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You should give JAX a go.

+1 for JAX. Basically designed to be the successor to TensorFlow, and much nicer to work with. Strangely I've not seen it discussed around HN much but it's what I do 100% of my work in these days.

Whilst I'm here: shameless self-promotion for Equinox and Diffrax:

https://github.com/patrick-kidger/equinox https://github.com/patrick-kidger/diffrax

Which are neural network and differential equation libraries for JAX.

[Obligatory I-am-a-googler-my-opinions-do-not-represent-your-employer...]

I feel like JAX usually comes up on PyTorch posts (in the same way PyTorch usually comes up in the comments on TF posts).

I think the delta between JAX and PT on commodity hardware is just a little bit too small to really create much splash on HN.

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