GoogleJAX是一个用于变换数值函数的机器学习框架，Google称其为为结合了修改版本的Autograd（通过函数微分自动获得梯度函数）和TensorFlow的XLA（加速线性代数）。该框架的设计尽可能遵循NumPy的结构和工作流程，并与TensorFlow和PyTorch等各种现有框架协同工作。
JAX的主要功能是包括：
- grad：自动微分
- jit：编译
- vmap：自动矢量化
- pmap：SPMD编程
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