Xavier Dupré

So you would like to get a way to get the returned values by method [inverse_transform](https://scikit-learn.org/stable/modules/generated/sklearn.pipeline.Pipeline.html#sklearn.pipeline.Pipeline.inverse_transform).

Could you sign off your commit? You can click on details button after dco to get the git instruction to do it.

Sparse tensors are not currently high priority for Onnxruntime. We could write the converters to create an ONNX graph using sparse vectors but it would be difficult to make sure...

Your model requires the inverse function to be converted into ONNX and that's not always possible. There are multiple options to do that, have the runtime run some python code,...

I create another approach. It is a [numpy API for ONNX](http://www.xavierdupre.fr/app/mlprodict/helpsphinx/blog/2021/2021-05-05_numpyapionnx1.html). If you write your function with this api, the conversion is free.

The following page indicates the list of supported models: https://onnx.ai/sklearn-onnx/supported.html. There is no converter for it right now. So if you implemented a new converter, you need to register it:...

A new project https://github.com/microsoft/onnx-script has started to help create onnx models. It might be easier to use. i did not write example with sklearn-onnx but it should be soon.

I need to know more about the model your need to convert. Your scenario is still the same as the one mentioned at the beginning of the issue? What about...

I see. I'll complete the example to make it work.

I guess that was not that obvious but if you install the latest version of mlprodict, you should be able to run the following example https://github.com/sdpython/mlprodict/blob/master/_doc/examples/plot_converters.py which covers your need.