def test_speedup_kmeans64_op_version(self):
data = load_iris()
X, y = data.data, data.target
spd = OnnxSpeedupCluster(KMeans(n_clusters=3),
target_opset=self.opset(),
enforce_float32=False)
spd.fit(X, y)
opset = spd.op_version
self.assertGreater(self.opset(), opset[''])
def test_speedup_kmeans32(self):
data = load_iris()
X, y = data.data, data.target
spd = OnnxSpeedupCluster(KMeans(n_clusters=3),
target_opset=self.opset())
spd.fit(X, y)
spd.assert_almost_equal(X, decimal=4)
def test_speedup_kmeans64(self):
data = load_iris()
X, y = data.data, data.target
spd = OnnxSpeedupCluster(KMeans(n_clusters=3),
target_opset=self.opset(),
enforce_float32=False)
spd.fit(X, y)
spd.assert_almost_equal(X)
def test_speedup_kmeans32_weight(self):
data = load_iris()
X, y = data.data, data.target
spd = OnnxSpeedupCluster(KMeans(n_clusters=3),
target_opset=self.opset())
w = numpy.ones(y.shape, dtype=X.dtype)
spd.fit(X, y, w)
spd.assert_almost_equal(X, decimal=4)
def test_speedup_kmeans32_numba(self):
data = load_iris()
X, y = data.data, data.target
X = X.astype(numpy.float32)
spd = OnnxSpeedupCluster(KMeans(n_clusters=3),
target_opset=self.opset(),
runtime="numba",
nopython=False)
spd.fit(X, y)
spd.assert_almost_equal(X, decimal=4)
self.assertIn("CPUDispatch", str(spd.onnxrt_.func))
def test_speedup_kmeans64_onnx(self):
data = load_iris()
X, y = data.data, data.target
spd = OnnxSpeedupCluster(KMeans(n_clusters=3),
target_opset=self.opset(),
enforce_float32=False)
spd.fit(X, y)
expected_label = spd.predict(X)
expected_score = spd.transform(X)
onx = to_onnx(spd, X[:1])
oinf = OnnxInference(onx)
got = oinf.run({'X': X})
self.assertEqualArray(expected_score, got['scores'])
self.assertEqualArray(expected_label, got['label'])
def test_speedup_kmeans64_pickle(self):
data = load_iris()
X, y = data.data, data.target
spd = OnnxSpeedupCluster(KMeans(n_clusters=3),
target_opset=self.opset(),
enforce_float32=False)
spd.fit(X, y)
st = BytesIO()
pickle.dump(spd, st)
st2 = BytesIO(st.getvalue())
spd2 = pickle.load(st2)
expected = spd.predict(X)
got = spd2.predict(X)
self.assertEqualArray(expected, got)
expected = spd.raw_predict(X)
got = spd2.raw_predict(X)
self.assertEqualArray(expected, got)