In a blog post by Team PyTorch, the announcement of the release of PyTorch 2.0, the popular open-source machine learning framework, has been made official. As you can imagine, the release has been eagerly anticipated by the data science community, and from the looks of it, the team did not disappoint. According to the post, PyTorch 2.0 brings a host of new features and improvements to the platform, making it even more powerful and versatile than before.
The latest release comes packed with exciting new features. Notably, Accelerated Transformers, which was previously referred to as Better Transformers, is now available in a stable version. Additionally, the beta version includes a host of improvements such as torch.compile serving as the primary API for PyTorch 2.0, the inclusion of the scaled_dot_product_attention function in the torch.nn.functional module, the MPS backend, and functorch APIs in the torch.func module.
Furthermore, there are several other beta and prototype enhancements aimed at optimizing inferences, performance, and training on both GPUs and CPUs. Speaking of which, another major improvement in PyTorch 2.0 is the addition of distributed training capabilities. With this new feature, users can train large-scale machine learning models across multiple GPUs or even multiple machines. This can dramatically reduce training time and enable users to work with much larger datasets than before.
PyTorch 2.0 also includes a number of smaller improvements and bug fixes, including better support for Windows and improved performance on GPUs. In addition, the PyTorch community has created a number of new libraries and tools to help users get the most out of the platform, including the PyTorch Lightning library for easier model training and the PyTorch Hub for sharing pre-trained models.
The release of PyTorch 2.0 is a major step forward for the popular open-source machine learning framework, and it has the potential to greatly improve the productivity and effectiveness of data scientists and machine learning professionals. With its new features and improvements, PyTorch 2.0 is poised to continue its rapid growth and become an even more widely adopted machine learning framework in the years to come.