diff --git a/optuna/integration/botorch.py b/optuna/integration/botorch.py
index 54ee6c8fd6..2e49984b83 100644
--- a/optuna/integration/botorch.py
+++ b/optuna/integration/botorch.py
@@ -883,6 +883,9 @@ def reseed_rng(self) -> None:
         if self._seed is not None:
             self._seed = numpy.random.RandomState().randint(numpy.iinfo(numpy.int32).max)
 
+    def before_trial(self, study: Study, trial: FrozenTrial) -> None:
+        self._independent_sampler.before_trial(study, trial)
+
     def after_trial(
         self,
         study: Study,
diff --git a/optuna/integration/cma.py b/optuna/integration/cma.py
index 0bce5db94c..24506b600d 100644
--- a/optuna/integration/cma.py
+++ b/optuna/integration/cma.py
@@ -291,6 +291,9 @@ def _log_independent_sampling(self, trial: FrozenTrial, param_name: str) -> None
             )
         )
 
+    def before_trial(self, study: Study, trial: FrozenTrial) -> None:
+        self._independent_sampler.before_trial(study, trial)
+
     def after_trial(
         self,
         study: Study,
diff --git a/optuna/samplers/_cmaes.py b/optuna/samplers/_cmaes.py
index 920dcc48c6..9233f1219d 100644
--- a/optuna/samplers/_cmaes.py
+++ b/optuna/samplers/_cmaes.py
@@ -1,3 +1,5 @@
+from __future__ import annotations
+
 import copy
 import math
 import pickle
@@ -779,6 +781,9 @@ def _get_solution_trials(
         generation_attr_key = self._attr_keys.generation(n_restarts)
         return [t for t in trials if generation == t.system_attrs.get(generation_attr_key, -1)]
 
+    def before_trial(self, study: optuna.Study, trial: FrozenTrial) -> None:
+        self._independent_sampler.before_trial(study, trial)
+
     def after_trial(
         self,
         study: "optuna.Study",
diff --git a/optuna/samplers/_nsgaiii.py b/optuna/samplers/_nsgaiii.py
index 93b1a0b08c..2ba357745d 100644
--- a/optuna/samplers/_nsgaiii.py
+++ b/optuna/samplers/_nsgaiii.py
@@ -315,6 +315,9 @@ def _select_elite_population(
                 break
         return elite_population
 
+    def before_trial(self, study: Study, trial: FrozenTrial) -> None:
+        self._random_sampler.before_trial(study, trial)
+
     def after_trial(
         self,
         study: Study,
diff --git a/optuna/samplers/_partial_fixed.py b/optuna/samplers/_partial_fixed.py
index 050f2593d3..d8eb62f914 100644
--- a/optuna/samplers/_partial_fixed.py
+++ b/optuna/samplers/_partial_fixed.py
@@ -106,6 +106,9 @@ def sample_independent(
                 )
             return param_value
 
+    def before_trial(self, study: Study, trial: FrozenTrial) -> None:
+        self._base_sampler.before_trial(study, trial)
+
     def after_trial(
         self,
         study: Study,
diff --git a/optuna/samplers/_qmc.py b/optuna/samplers/_qmc.py
index bce3d7fa3c..b9d15f6238 100644
--- a/optuna/samplers/_qmc.py
+++ b/optuna/samplers/_qmc.py
@@ -249,6 +249,9 @@ def sample_relative(
         sample = trans.bounds[:, 0] + sample * (trans.bounds[:, 1] - trans.bounds[:, 0])
         return trans.untransform(sample[0, :])
 
+    def before_trial(self, study: Study, trial: FrozenTrial) -> None:
+        self._independent_sampler.before_trial(study, trial)
+
     def after_trial(
         self,
         study: "optuna.Study",
diff --git a/optuna/samplers/_tpe/sampler.py b/optuna/samplers/_tpe/sampler.py
index f0317d3c45..a725176c8d 100644
--- a/optuna/samplers/_tpe/sampler.py
+++ b/optuna/samplers/_tpe/sampler.py
@@ -553,6 +553,9 @@ def objective(trial):
             "weights": default_weights,
         }
 
+    def before_trial(self, study: Study, trial: FrozenTrial) -> None:
+        self._random_sampler.before_trial(study, trial)
+
     def after_trial(
         self,
         study: Study,
diff --git a/optuna/samplers/nsgaii/_sampler.py b/optuna/samplers/nsgaii/_sampler.py
index bf03bd4eed..6c081a87c9 100644
--- a/optuna/samplers/nsgaii/_sampler.py
+++ b/optuna/samplers/nsgaii/_sampler.py
@@ -355,6 +355,9 @@ def _collect_parent_population(self, study: Study) -> tuple[int, list[FrozenTria
 
         return parent_generation, parent_population
 
+    def before_trial(self, study: Study, trial: FrozenTrial) -> None:
+        self._random_sampler.before_trial(study, trial)
+
     def after_trial(
         self,
         study: Study,