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- Tensors and Dynamic neural networks in Python with strong GPU acceleration
- Datasets, Transforms and Models specific to Computer Vision
- Model interpretability and understanding for PyTorch
- Training PyTorch models with differential privacy
- On-device AI across mobile, embedded and edge for PyTorch
- FB (Facebook) + GEMM (General Matrix-Matrix Multiplication) - https://code.fb.com/ml-applications/fbgemm/
test-infra
Public- PyTorch native quantization and sparsity for training and inference
data
Public- Pytorch domain library for recommendation systems
- A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.
builder
Publictensordict
Publictext
PublicModels, data loaders and abstractions for language processing, powered by PyTorchignite
PublicHigh-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.