case when all nans in test

Author: ravinkohli

autoPyTorch/data/tabular_feature_validator.py

@@ -521,7 +521,7 @@ def _is_datasets_consistent(self, diff_cols: List[Union[int, str]], X: pd.DataFr
             if len(diff_cols) == 0:
                 return True
             else:
-                return False
+                return all(X[diff_cols].isna().all())
 
         # dtype is different ==> the column in at least either of train or test datasets must be all NaN
         # inconsistent <==> dtype is different and the col in both train and test is not all NaN