Merge pull request optuna#2425 from jeromepatel/motpesampler-after-trial

`after_trial` implemented for `MOTPESampler`

optuna/samplers/_tpe/multi_objective_sampler.py

@@ -5,6 +5,7 @@
 from typing import Dict
 from typing import List
 from typing import Optional
+from typing import Sequence
 from typing import Tuple
 
 import numpy as np
@@ -564,6 +565,16 @@ def _calculate_weights_below(
             weights_below = np.clip(contributions / np.max(contributions), 0, 1)
             return weights_below
 
+    def after_trial(
+        self,
+        study: optuna.study.Study,
+        trial: optuna.trial.FrozenTrial,
+        state: optuna.trial.TrialState,
+        values: Optional[Sequence[float]],
+    ) -> None:
+
+        self._mo_random_sampler.after_trial(study, trial, state, values)
+
 
 def _calculate_nondomination_rank(loss_vals: np.ndarray) -> np.ndarray:
     vecs = loss_vals.copy()

tests/samplers_tests/tpe_tests/test_multi_objective_sampler.py

@@ -687,3 +687,13 @@ def test_reseed_rng() -> None:
         sampler.reseed_rng()
         assert mock_object.call_count == 1
         assert original_seed != sampler._rng.seed
+
+
+def test_call_after_trial_of_mo_random_sampler() -> None:
+    sampler = MOTPESampler()
+    study = optuna.create_study(sampler=sampler)
+    with patch.object(
+        sampler._mo_random_sampler, "after_trial", wraps=sampler._mo_random_sampler.after_trial
+    ) as mock_object:
+        study.optimize(lambda _: 1.0, n_trials=1)
+        assert mock_object.call_count == 1