MyCaffe is a complete C# re-write of the native C++ CAFFE[1] open source project.

MyCaffe allows Windows C# software developers to use and expand deep learning solutions in their native C# language. All layers except for a few, and nearly every unit test are now provided in C#. Windows programmers can now write their own custom layers in the C# language, yet still enjoy the benefit of an efficient deep learning architecture that supports multi-GPU training on up to 8 headless GPU's using NCCL 1.4 ('Nickel').

Now you can create custom layers for MyCaffe in native C# using the full extent of the Windows .NET Framwork!

We have made a large effort to keep the MyCaffe C# code true to the original down to comment with the hope of making it even easier to extend the general CAFFE architecture for all. In addition, MyCaffe uses the same Proto Buffer file format for solver and model descriptions and model binary files allowing an easy exchange between the MyCaffe and C++ CAFFE platforms.

Most of the MyCaffe C# code is very similar to the C++ CAFFE code, for our goal is to extend the CAFFE platform to C# programmers, while maintaining compatibility with CAFFE's solver descriptions, model descriptions and binary weight format.

The C# based MyCaffe open-source project is independently maintained by SignalPop LLC and made available under the Apache 2.0 License.

NOTE: Visual Studio 2017 support noted above currently uses the Platform Toolset "Visual Studio 2015 (v140)" build setting.

IMPORTANT: The open-source MyCaffe project on GitHub is considered 'pre-release' and will have bugs. When you find bugs or other issues, please report them here - or better yet, get involved and propose a fix!

[1] Caffe: Convolutional Architecture for Fast Feature Embedding by Yangqing Jai, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, and Trevor Darrell, 2014.

For more information on the C++ CAFFE open-source project, please see the following link.