A simple C++ implementation of Neural Nets, inspired by the functionality of Tensorflow and pyTorch.
The documentation with this readme is available at Documentation
- like the functional API of tensorflow
- using eigen3 library
- more to come
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Modern CMake configuration and project, which, to the best of my knowledge, uses the best practices,
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An example of a Clang-Format config, inspired from the base Google model, with minor tweaks. This is aimed only as a starting point, as coding style is a subjective matter, everyone is free to either delete it (for the LLVM default) or supply their own alternative,
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Static analyzers integration, with Clang-Tidy and Cppcheck, the former being the default option,
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Doxygen support, through the
ENABLE_DOXYGENoption, which you can enable if you wish to use it, -
Unit testing support, through GoogleTest (with an option to enable GoogleMock) or Catch2,
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Code coverage, enabled by using the
ENABLE_CODE_COVERAGEoption, through Codecov CI integration, -
Package manager support, with Conan and Vcpkg, through their respective options
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CI workflows for Windows, Linux and MacOS using GitHub Actions, making use of the caching features, to ensure minimum run time,
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.md templates for: README, Contributing Guideliness, Issues and Pull Requests,
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Permissive license to allow you to integrate it as easily as possible. The template is licensed under the Unlicense,
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Options to build as a header-only library or executable, not just a static or shared library.
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Ccache integration, for speeding up rebuild times
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
This project is meant as a template and a good starting point for learning how create larger c++ projects, compile and run them. can be change to better suit the needs of the developer(s). If you wish to use the template as-is, meaning using the versions recommended here, then you will need:
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CMake v3.15+ - found at https://cmake.org/
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C++ Compiler - needs to support at least the C++17 standard, i.e. MSVC, GCC, Clang
Note: You also need to be able to provide CMake a supported generator.
- Different data - MNIST AND https://home.bawue.de/~horsch/teaching/inf205/src/image-benchmark.zip
There are few select extensions which are recommended
- https://marketplace.visualstudio.com/items?itemName=ms-vscode.cpptools-extension-pack
- https://marketplace.visualstudio.com/items?itemName=notskm.clang-tidy
- eigen3 : https://eigen.tuxfamily.org/index.php?title=Main_Page
- OpenMP : https://github.com/OpenMP
- OpenBLAS : https://github.com/xianyi/OpenBLAS
- csv-parser : https://github.com/vincentlaucsb/csv-parser
It is fairly easy to install the project, all you need to do is clone if from GitHub.
If you wish to clone the repository, you simply need to run:
git clone https://github.com/jkorsvik/NMBUFlowTorch/or
git clone git@github.com:jkorsvik/NMBUFlowTorch.gitInstall requirements (cmake, conan, etc..)
source install_reqs.shBuild and install project as an executable
source automatic_rebuild_and_install.shIf you just want to rebuild fast and you are happy with the install location, run:
source cached_build_and_install.shThe executables of the project will then be in the
To install an already built project, you need to run the install target with CMake.
For example:
cmake --build build --target install --config Release
# a more general syntax for that command is:
cmake --build <build_directory> --target install --config <desired_config>If you have not built the project yet, the automatic_rebuild_and_install.sh will do fine, otherwise follow the next section:
Note: If you want to supress a lot of warnings when building, see the CMakeLists.txt at line 145 and 146, and uncomment the preferred.
To build the project, all you need to do, after correctly installing the project, is run a similar CMake routine to the the one below:
mkdir build/ && cd build/
cmake .. -DCMAKE_INSTALL_PREFIX=/absolute/path/to/custom/install/directory
cmake --build . --target installNote: The custom
CMAKE_INSTALL_PREFIXcan be omitted if you wish to install in the default install location.
More options that you can set for the project can be found in the
cmake/StandardSettings.cmake file. For certain
options additional configuration may be needed in their respective *.cmake files
(i.e. Conan needs the CONAN_REQUIRES and might need the CONAN_OPTIONS to be setup
for it work correctly; the two are set in the cmake/Conan.cmake file).
In order to generate documentation for the project, you need to configure the build to use Doxygen. This is easily done, by modifying the workflow shown above as follows:
source build_auto_docs.shNote: This will generate a
docs/directory in the project's root directory.
This project uses Google Test
for unit testing. Unit testing can be disabled in the options, by setting the
ENABLE_UNIT_TESTING (from
cmake/StandardSettings.cmake) to be false. To run
the tests, simply use CTest, from the build directory, passing the desire
configuration for which to run tests for. An example of this procedure is:
cd build # if not in the build directory already
ctest -C Release # or `ctest -C Debug` or any other configuration you wish to test
# you can also run tests with the `-VV` flag for a more verbose output (i.e.
#GoogleTest output as well)after installing run the following in the project directory:
nmbluflowtorch [parallel | not ] [xor | autoencoder] [--epochs int]example:
The following will executethe xor program with parallelization for 100 epochs
nmbluflowtorch parallel xor --epochs 100- https://github.com/filipdutescu/modern-cpp-template Used for bootstrapping a c++ project and for managing building, installing, structure, as well as testing.
- https://github.com/krocki/MLP-CXX
- https://github.com/TheFirstGuy/ann
- https://github.com/leondavi/cppSANN
- https://github.com/Black-Phoenix/CUDA-MLP
This project is licensed under the Unlicense - see the LICENSE file for details