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MegEngine

Documentation | 中文文档

MegEngine is a fast, scalable, and user friendly deep learning framework with 3 key features.

  • Unified framework for both training and inference
    • Quantization, dynamic shape/image pre-processing, and even derivation with a single model.
    • After training, put everything into your model to inference on any platform with speed and precision. Check here for a quick guide.
  • The lowest hardware requirements
    • The memory usage of the GPU can be reduced to one-third of the original memory usage when DTR algorithm is enabled.
    • Inference models with the lowest memory usage by leveraging our Pushdown memory planner.
  • Inference efficiently on all platforms
    • Inference with speed and high-precision on x86, Arm, CUDA, and RoCM.
    • Supports Linux, Windows, iOS, Android, TEE, etc.
    • Optimize performance and memory usage by leveraging our advanced features.

Installation

NOTE: MegEngine now supports Python installation on Linux-64bit/Windows-64bit/MacOS(CPU-Only)-10.14+/Android 7+(CPU-Only) platforms with Python from 3.5 to 3.8. On Windows 10 you can either install the Linux distribution through Windows Subsystem for Linux (WSL) or install the Windows distribution directly. Many other platforms are supported for inference.

Binaries

To install the pre-built binaries via pip wheels:

python3 -m pip install --upgrade pip
python3 -m pip install megengine -f https://megengine.org.cn/whl/mge.html

Building from Source

How to Contribute

We strive to build an open and friendly community. We aim to power humanity with AI.

How to Contact Us

Resources

License

MegEngine is licensed under the Apache License, Version 2.0

Citation

If you use MegEngine in your publication,please cite it by using the following BibTeX entry.

@Misc{MegEngine,
  institution = {megvii},
  title =  {MegEngine:A fast, scalable and easy-to-use deep learning framework},
  howpublished = {\url{https://github.com/MegEngine/MegEngine}},
  year = {2020}
}

Copyright (c) 2014-2021 Megvii Inc. All rights reserved.