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ensmallen: a C++ header-only library for numerical optimization

ensmallen is a high-quality C++ library for non-linear numerical optimization.

ensmallen provides many types of optimizers that can be used for virtually any numerical optimization task. This includes gradient descent techniques, gradient-free optimizers, and constrained optimization. ensmallen also allows optional callbacks to customize the optimization process.

Documentation and downloads: http://ensmallen.org

Requirements

  • C++ compiler with C++11 support
  • Armadillo: http://arma.sourceforge.net
  • OpenBLAS or Intel MKL or LAPACK (see Armadillo site for details)

Installation

ensmallen can be installed in several ways: either manually or via cmake, with or without root access.

The cmake based installation will check the requirements and optionally build the tests. If cmake 3.3 (or a later version) is not already available on your system, it can be obtained from cmake.org. If you are using an older system such as RHEL 7 or CentOS 7, an updated version of cmake is also available via the EPEL repository (see the cmake3 package).

Example cmake based installation with root access:

mkdir build
cd build
cmake ..
sudo make install

Example cmake based installation without root access, installing into /home/blah/ (adapt as required):

mkdir build
cd build
cmake .. -DCMAKE_INSTALL_PREFIX:PATH=/home/blah/
make install

The above will create a directory named /home/blah/include/ and place all ensmallen headers there.

To optionally build and run the tests (after running cmake as above), use the following additional commands:

make ensmallen_tests
./ensmallen_tests --durations yes

Manual installation involves simply copying the include/ensmallen.hpp header and the associated include/ensmallen_bits directory to a location such as /usr/include/ which is searched by your C++ compiler. If you can't use sudo or don't have write access to /usr/include/, use a directory within your own home directory (eg. /home/blah/include/).

Example Compilation

If you have installed ensmallen in a standard location such as /usr/include/:

g++ prog.cpp -o prog -O2 -larmadillo

If you have installed ensmallen in a non-standard location, such as /home/blah/include/, you will need to make sure that your C++ compiler searches /home/blah/include/ by explicitly specifying the directory as an argument/option. For example, using the -I switch in gcc and clang:

g++ prog.cpp -o prog -O2 -I /home/blah/include/ -larmadillo

Example Optimization

See example.cpp for example usage of the L-BFGS optimizer in a linear regression setting.

License

Unless stated otherwise, the source code for ensmallen is licensed under the 3-clause BSD license (the "License"). A copy of the License is included in the "LICENSE.txt" file. You may also obtain a copy of the License at http://opensource.org/licenses/BSD-3-Clause

Citation

Please cite the following paper if you use ensmallen in your research and/or software. Citations are useful for the continued development and maintenance of the library.

@article{ensmallen_JMLR_2021,
  author  = {Ryan R. Curtin and Marcus Edel and Rahul Ganesh Prabhu and Suryoday Basak and Zhihao Lou and Conrad Sanderson},
  title   = {The ensmallen library for flexible numerical optimization},
  journal = {Journal of Machine Learning Research},
  year    = {2021},
  volume  = {22},
  number  = {166},
  pages   = {1--6},
  url     = {http://jmlr.org/papers/v22/20-416.html}
}

Developers and Contributors

  • Ryan Curtin
  • Dongryeol Lee
  • Marcus Edel
  • Sumedh Ghaisas
  • Siddharth Agrawal
  • Stephen Tu
  • Shikhar Bhardwaj
  • Vivek Pal
  • Sourabh Varshney
  • Chenzhe Diao
  • Abhinav Moudgil
  • Konstantin Sidorov
  • Kirill Mishchenko
  • Kartik Nighania
  • Haritha Nair
  • Moksh Jain
  • Abhishek Laddha
  • Arun Reddy
  • Nishant Mehta
  • Trironk Kiatkungwanglai
  • Vasanth Kalingeri
  • Zhihao Lou
  • Conrad Sanderson
  • Dan Timson
  • N Rajiv Vaidyanathan
  • Roberto Hueso
  • Sayan Goswami