AlexHex7/Non-local_pytorch

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1564 stars · 269 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch implementation of the Non-local Neural Block from the paper 'Non-local Neural Networks', providing multiple variants (concatenation, gaussian, embedded gaussian, dot product). It includes demo training on MNIST and tools for visualizing non-local attention maps.

Use cases

• add non-local attention blocks to my pytorch model
• implement non-local neural networks in pytorch
• visualize non-local attention maps
• compare different non-local block variants
• train a network with non-local blocks on MNIST
• use mixed precision training with non-local blocks

When to choose

• you need a ready-made, well-starred PyTorch implementation of the Non-local Block
• you want to experiment with all four non-local block variants
• you want to visualize non-local attention maps for interpretability

When to avoid

• you need a maintained library with recent updates and broad model integrations
• you want attention modules beyond the non-local family (e.g., transformers, SE blocks)
• you need production training pipelines rather than demo code

Facets

library · maturity maintenance

machine-learning deep-learning image-processing computer-vision deep-learning computer-vision machine-learning python non-local-block pytorch attention neural-networks mnist mixed-precision visualization gpu

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