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PyTorch Governance | Maintainers

Responsibilities

  • Triage and fix high priority issues assigned to the module or library

  • Triage, review, and land high priority pull requests assigned to the module or library

  • Answer module or library questions on discuss.pytorch.org and dev-discuss.pytorch.org

  • Maintain public user and development documentation

  • Run meetings and share minutes plus roadmap on a half or quarterly basis

Lead Core Maintainer (BDFL)

Core Maintainers

Module-level maintainers

NN APIs (torch.nn)

Optimizers (torch.optim)

Autograd (torch.autograd)

Compilers (JIT / TorchScript / FX / TorchDynamo)

Distributions & RNG

Distributed

Multiprocessing and DataLoaders

Linear Algebra (torch.linalg)

Sparse (torch.sparse)

NestedTensor (torch.nested)

MaskedTensor (torch.masked)

Fast Fourier Transform (torch.fft)

CPU Performance (Torch Inductor / MKLDNN)

GPU Performance (Torch Inductor / Triton / CUDA)

NVFuser

AMD/ROCm/HIP

Build + CI

Performance Tools

C++ API

C10 utils and operator dispatch

ONNX exporter

Mobile / Edge

Model Compression & Optimization

Windows

Apple M1/MPS

PowerPC

AArch64 CPU

Docs / Tutorials

Library-level maintainers

XLA

TorchServe

TorchVision

TorchText

TorchAudio

TorchRec

TorchX

TorchData / TorchArrow

Docs

Access comprehensive developer documentation for PyTorch

View Docs

Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

Resources

Find development resources and get your questions answered

View Resources