def test_multiple_transform(self):
x = pandas.DataFrame(data=[[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]])
x.columns = "X1 X2".split()
content = self.get_onnx_mul()
res = list(OnnxTransformer.enumerate_create(content))
self.assertNotEmpty(res)
for _, tr in res:
tr.fit()
self.assertRaise(lambda tr=tr: tr.transform(x), RuntimeError)
def test_pipeline_iris(self):
iris = load_iris()
X, y = iris.data, iris.target
pipe = make_pipeline(PCA(n_components=2), LogisticRegression())
pipe.fit(X, y)
onx = convert_sklearn(pipe, initial_types=[
('input', FloatTensorType((None, X.shape[1])))])
onx_bytes = onx.SerializeToString()
res = list(OnnxTransformer.enumerate_create(onx_bytes))
outputs = []
shapes = []
for k, tr in res:
outputs.append(k)
tr.fit()
y = tr.transform(X)
self.assertEqual(y.shape[0], X.shape[0])
shapes.append(y.shape)
self.assertEqual(len(set(outputs)), len(outputs))
shapes = set(shapes)
self.assertEqual(shapes, {(150, 3), (150, 4), (150, 2), (150,)})
