BobMcDear/attorch
A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.
This project offers a collection of neural network building blocks, like convolution layers and activation functions, that are designed to be easily customizable and highly efficient. It takes in raw data or intermediate feature maps and processes them through optimized network layers, outputting improved feature representations or predictions. This is for machine learning engineers and researchers who build and train deep learning models and need fine-grained control over performance.
597 stars. No commits in the last 6 months.
Use this if you are developing custom deep learning operations and want to create fast, specialized neural network components without writing complex CUDA code.
Not ideal if you primarily need off-the-shelf convolutional or pooling layers, as PyTorch's native implementations are generally faster for these specific operations.
Stars
597
Forks
32
Language
Python
License
MIT
Category
Last pushed
Aug 12, 2025
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