├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── external       <- Data from third party sources.
│   ├── interim        <- Intermediate data that has been transformed.
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── docs               <- A default Sphinx project; see sphinx-doc.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),
│                         the creator's initials, and a short `-` delimited description, e.g.
│                         `1.0-jqp-initial-data-exploration`.
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── data           <- Scripts to download or generate data
│   │   └── make_dataset.py
│   │
│   ├── features       <- Scripts to turn raw data into features for modeling
│   │   └── build_features.py
│   │
│   ├── models         <- Scripts to train models and then use trained models to make
│   │   │                 predictions
│   │   ├── predict_model.py
│   │   └── train_model.py
│   │
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
│
└── tox.ini            <- tox file with settings for running tox; see tox.testrun.org

touch /etc/apt/sources.list.d/nvidia-ml.list
sudo echo 'deb http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1404/x86_64/ /' > /etc/apt/sources.list.d/nvidia-ml.list
sudo apt-get update && sudo apt-get install -y --no-install-recommends build-essential python3-dev cmake git curl vim ca-certificates libnccl2=2.0.5-2+cuda8.0 libnccl-dev=2.0.5-2+cuda8.0 libjpeg-dev libpng12-dev && rm -rf /var/lib/apt/lists/*
sudo apt-get update && sudo apt-get install -y libxtst6 g++
sudo -E add-apt-repository -y ppa:george-edison55/cmake-3.x
sudo -E apt-get update
sudo apt-get install cmake
sudo apt-get update
sudo apt-get upgrade

sudo apt-get install libmecab-dev make
sudo apt-get install mecab mecab-ipadic-utf8

$ git clone --depth 1 https://github.com/neologd/mecab-ipadic-neologd.git

$ cd mecab-ipadic-neologd

$ ./bin/install-mecab-ipadic-neologd -n

$ echo `mecab-config --dicdir`"/mecab-ipadic-neologd"

$ ./bin/install-mecab-ipadic-neologd -h

curl -o ~/miniconda.sh -O  https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
chmod +x ~/miniconda.sh
sh ~/miniconda.sh -b -p conda/ && rm ~/miniconda.sh
conda/bin/conda install numpy pyyaml mkl setuptools cmake cffi matplotlib

conda/bin/conda install -c soumith magma-cuda80

git clone --recursive https://github.com/pytorch/pytorch
cd pytorch
export PYTHON_VERSION=3.6
conda/bin/conda create -y --name pytorch-py$PYTHON_VERSION python=$PYTHON_VERSION numpy pyyaml scipy ipython mkl pyymal
conda/bin/conda clean -ya
source ../conda/bin/activate pytorch-py3.6
python setup.py insatll
export PATH=/opt/conda/envs/pytorch-py$PYTHON_VERSION/bin:$PATH
conda install --name pytorch-py$PYTHON_VERSION -c soumith magma-cuda80
export PATH=`pwd`/pytorch-reinforcement-learning/conda/envs/pytorch-py3.6/bin/:$PATH
conda install --name pytorch-py$PYTHON_VERSION -c soumith magma-cuda80
TORCH_CUDA_ARCH_LIST="3.5 5.2 6.0 6.1+PTX" TORCH_NVCC_FLAGS="-Xfatbin -compress-all"
CMAKE_PREFIX_PATH="$(dirname $(which conda))/../"
pip install -v .
git clone https://github.com/pytorch/vision.git && cd vision && pip install -v .
conda install pytorch torchvision cuda80 -c soumith
pip install git+https://github.com/pytorch/pytorch
pip install torchvision

source conda/bin/activate pytorch-py3.6