[P] JAXnet (preview) – An alternative to TensorFlow2/Keras/PyTorch for more concise, robust and optimized deep learning code
JAXnet is a deep learning library based on Google’s JAX. JAXnet’s functional API provides unique benefits over TensorFlow2, Keras and PyTorch, while maintaining user-friendliness, modularity and scalability:
- More robustness through immutable weights, no global compute graph.
- GPU-compiled numpy code for networks, training loops, pre- and postprocessing.
- Regularization and reparametrization of any module or whole networks in one line.
- No global random state, flexible random key control.
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