@PyTorch
PyTorch 2.12 introduces updates across compilation, distributed systems, export, graph capture, and accelerator support. Join Andrey Talman (@Meta), @albanDesmaison (@Meta), and @joespeez (@reflection_ai), moderated by @Chris_AI_HPC (@Meta), on May 20 at 10:00 AM PT for a live Q&A covering the release and answering questions from the community. Highlights include the new device-agnostic torch.accelerator.Graph API, up to 100x faster batched eigenvalue decomposition on CUDA, support for microscaling quantization formats in https://t.co/DQ6E1nOVvb, fused Adagrad optimizer support, FlightRecorder updates, multi-GPU and multi-node profiling improvements, updated backend selection for torch.linalg.eigh on CUDA, and expanded CUDA, ROCm, XPU, MPS, and Arm platform support. 🔗 Register today: https://t.co/LThdjj96F0 #PyTorch #OpenSourceAI