From 4b82a43ff23fb4b6c4bf00d5616e44c0267f4708 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?xavier=20dupr=C3=A9?= <xavier.dupre@gmail.com>
Date: Sat, 7 Nov 2020 12:36:36 +0100
Subject: [PATCH] Fixes #183, fix missing parameter black_op in OnnxPipeline

---
 _unittests/ut_sklapi/test_onnx_pipeline.py | 9 +++++++++
 mlprodict/sklapi/onnx_pipeline.py          | 6 ++++--
 2 files changed, 13 insertions(+), 2 deletions(-)

diff --git a/_unittests/ut_sklapi/test_onnx_pipeline.py b/_unittests/ut_sklapi/test_onnx_pipeline.py
index a4e688b02..a7256853c 100644
--- a/_unittests/ut_sklapi/test_onnx_pipeline.py
+++ b/_unittests/ut_sklapi/test_onnx_pipeline.py
@@ -10,6 +10,7 @@
 from sklearn.datasets import load_iris
 from sklearn.linear_model import LogisticRegression
 from sklearn.mixture import GaussianMixture
+from sklearn.tree import DecisionTreeRegressor
 from pyquickhelper.pycode import ExtTestCase, ignore_warnings
 from mlinsights.mlmodel import TransferTransformer
 from mlprodict.onnx_conv import to_onnx
@@ -46,6 +47,13 @@ def test_pipeline_iris(self):
         self.assertEqualArray(res["label"], pipe.predict(X))
         self.assertEqualArray(res["probabilities"], pipe.predict_proba(X))
 
+    def test_pipeline_none_params(self):
+        model_onx = OnnxPipeline([
+            ('scaler', StandardScaler()),
+            ('dt', DecisionTreeRegressor(max_depth=2))
+        ])
+        self.assertNotEmpty(model_onx)
+
     def test_pipeline_iris_enfore_false(self):
         iris = load_iris()
         X, y = iris.data, iris.target
@@ -235,4 +243,5 @@ def cache(self, obj):
 
 
 if __name__ == '__main__':
+    TestOnnxPipeline().test_pipeline_none_params()
     unittest.main()
diff --git a/mlprodict/sklapi/onnx_pipeline.py b/mlprodict/sklapi/onnx_pipeline.py
index 5ddcb9248..92be41d6a 100644
--- a/mlprodict/sklapi/onnx_pipeline.py
+++ b/mlprodict/sklapi/onnx_pipeline.py
@@ -66,8 +66,6 @@ def __init__(self, steps, *, memory=None, verbose=False,
                  runtime='python', options=None,
                  white_op=None, black_op=None, final_types=None,
                  op_version=None):
-        Pipeline.__init__(
-            self, steps, memory=memory, verbose=verbose)
         self.output_name = output_name
         self.enforce_float32 = enforce_float32
         self.runtime = runtime
@@ -77,6 +75,10 @@ def __init__(self, steps, *, memory=None, verbose=False,
         self.black_op = black_op
         self.final_types = final_types
         self.op_version = op_version
+        # The constructor calls _validate_step and it checks the value
+        # of black_op.
+        Pipeline.__init__(
+            self, steps, memory=memory, verbose=verbose)
 
     def fit(self, X, y=None, **fit_params):
         """