Target predictions in the browser with RDKit MinimalLib (JS) and ONNX.js

Three Dowsing Questions Answered | Center for Inquiry

Some time ago we showed an example of how a model trained in Python's PyTorch could be run in a C++ backend by exporting it to the ONNX format.

Greg also showed us in his blogpost how our multitask neural network model could be used in a very nice KNIME workflow by exporting it to ONNX. That was possible thanks to RDKit's Java bindings and the ONNX Java runtime.

As a refresher, most of the most popular machine learning frameworks can export their models to this format and many programming languages can load them to run the predictions. This certainly is a beautiful example of interoperability!

In November 2019 RDKit introduced a reduced functionality Javascript library which is able to do all we need in order to use our multitask model in the browser. So, the only thing that was left to do was to combine these two awesome tools... and we did it!

Here is our demo with its available source code. Start typing a smiles into the box and enjoy!

Updated code to generate the model is also available here. This updated code takes advantage of the PyTorch Lightning library.

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