Weng et al.) that is publicly availible on GitHub. For this example, I chose the ChexNet (the one from Rajpurkar et al.) and implementation by arroweng (i.e. In this article I’m going to go over an example of deploying a trained PyTorch model using GraphPipe and my own model agnostic (MA) library (which now includes support for GraphPipe). I’m still planning on taking a look at Kubeflow at some point as it has many nice features (like AB testing/multi-armed bandit updates to redirect traffic), but I found GraphPipe easier to use and at least according to its website it is much faster than JSON type APIs (like Kubeflow).
However, I got bogged down with a lot of work and in the interim a new model deployment framework emerged by Oracle called GraphPipe. I was originally planning to write the second article in my series on Kubeflow.
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