def test_algebra_normalizer(self):
op = OnnxNormalizer('I0', norm='L1', op_version=1)
onx = op.to_onnx({'I0': numpy.ones((1, 2), dtype=numpy.float32)})
assert onx is not None
sonx = str(onx)
assert "ai.onnx.ml" in sonx
assert "version: 1" in sonx
import onnxruntime as ort
sess = ort.InferenceSession(onx.SerializeToString())
X = numpy.array([[0, 2], [0, -2]])
exp = numpy.array([[0, 1], [0, -1]])
Y = sess.run(None, {'I0': X.astype(numpy.float32)})[0]
assert_almost_equal(exp, Y)
def test_algebra_normalizer_argmin(self):
op = OnnxArgMin(OnnxNormalizer('I0', norm='L1'))
onx = op.to_onnx({'I0': numpy.ones((1, 2), dtype=numpy.float32)})
assert onx is not None
sonx = str(onx)
assert len(sonx) > 0
import onnxruntime as ort
sess = ort.InferenceSession(onx.SerializeToString())
X = numpy.array([[0, 2], [0, -2]])
exp = numpy.array([[0, 1]])
Y = sess.run(None, {'I0': X.astype(numpy.float32)})[0]
assert_almost_equal(exp, Y)
