Add validation of dists

package/samplers/hebo/sampler.py

@@ -26,6 +26,27 @@
 _logger = get_logger(f"optuna.{__name__}")
 
 
+def _validate_distributions(
+    param_name: str,
+    target_distribution: FloatDistribution | IntDistribution,
+    trials: list[FrozenTrial],
+) -> None:
+    assert not target_distribution.log and target_distribution.step is not None
+    dists = [t.distributions[param_name] for t in trials]
+    lows = np.asarray([d.low for d in dists])
+    highs = np.asarray([d.high for d in dists])
+    steps = np.asarray([d.step if d.step is not None else np.nan for d in dists])
+    if (
+        not np.allclose(target_distribution.low, lows)
+        or not np.allclose(target_distribution.high, highs)
+        or not np.allclose(target_distribution.step, steps)
+    ):
+        raise ValueError(
+            "When using the `step` option or `suggest_int`, `low`, `high`, and `step` cannot be "
+            f"modified during study, but modifications were detected in `{param_name}`."
+        )
+
+
 class HEBOSampler(optunahub.samplers.SimpleBaseSampler):
     """A sampler using `HEBO <https://github.com/huawei-noah/HEBO/tree/master/HEBO>__` as the backend.
 
@@ -134,6 +155,7 @@ def _transform_to_dict_and_observe(
                 and not dist.log
                 and dist.step is not None
             ):
+                _validate_distributions(name, dist, trials)
                 params[name] = np.round((params[name] - dist.low) / dist.step).astype(int)
 
         hebo.observe(params, nan_padded_values)
@@ -161,7 +183,6 @@ def _sample_relative_stateless(
             return {}
 
         trials = [t for t in trials if set(search_space.keys()) <= set(t.params.keys())]
-
         seed = int(self._rng.integers(low=1, high=(1 << 31)))
         hebo = HEBO(self._convert_to_hebo_design_space(search_space), scramble_seed=seed)
         self._transform_to_dict_and_observe(hebo, search_space, study, trials)