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- On-device AI across mobile, embedded and edge for PyTorch
- Tensors and Dynamic neural networks in Python with strong GPU acceleration
- PyTorch native quantization and sparsity for training and inference
- Pytorch domain library for recommendation systems
- FB (Facebook) + GEMM (General Matrix-Matrix Multiplication) - https://code.fb.com/ml-applications/fbgemm/
- Datasets, Transforms and Models specific to Computer Vision
- Models, data loaders and abstractions for language processing, powered by PyTorch
- CPU INFOrmation library (x86/x86-64/ARM/ARM64, Linux/Windows/Android/macOS/iOS)
- A lightweight library for PyTorch training tools and utilities
- High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
- Model interpretability and understanding for PyTorch
- TorchX is a universal job launcher for PyTorch applications. TorchX is designed to have fast iteration time for training/research and support for E2E production ML pipelines when you're ready.
- A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.