After installing PyTorch, a user will be able to import functorch and use functorch without needing to install another package. Previously, functorch was released out-of-tree in a separate package. Timely deprecating older CUDA versions allows us to proceed with introducing the latest CUDA version as they are introduced by Nvidia®, and hence allows support for C++17 in PyTorch and new NVIDIA Open GPU Kernel Modules. Additional improvements include accelerated add+matmul linear algebra kernels for sizes commonly used in Transformer models and Nested Tensors is now enabled by default. The BetterTransformer feature set supports fastpath execution for common Transformer models during Inference out-of-the-box, without the need to modify the model. We want to sincerely thank our dedicated community for your contributions. This release is composed of over 3,749 commits and 467 contributors since 1.12.1. Beta includes improved support for Apple M1 chips and functorch, a library that offers composable vmap (vectorization) and autodiff transforms, being included in-tree with the PyTorch release. We deprecated CUDA 10.2 and 11.3 and completed migration of CUDA 11.6 and 11.7. We are excited to announce the release of PyTorch ® 1.13 ( release note)! This includes Stable versions of BetterTransformer.
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