Fixed Adaboost converter's incorrect results with non-default LR

skl2onnx/operator_converters/ada_boost.py

@@ -160,7 +160,7 @@ def convert_sklearn_ada_boost_classifier(scope, operator, container):
             attrs['classlabels_strings'] = classes
 
         add_tree_to_attribute_pairs(attrs, True, op.estimators_[tree_id].tree_,
-                                    0, op.learning_rate, 0, True)
+                                    0, 1, 0, True)
         container.add_node(
             op_type, operator.input_full_names,
             [label_name, proba_name],
@@ -234,7 +234,7 @@ def _get_estimators_label(scope, operator, container, model):
         attrs['n_targets'] = int(model.estimators_[tree_id].n_outputs_)
         add_tree_to_attribute_pairs(attrs, False,
                                     model.estimators_[tree_id].tree_,
-                                    0, model.learning_rate, 0, False)
+                                    0, 1, 0, False)
 
         container.add_node(op_type, input_name,
                            estimator_label_name, op_domain='ai.onnx.ml',

tests/test_sklearn_adaboost_converter.py

@@ -69,6 +69,34 @@ def test_ada_boost_classifier_samme(self):
             "<= StrictVersion('0.2.1')",
         )
 
+    @unittest.skipIf(not onnx_built_with_ml(),
+                     reason="Requires ONNX-ML extension.")
+    def test_ada_boost_classifier_lr(self):
+        data = load_digits()
+        X, y = data.data, data.target
+        X = X.astype('int64')
+        X_train, X_test, y_train, y_test = train_test_split(X,
+                                                            y,
+                                                            test_size=0.2,
+                                                            random_state=42)
+        model = AdaBoostClassifier(learning_rate=0.3, random_state=42)
+        model.fit(X_train, y_train)
+        model_onnx = convert_sklearn(
+            model,
+            "AdaBoost classification",
+            [("input", Int64TensorType(X_test.shape))],
+        )
+        self.assertIsNotNone(model_onnx)
+        dump_data_and_model(
+            X_test,
+            model,
+            model_onnx,
+            basename="SklearnAdaBoostClassifierLR",
+            allow_failure="StrictVersion("
+            "onnxruntime.__version__)"
+            "<= StrictVersion('0.2.1')",
+        )
+
     def test_ada_boost_regressor(self):
         model, X = fit_regression_model(
             AdaBoostRegressor(n_estimators=5))
@@ -107,6 +135,25 @@ def test_ada_boost_regressor_int(self):
             "== StrictVersion('1.4.1')",
         )
 
+    def test_ada_boost_regressor_lr(self):
+        model, X = fit_regression_model(
+            AdaBoostRegressor(learning_rate=0.5, random_state=42))
+        model_onnx = convert_sklearn(
+            model, "AdaBoost regression",
+            [("input", FloatTensorType([1, X.shape[1]]))])
+        self.assertIsNotNone(model_onnx)
+        dump_data_and_model(
+            X,
+            model,
+            model_onnx,
+            basename="SklearnAdaBoostRegressorLR-OneOffArray-Dec4",
+            allow_failure="StrictVersion("
+            "onnxruntime.__version__) "
+            "<= StrictVersion('0.2.1') or "
+            "StrictVersion(onnx.__version__) "
+            "== StrictVersion('1.4.1')",
+        )
+
 
 if __name__ == "__main__":
     unittest.main()