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Add multi_gpu_training_jax.ipynb for multi_gpu_training_torch.ipynb
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Description
Colab link
https://colab.research.google.com/drive/1fa05RZZnDW5KOlaFaZbgMSidYm0CXfC7?usp=sharing
Issue
probml/pyprobml#686
Checklist:
Potential problems/Important remarks
Since writing JAX requires a completely different mindset from that of PyTorch, translating the notebook work-by-word would inevitably lead to JAX code with a PyTorch "accent". To avoid that, I created an idiomatic JAX/Flax implementation of multi-device training from scratch. It borrows some code from the official Parallel Evaluation in JAX notebook (which trains a linear regression model), and follows roughly the same narration as the original D2L notebook.