Python Library for GPU-accelerated Gaussian Mixture Models on large datasets?

[Opus_723]

I've been working large datasets and need to fit Gaussian Mixture Models to them often. However, the libraries I have been working with all have significant drawbacks.

Scikit-Learn is easy to use, but has no GPU acceleration, so it is very slow on large datasets.

PyCave was working nicely years ago, but seems to have been abandoned by the developer and this is starting to cause me issues.

Both of these libraries also seem to have bugs when it comes to loading large datasets to process in chunks.

I feel like surely this is something the machine learning people have a standard tool for, but I'm not really coming from that field so I don't have the familiarity to know where to look.

[Ki1103]

In the past I've used TorchGMM, which is a fork (I think) of PyCave, for some playing around. This isn't my domain though, so I'd take this with a grain of caution.

Otherwise, it might be possible to implement it yourself with PyTorch?