Notice: Menoh is no longer maintained. Part of its functionality is inherited by chainer-compiler.
Menoh is DNN inference library with C API.
Menoh is released under MIT License.
DISCLAIMER: Menoh is still experimental. Use it at your own risk. In particular not all operators in ONNX are supported, so please check whether the operators used in your model are supported. We have checked that VGG16 and ResNet50 models converted by onnx-chainer work fine.
This codebase contains C API and C++ API.
- DNN Inference with CPU
- ONNX support
- Easy to use.
- Chainer model to ONNX : onnx-chainer
- C# wrapper : menoh-sharp
- Go wrapper : go-menoh
- (unofficial wrapper gomenoh by kou-m san has been merged)
- Haskell wrapper : menoh-haskell
- Node.js wrapper : node-menoh
- Ruby wrapper : menoh-ruby
- Rust wrapper : menoh-rs
- There is also unofficial Rust wrapper by Y-Nak san
- Java wrapper : menoh-java
- [Unofficial] ROS interface by Akio Ochiai san : menoh_ros
- [Unofficial] OCaml wrapper by wkwkes san : Menohcaml
Installation using package manager or binary packages
- For Windows users, prebuild libraries are available (see release) and Nuget package is available.
- For macOS user, Homebrew tap repository is available.
- For Ubuntu user, binary packages are available.
If you are using Ubuntu 18.04, please replace
$ curl -LO https://github.com/pfnet-research/menoh/releases/download/v1.1.1/ubuntu1604_mkl-dnn_0.16-1_amd64.deb $ curl -LO https://github.com/pfnet-research/menoh/releases/download/v1.1.1/ubuntu1604_menoh_1.1.1-1_amd64.deb $ curl -LO https://github.com/pfnet-research/menoh/releases/download/v1.1.1/ubuntu1604_menoh-dev_1.1.1-1_amd64.deb $ sudo apt install ./ubuntu1604_*_amd64.deb
Installation from source
- MKL-DNN Library (0.14 or later)
- Protocol Buffers (2.6.1 or later)
Execute following commands in root directory.
python scripts/retrieve_data.py mkdir build && cd build cmake .. make
See BUILDING.md for details.
Execute following command in build directory created at Build section.
Run VGG16 example (it can run ResNet-50 as well)
Execute following command in root directory.
Result is here
vgg16 example -18.1883 -26.5022 -20.0474 13.5325 -0.107129 0.76102 -23.9688 -24.218 -21.6314 14.2164 top 5 categories are 8 0.885836 n01514859 hen 7 0.104591 n01514668 cock 86 0.00313584 n01807496 partridge 82 0.000934658 n01797886 ruffed grouse, partridge, Bonasa umbellus 97 0.000839487 n01847000 drake
You can also run ResNet-50
./example/vgg16_example_in_cpp -m ../data/resnet50.onnx
--help option for details
Then, execute following commands in root directory.
python scripts/gen_test_data.py cd build cmake -DENABLE_TEST=ON .. make ./test/menoh_test.out
Current supported operators
Neural network connections
Menoh is released under MIT License. Please see the LICENSE file for details.
Pre-trained models downloaded via
retrieve_data.py were converted by onnx-chainer. The original models were downloaded via ChainerCV.