diff --git a/docs/examples/plot_cast_transformer.py b/docs/examples/plot_cast_transformer.py
index 34efc74f8..82cfef35e 100644
--- a/docs/examples/plot_cast_transformer.py
+++ b/docs/examples/plot_cast_transformer.py
@@ -30,7 +30,6 @@
 """
 import onnxruntime
 import onnx
-import numpy
 import os
 import math
 import numpy as np
diff --git a/docs/examples/plot_tfidfvectorizer.py b/docs/examples/plot_tfidfvectorizer.py
index 96321bfbf..290eb5e36 100644
--- a/docs/examples/plot_tfidfvectorizer.py
+++ b/docs/examples/plot_tfidfvectorizer.py
@@ -24,7 +24,6 @@
 import matplotlib.pyplot as plt
 import os
 from onnx.tools.net_drawer import GetPydotGraph, GetOpNodeProducer
-import numpy
 import onnxruntime as rt
 from skl2onnx.common.data_types import StringTensorType
 from skl2onnx import convert_sklearn
diff --git a/tests/test_sklearn_classifiers_extreme.py b/tests/test_sklearn_classifiers_extreme.py
index 8996aeaf9..d26ca31a5 100644
--- a/tests/test_sklearn_classifiers_extreme.py
+++ b/tests/test_sklearn_classifiers_extreme.py
@@ -2,7 +2,11 @@
 
 import unittest
 import numpy as np
-from onnx.reference import ReferenceEvaluator
+
+try:
+    from onnx.reference import ReferenceEvaluator
+except ImportError:
+    ReferenceEvaluator = None
 from sklearn.tree import DecisionTreeClassifier
 from onnxruntime import InferenceSession
 from skl2onnx import to_onnx
@@ -21,11 +25,15 @@ def test_one_training_class(self):
         onx = to_onnx(cl, x, target_opset=TARGET_OPSET, options={"zipmap": False})
 
         for cls in [
-            lambda onx: ReferenceEvaluator(onx, verbose=0),
+            (lambda onx: ReferenceEvaluator(onx, verbose=0))
+            if ReferenceEvaluator is not None
+            else None,
             lambda onx: InferenceSession(
                 onx.SerializeToString(), providers=["CPUExecutionProvider"]
             ),
         ]:
+            if cls is None:
+                continue
             sess = cls(onx)
             res = sess.run(None, {"X": x})
             self.assertEqual(len(res), len(expected))