Fix pylint. (dmlc#10296)

Author: trivialfis

python-package/xgboost/spark/core.py

@@ -527,7 +527,8 @@ def _validate_and_convert_feature_col_as_array_col(
             (DoubleType, FloatType, LongType, IntegerType, ShortType),
         ):
             raise ValueError(
-                "If feature column is array type, its elements must be number type."
+                "If feature column is array type, its elements must be number type, "
+                f"got {features_col_datatype.elementType}."
             )
         features_array_col = features_col.cast(ArrayType(FloatType())).alias(alias.data)
     elif isinstance(features_col_datatype, VectorUDT):
@@ -1379,15 +1380,15 @@ def _transform(self, dataset: DataFrame) -> DataFrame:
         # to avoid the `self` object to be pickled to remote.
         xgb_sklearn_model = self._xgb_sklearn_model
 
-        has_base_margin = False
+        base_margin_col = None
         if (
             self.isDefined(self.base_margin_col)
             and self.getOrDefault(self.base_margin_col) != ""
         ):
-            has_base_margin = True
             base_margin_col = col(self.getOrDefault(self.base_margin_col)).alias(
                 alias.margin
             )
+        has_base_margin = base_margin_col is not None
 
         features_col, feature_col_names = self._get_feature_col(dataset)
         enable_sparse_data_optim = self.getOrDefault(self.enable_sparse_data_optim)
@@ -1472,6 +1473,7 @@ def to_gpu_if_possible(data: ArrayLike) -> ArrayLike:
                 yield predict_func(model, X, base_margin)
 
         if has_base_margin:
+            assert base_margin_col is not None
             pred_col = predict_udf(struct(*features_col, base_margin_col))
         else:
             pred_col = predict_udf(struct(*features_col))