From 3660dc994eeab722a397a32680382da614468184 Mon Sep 17 00:00:00 2001
From: ktz03 <2484593937@qq.com>
Date: Sun, 11 Oct 2026 14:30:12 +0800
Subject: [PATCH 1/2] Fix load-state parameter key validation

---
 bayes_opt/bayesian_optimization.py  |  4 ++++
 tests/test_bayesian_optimization.py | 23 +++++++++++++++++++++++
 2 files changed, 27 insertions(+)

diff --git a/bayes_opt/bayesian_optimization.py b/bayes_opt/bayesian_optimization.py
index 828bff27..737cb0e8 100644
--- a/bayes_opt/bayesian_optimization.py
+++ b/bayes_opt/bayesian_optimization.py
@@ -456,6 +456,10 @@ def _load_state_dict(self, state: dict[str, Any]) -> None:
         state : dict
             Dictionary containing the optimizer state.
         """
+        if state["keys"] != self._space.keys:
+            msg = "Saved state must have the same parameter keys in the same order as the optimizer."
+            raise ValueError(msg)
+
         params_array = np.asarray(state["params"], dtype=np.float64)
         target_array = np.asarray(state["target"], dtype=np.float64)
         constraint_array = (
diff --git a/tests/test_bayesian_optimization.py b/tests/test_bayesian_optimization.py
index 7fb9f4de..90f01056 100644
--- a/tests/test_bayesian_optimization.py
+++ b/tests/test_bayesian_optimization.py
@@ -368,6 +368,29 @@ def test_save_load_state(tmp_path):
     np.testing.assert_array_equal(optimizer.space.target, new_optimizer.space.target)
 
 
+@pytest.mark.parametrize("saved_points", [False, True])
+@pytest.mark.parametrize("existing_points", [False, True])
+@pytest.mark.parametrize("pbounds", [{"p2": (0, 10), "p1": (0, 10)}, {"width": (0, 10), "height": (0, 10)}])
+def test_load_state_rejects_incompatible_keys(tmp_path, saved_points, existing_points, pbounds):
+    original = BayesianOptimization(target_func, PBOUNDS, random_state=1, verbose=0)
+    if saved_points:
+        original.probe({"p1": 1, "p2": 2}, lazy=False)
+    state_path = tmp_path / "optimizer_state.json"
+    original.save_state(state_path)
+
+    restored = BayesianOptimization(target_func, pbounds, random_state=7, verbose=0)
+    if existing_points:
+        restored.probe(dict.fromkeys(pbounds, 0), lazy=False)
+    before = restored.res
+
+    with pytest.raises(ValueError, match="parameter keys.*same order"):
+        restored.load_state(state_path)
+
+    assert restored.res == before
+    control = BayesianOptimization(target_func, pbounds, random_state=7, verbose=0)
+    assert restored.random_sample(2) == control.random_sample(2)
+
+
 def test_save_load_w_categorical_params(tmp_path):
     """Test saving and loading optimizer state with categorical parameters."""
 

From e47d1a3fc583fe4bc4836c8c5deace16e99d2ccf Mon Sep 17 00:00:00 2001
From: ktz03 <2484593937@qq.com>
Date: Sun, 11 Oct 2026 14:43:17 +0800
Subject: [PATCH 2/2] Document incompatible-state regression coverage

---
 tests/test_bayesian_optimization.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/tests/test_bayesian_optimization.py b/tests/test_bayesian_optimization.py
index 90f01056..2788e192 100644
--- a/tests/test_bayesian_optimization.py
+++ b/tests/test_bayesian_optimization.py
@@ -372,6 +372,7 @@ def test_save_load_state(tmp_path):
 @pytest.mark.parametrize("existing_points", [False, True])
 @pytest.mark.parametrize("pbounds", [{"p2": (0, 10), "p1": (0, 10)}, {"width": (0, 10), "height": (0, 10)}])
 def test_load_state_rejects_incompatible_keys(tmp_path, saved_points, existing_points, pbounds):
+    """Reject incompatible keys without changing results or random-state progression."""
     original = BayesianOptimization(target_func, PBOUNDS, random_state=1, verbose=0)
     if saved_points:
         original.probe({"p1": 1, "p2": 2}, lazy=False)