https://github.com/sdadia/deep-learning-and-optimization

C++ Optimization/Deep Learning Framework For Research & Prototyping
https://github.com/sdadia/deep-learning-and-optimization

cpp cpp14 deep-learning optimization-library

Last synced: 6 months ago
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C++ Optimization/Deep Learning Framework For Research & Prototyping

• Host: GitHub
• URL: https://github.com/sdadia/deep-learning-and-optimization
• Owner: sdadia
• License: mit
• Created: 2017-08-12T20:41:43.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2017-08-17T15:08:59.000Z (over 8 years ago)
• Last Synced: 2025-01-29T16:31:44.616Z (11 months ago)
• Topics: cpp, cpp14, deep-learning, optimization-library
• Language: C++
• Size: 76.2 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
![DPLO](.dpl_logo.png?raw=true "Deep Learning & Optimization")

## Dependencies

- Xtensor : https://github.com/QuantStack/xtensor

- BLAS & LAPACK

- Gtest : https://github.com/google/googletest

- Cmake

- Make

- Doxygen

- Git

## Install Dependencies

    sudo apt-get update ; sudo apt-get upgrade

- BLAS and LAPACK, Make, libstdc++, GCC, Doxygen, Gtest:

    sudo apt-get install build-essential git libblas-dev liblapack-dev libgtest-dev doxygen

- Xtensor : https://github.com/QuantStack/xtensor

    cd $HOME ; git clone https://github.com/QuantStack/xtensor

    cd xtensor; mkdir build && cd build;

    cmake -DBUILD_TESTS=ON -DDOWNLOAD_GTEST=ON ..

    make

    make xtest

    sudo make install

## Compilation & Install

This will create static library in **build/lib** & executibles in **build/bin/**

    make all -j4 -s -O      # to make static library and test executible

    make docs               # to create documentation

    make clean # to remove all the above

## Create new layer

Just create a new .hpp and .cpp file with the corresponding layer name

* implement setUp(), forward(), backward() functions

**sigmoid.hpp**

    #include "common.hpp"

    namespace dpl

    {

        class MySigmoidLayer

        {

            void setUp(std::vector inputs);

            void forward();

            void backward(std::vector grad_from_top);

        }

    }

**sigmoid.cpp**

    #include "common.hpp"

    #include "sigmoid.hpp"

    namespace dpl

    {

        void MySigmoidLayer::setUp(std::vector inputs)

        {

            // code here

        }

        void MySigmoidLayer::forward()

        {

            // forward prop code here

        }   

        void MySigmoidLayer::backward(std::vector grad_from_top)

        {

            // back prop code here

        }

        

    }