The tutorial goes from a simple example which converts a pipeline to a more complex example involving operator not actually implemented in ONNX operators or ONNX ML operators.

The tutorial was tested with following version:


import numpy
import scipy
import sklearn
import lightgbm
import onnx
import onnxmltools
import onnxruntime
import xgboost
import skl2onnx
import mlprodict
import pyquickhelper

mods = [numpy, scipy, sklearn, lightgbm, xgboost,
        onnx, onnxmltools, onnxruntime,
        skl2onnx, mlprodict, pyquickhelper]
mods = [(m.__name__, m.__version__) for m in mods]
mx = max(len(_[0]) for _ in mods) + 1
for name, vers in sorted(mods):
    print("%s%s%s" % (name, " " * (mx - len(name)), vers))


    lightgbm      3.2.1
    mlprodict     0.7.1631
    numpy         1.21.4
    onnx          1.10.1
    onnxmltools   1.10.0
    onnxruntime   1.10.0+cpu
    pyquickhelper 1.10.3660
    scipy         1.7.2
    skl2onnx      1.10.2
    sklearn       1.1.dev0
    xgboost       1.5.0