOptimization(domain=domain, seed=7) test_utils.evaluate_heterogeneous_3d(bayes_opt, batch_size=7, n_steps=3)
def test_bo_simple_continuous(): domain = Domain({"x": [-1., 6.]}) bayes_opt = bo.BayesianOptimization(domain=domain, seed=7) test_utils.evaluate_continuous_1d(bayes_opt, batch_size=2, n_steps=7)