https://github.com/MarioSieg/magnetron
(WIP) A small but powerful, homemade PyTorch from scratch.
https://github.com/MarioSieg/magnetron
artificial-intelligence cpp cuda high-performance-computing machine-learning neuronal-network python pytorch research-project tensorflow tiny
Last synced: 2 months ago
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(WIP) A small but powerful, homemade PyTorch from scratch.
- Host: GitHub
- URL: https://github.com/MarioSieg/magnetron
- Owner: MarioSieg
- License: other
- Created: 2025-01-02T21:25:56.000Z (11 months ago)
- Default Branch: master
- Last Pushed: 2025-09-09T09:29:07.000Z (2 months ago)
- Last Synced: 2025-09-09T12:43:49.734Z (2 months ago)
- Topics: artificial-intelligence, cpp, cuda, high-performance-computing, machine-learning, neuronal-network, python, pytorch, research-project, tensorflow, tiny
- Language: C
- Homepage:
- Size: 26.6 MB
- Stars: 638
- Watchers: 8
- Forks: 30
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
- awesome-cuda-and-hpc - MarioSieg/magnetron
README
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magnetron
Super minimalistic machine-learning framework.
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## 📖 About
Magnetron is a minimalistic, PyTorch-inspired machine-learning framework designed for IoT and other resource-limited environments.
The tiny C core - wrapped in a modern Python API - gives you dynamic graphs, automatic differentiation and network building blocks without the bloat.
A CUDA backend is also WIP.
### Key features
* **PyTorch-close** Python API
- Seamless switch for PyTorch users with familiar syntax and behavior
* **Automatic differentiation** on dynamic computation graphs
- Supports flexible model construction and training workflows
* High-level **neural-net building blocks**
- Includes `nn.Module`, `Linear`, `Sequential`, and more out of the box
* **Highly optimized CPU kernels**
- Runtime CPU detection, multithreading, and SIMD acceleration (SSE, AVX2, AVX512, NEON)
* Multiple **datatypes**: **float32**, **float16**, **int32**, and **boolean**
- Flexibility for both training and quantized inference
* Custom **compressed tensor file formats**
- Fast serialization & model loading
* Clear **validation** and **error messages**
- Easier debugging and better developer experience
* No external **C or Python dependencies** (except **CFFI** for the Python wrapper)
- Lightweight and portable - great for embedded or restricted environments
## 📦 Installation
Make sure you are inside a **Python virtual environment** before installing.
**With pip**
```bash
pip install magnetron
```
**With uv**
```bash
uv pip install magnetron
```
> ⚠️ Currently, prebuilt wheels are available for **macOS (Apple Silicon)** and **Linux x86-64**.
> On other platforms, the package must be built from source.
## 🧪 Examples
### GPT-2 inference
### Training a simple feedforward network
## 🤝 Contributing
Contributions are welcome!
Please open issues for ideas, or submit pull requests for new **features**.
PRs that only fix typos or minor formatting will not be accepted.
## 📜 License
(c) 2025 Mario Sieg. mario.sieg.64@gmail.com
Distributed under the Apache 2 License.
See `LICENSE` for more information.
## 🧩 Similar Projects
* [GGML](https://github.com/ggerganov/ggml)
* [TINYGRAD](https://github.com/tinygrad/tinygrad)
* [MICROGRAD](https://github.com/karpathy/micrograd)
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[license-url]: https://github.com/MarioSieg/magnetron/blob/master/LICENSE.txt
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