Tutorial#

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 catboost
import numpy
import scipy
import sklearn
import lightgbm
import onnx
import onnxmltools
import onnxruntime
import xgboost
import skl2onnx

mods = [
    numpy,
    scipy,
    sklearn,
    lightgbm,
    xgboost,
    catboost,
    onnx,
    onnxmltools,
    onnxruntime,
    skl2onnx,
]
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))

>>>

    <frozen importlib._bootstrap>:241: RuntimeWarning: numpy.ufunc size changed, may indicate binary incompatibility. Expected 216 from C header, got 232 from PyObject
    catboost    1.2.2
    lightgbm    4.2.0
    numpy       1.26.2
    onnx        1.16.0
    onnxmltools 1.13.0
    onnxruntime 1.17.0+cu118
    scipy       1.11.3
    skl2onnx    1.17.0
    sklearn     1.5.dev0
    xgboost     2.0.3