About PyTorch 2.0
PyTorch is an open-source machine learning framework that accelerates the transition from research prototyping to production deployment. The next-generation release, PyTorch 2.0, is described as being faster, more Pythonic, and more dynamic than ever.
Features of PyTorch 2.0
- Production Ready: PyTorch 2.0 offers a seamless transition between eager and graph modes with TorchScript. It also accelerates the path to production with TorchServe.
- Distributed Training: The framework supports scalable distributed training and performance optimization in both research and production through the
- Robust Ecosystem: PyTorch 2.0 boasts a rich ecosystem of tools and libraries that extend its capabilities. These tools support development in various domains, including computer vision and natural language processing (NLP).
- Cloud Support: PyTorch is well-supported on major cloud platforms, ensuring frictionless development and easy scaling.
- Ecosystem of Libraries and Tools: PyTorch’s ecosystem includes a variety of libraries and tools that support development. For instance, Captum is an open-source library built on PyTorch for model interpretability. PyTorch Geometric is designed for deep learning on irregular input data such as graphs, point clouds, and manifolds. Additionally, skorch provides high-level integration with PyTorch and ensures full scikit-learn compatibility.
- Community and Governance: PyTorch has a vibrant developer community where individuals can contribute, learn, and get their questions answered. The community also offers resources in multiple languages, including Chinese, Korean, and Japanese. The governance structure and design principles of PyTorch are transparent and accessible to all contributors and maintainers.