def test_extratreesclassifier_decision_path(self):
model = ExtraTreesClassifier(max_depth=2, n_estimators=3)
X, y = make_classification(10, n_features=4, random_state=42)
X = X[:, :2]
model.fit(X, y)
initial_types = [('input', FloatTensorType((None, X.shape[1])))]
model_onnx = convert_sklearn(
model, initial_types=initial_types,
options={id(model): {'decision_path': True, 'zipmap': False}},
target_opset=TARGET_OPSET)
sess = InferenceSession(model_onnx.SerializeToString())
res = sess.run(None, {'input': X.astype(numpy.float32)})
pred = model.predict(X)
assert_almost_equal(pred, res[0].ravel())
prob = model.predict_proba(X)
assert_almost_equal(prob, res[1])
dec = model.decision_path(X)
exp = binary_array_to_string(dec[0].todense())
got = numpy.array([''.join(row) for row in res[2]])
assert exp == got.ravel().tolist()
