Update recipes/007_benchmarks_advanced.py

Co-authored-by: Shuhei Watanabe <[email protected]>

recipes/007_benchmarks_advanced.py

@@ -87,7 +87,7 @@ def evaluate_constraints(self, params: dict[str, float]) -> tuple[float]:
 
 ###################################################################################################
 # Then, you can optimize the problem with Optuna as usual.
-# Don't forget to set the `constraints_func` argument of the sampler to the `constraints_func` of the problem.
+# Don't forget to set the `constraints_func` argument to the sampler to use.
 problem = ConstrainedProblem()
 sampler = optuna.samplers.TPESampler(
     constraints_func=problem.constraints_func