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live
PyTorch Live is an easy to use library of tools for creating on-device ML demos on Android and iOS. With Live, you can build a working mobile ML prototype in minutes. (by pytorch)
I'd say stick with PT for now! If you're interested in deployment, might wanna look into TF, but I'd use PyTorch Live to build a mobile application before you do that!
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From other comments, a lot of JavaScript developers who want to use TensorFlow had never heard of TensorFlow.js or ml5.js!
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SonarLint
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If you're interested in function transformations in PyTorch, try out functorch :) https://github.com/pytorch/functorch
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I just started using equinox for neural networks in jax. It's really simple. I'd highly recommend you take a look!
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pytorch-lightning
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.
Is the problem the sheer number of options, or the fact that they are all together in one place? Would it be better if they were organized into the different trainer entrypoints (fit, validate, ...)? If that is the case, there was an RFC proposing this which you might find interesting, feel free to drop by and comment on the issue: https://github.com/PyTorchLightning/pytorch-lightning/issues/10444