Those new features include top-level support for TorchDynamo, AOTAutograd, PrimTorch, and TorchInductor. If you ask yourself, why is there a new major version and no breaking changes? The PyTorch team answered this question in their FAQ: “We were releasing substantial new features that we believe change how you meaningfully use PyTorch, so we are calling it 2.0 instead.” Pytorch 2.0 will not require any modification to existing PyTorch code but can optimize your code by adding a single line of code with model = pile(model). PyTorch 2.0 or, better, 1.14 is entirely backward compatible.
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