Takion is C++17 template based implementation of deep learning. It is suitable for deep learning on limited computational resource, embedded systems and IoT devices. The code can be compiled with commonly available compilers such as g++, clang++, or Microsoft Visual Studio. Takion currently supports macOS (10.12.6 or later), Ubuntu (18.04 or later), Windows (Visual Studio 2017 or later), and Windows Subsystem for Linux (WSL). Other untested platforms that support C++17 also should be able to build Takion.
- Reasonably fast, without GPU
- Portable & header-only
- Easy to integrate with real applications
- Simply implemented
- Supports AVX/AVX2 based vector extensions with OpenMP
- Automatically finds concurrency in graph structure
You can contact me via e-mail (jwkim98@kaist.ac.kr). I am always happy to answer questions or help with any issues you might have, and please be sure to share any additional work or your creations with me, I love seeing what other people are making.
Here is the example code for building graphs
The graph interface is meant to be user friendly and interactive
After browsing into cloned repository directory,
Change the value of trainFilePath and validationFilePath to the file path that you saved your
mnist_train.csv and mnist_test.csv file from
Tests/UnitTests/GraphTest/SimpleGraphTest.cpp
Sample dataset can be downloaded from (https://www.kaggle.com/oddrationale/mnist-in-csv)
Or you can make build model using the interface
Linux
git submodule init
git submodule update
cmake .
make -j$(nproc)
./bin/UnitTests
The class is licensed under the MIT License:
Copyright ©: Jaewoo Kim
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.