compile.rst

Install and Citations
=====================


Installation
------------

    * Install PyTorch 1.4.0 by following the `PyTorch instructions <http://pytorch.org/>`_.
 
    * PIP Install::

        pip install torch-encoding --pre
        # macOS
        CC=clang CXX=clang++ pip install torch-encoding --pre

    * Install from source:: 

        git clone https://github.com/zhanghang1989/PyTorch-Encoding && cd PyTorch-Encoding
        # ubuntu
        python setup.py install
        # macOS
        CC=clang CXX=clang++ python setup.py install


Using Docker
------------

We strongly recommend using the docker option, if you are experiencing any errors using standard installation.

    * Install Docker Engine by following the `Install Docker Engine <https://docs.docker.com/engine/install/>`_.
    * Build the docker image::

        git clone https://github.com/zhanghang1989/PyTorch-Encoding && cd PyTorch-Encoding
        bash scripts/build_docker.sh

    * Run the docker::

        bash scripts/run_docker.sh


Detailed Steps
--------------

This tutorial is a sucessful setup example for AWS EC2 p3 instance with ubuntu 16.04, CUDA 10.
We cannot guarantee it to work for all the machines, but the steps should be similar.
Assuming CUDA and cudnn are already sucessfully installed, otherwise please refer to other tutorials.

      * Install Anaconda from the `link <https://www.anaconda.com/distribution/>`_ .

      * Install ninja::
 
         wget https://github.com/ninja-build/ninja/releases/download/v1.8.2/ninja-linux.zip
         sudo unzip ninja-linux.zip -d /usr/local/bin/
         sudo update-alternatives --install /usr/bin/ninja ninja /usr/local/bin/ninja 1 --force

      * Install PyTorch::

         conda install pytorch torchvision cudatoolkit=10.0 -c pytorch

      * Install this package::

         pip install torch-encoding --pre

Citations
---------

    .. note::
        * Hang Zhang et al. "ResNeSt: Split-Attention Networks" *arXiv 2020*::

            @article{zhang2020resnest,
            title={ResNeSt: Split-Attention Networks},
            author={Zhang, Hang and Wu, Chongruo and Zhang, Zhongyue and Zhu, Yi and Zhang, Zhi and Lin, Haibin and Sun, Yue and He, Tong and Muller, Jonas and Manmatha, R. and Li, Mu and Smola, Alexander},
            journal={arXiv preprint arXiv:2004.08955},
            year={2020}
            }

        * Hang Zhang, Kristin Dana, Jianping Shi, Zhongyue Zhang, Xiaogang Wang, Ambrish Tyagi, Amit Agrawal. "Context Encoding for Semantic Segmentation"  *The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2018*::

            @InProceedings{Zhang_2018_CVPR,
            author = {Zhang, Hang and Dana, Kristin and Shi, Jianping and Zhang, Zhongyue and Wang, Xiaogang and Tyagi, Ambrish and Agrawal, Amit},
            title = {Context Encoding for Semantic Segmentation},
            booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
            month = {June},
            year = {2018}
            }


        * Hang Zhang, Jia Xue, and Kristin Dana. "Deep TEN: Texture Encoding Network." *The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017*::

            @InProceedings{Zhang_2017_CVPR,
            author = {Zhang, Hang and Xue, Jia and Dana, Kristin},
            title = {Deep TEN: Texture Encoding Network},
            booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
            month = {July},
            year = {2017}
            }