[v632][Python] Adapt TMVA Pythonizations to XGBoost 3.1.0 JSON format

bindings/pyroot/pythonizations/python/ROOT/_pythonization/_tmva/_tree_inference.py

@@ -20,12 +20,23 @@ def get_basescore(model):
     Copy-pasted from XGBoost unit test code.
 
     See also:
-      * https://github.com/dmlc/xgboost/blob/a99bb38bd2762e35e6a1673a0c11e09eddd8e723/python-package/xgboost/testing/updater.py#L13
+      * https://github.com/dmlc/xgboost/blob/2463938/python-package/xgboost/testing/updater.py#L43
       * https://github.com/dmlc/xgboost/issues/9347
       * https://discuss.xgboost.ai/t/how-to-get-base-score-from-trained-booster/3192
     """
-    base_score = float(json.loads(model.get_booster().save_config())["learner"]["learner_model_param"]["base_score"])
-    return base_score
+    jintercept = json.loads(model.get_booster().save_config())["learner"]["learner_model_param"]["base_score"]
+    out = json.loads(jintercept)
+    if isinstance(out, float):
+        return out
+    # For XGBoost 3.1.0 and after, the value is itself a list.
+    # However, we don't support multiple base scores yet.
+    if len(out) > 1:
+        raise ValueError(
+            f"Model contains multiple base scores ({out}). "
+            "This typically occurs with XGBoost ≥ 3.1.0, which supports multi-target base scores. "
+            "This function only supports a single base score. "
+        )
+    return out[0]
 
 
 def SaveXGBoost(xgb_model, key_name, output_path, num_inputs):

tmva/tmva/test/rbdt_xgboost.py

@@ -82,6 +82,8 @@ def test_XGBMulticlass_default(self):
         """
         Test model trained with multiclass XGBClassifier.
         """
+        if xgboost.__version__ >= "3.1.0":
+            self.skipTest("We don't support multiclassification with xgboost>=3.1.0 yet")
         _test_XGBMulticlass("default")
 
     def test_XGBRegression_default(self):