sync Mar 27 2023

demo/guide-python/multioutput_regression.py

@@ -46,7 +46,7 @@ def gen_circle() -> Tuple[np.ndarray, np.ndarray]:
     return X, y
 
 
-def rmse_model(plot_result: bool, strategy: str):
+def rmse_model(plot_result: bool, strategy: str) -> None:
     """Draw a circle with 2-dim coordinate as target variables."""
     X, y = gen_circle()
     # Train a regressor on it
@@ -120,10 +120,10 @@ if __name__ == "__main__":
     parser = argparse.ArgumentParser()
     parser.add_argument("--plot", choices=[0, 1], type=int, default=1)
     args = parser.parse_args()
+
     # Train with builtin RMSE objective
     # - One model per output.
     rmse_model(args.plot == 1, "one_output_per_tree")
-
     # - One model for all outputs, this is still working in progress, many features are
     # missing.
     rmse_model(args.plot == 1, "multi_output_tree")

demo/json-model/json_parser.py

@@ -162,9 +162,6 @@ class Model:
 
         # Load the trees
         self.num_trees = int(model_shape["num_trees"])
-        self.leaf_size = int(model_shape["size_leaf_vector"])
-        # Right now XGBoost doesn't support vector leaf yet
-        assert self.leaf_size == 0, str(self.leaf_size)
 
         trees: List[Tree] = []
         for i in range(self.num_trees):