commit #27: add install tutorials

doc/OpenAI-gym-install.md

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+# OpenAI Gym Install & Setting
+
+Assume we already installed all of deep learning packages we need(tf, pytorch etc.)  
+
+
+## Install openai-gym
+
+
+In order to install openai-gym, we should setup the following packages:
+
+```
+sudo apt install cmake swig zlib1g-dev python3-tk -y
+```
+
+To save videos, we aslo need to install ffmpeg
+
+```
+sudo apt install ffmpeg
+```
+
+Then, we can setup openai-gym by the following commands:
+
+```
+git clone https://github.com/openai/gym
+cd gym
+pip3 install gym[all]
+```
+
+## Use fake screen to get videos
+
+
+Because remote server has no display device, we can't see the training process and save videos.  
+So we will use the following method to get the remote screen.
+
+
+- Change GPU fan setting
+
+```
+sudo nvidia-xconfig -a --cool-bits=4
+```
+
+
+- Download the file [dfp-edid.bin][1] & move it to ``/etc/``
+
+- Open xorg.conf
+
+```
+sudo vim /etc/X11/xorg.conf
+```
+
+- Insert the following three lines in each Section "Screen":
+
+![screen][2]
+
+```
+Option      "UseDisplayDevice" "DFP-0"
+Option      "ConnectedMonitor" "DFP-0"
+Option      "CustomEDID" "DFP-0:/etc/dfp-edid.bin"
+
+```
+
+- Restart X server(ex. lightdm)
+
+```
+sudo service lightdm restart
+```
+
+- Auto login setting
+
+bulid(or modify) file ``vim /etc/lightdm/lightdm.conf``  
+write the following lines:
+
+```
+[Seat:*]
+autologin-guest=false
+autologin-user=username
+autologin-user-timeout=0
+```
+then restart X server again.
+
+- Install anydesk
+    - Download & upload to your server(via sftp, scp or using wget etc.)
+    - Install deb: ``sudo dpkg -i anydesk.XXX.deb``
+    - Set password: ``anydesk --set-password``
+    - Get ID: ``anydesk --get-id``
+    - run anydesk ``anydesk``
+    - (optinal) if it still doesn't work, try to use cmd ``export DISPLAY=:0``
+
+
+## Use AnyDesk
+
+
+- Download AnyDesk from [official website][3], windowsx64 version in this tutorial.  
+- Double click to run the application(no need to install).
+- Enter the ID we got from remote server.
+- Enter the password.
+- Then,you can see the remote desktop, enjoy it!
+
+![anydesk][4]
+
+
+## Run an simple code
+
+```
+import gym
+env = gym.make('CartPole-v0')
+env.reset()
+for _ in range(1000):
+    env.render()
+    env.step(env.action_space.sample()) # take a random action
+```
+
+You can see the environment works fine!  
+Take it easy!
+
+
+![run][5]
+
+## Reference
+
+
+- [OpenAI Documentation][6]
+- [Command Line Interface][7]
+
+
+  [1]: https://1drv.ms/u/s!AiF_YAjgP2iqmUKHkH7t8lzlz9aO
+  [2]: ./img/screen.png
+  [3]: https://anydesk.com/platforms
+  [4]: ./img/anydesk.png
+  [5]: ./img/run.png
+  [6]: https://gym.openai.com/docs/
+  [7]: http://support.anydesk.com/knowledgebase/articles/441867-command-line-interface

doc/PyTorch-install.md

@@ -0,0 +1,238 @@
+# NVIDIA Driver & Pytorch installation 
+
+The simple setup tutorial for deep learning beginner. 
+
+## STEP 1: Install NVIDIA Driver
+
+
+```
+sudo apt-get update
+sudo apt-get upgrade
+```
+
+- Disable Nouveau
+
+```
+sudo vi /etc/modprobe.d/disable-nouveau.conf
+
+//insert the following lines
+blacklist nouveau
+options nouveau modeset=0
+
+```
+
+- Update kernel initramfs
+
+```
+sudo update-initramfs -u
+sudo reboot
+```
+
+- Install NVIDIA driver
+
+> hit **Ctrl+Alt+F1(tty1)** and login, stop lightdm service & install dirver
+
+```
+sudo service lightdm stop
+sudo apt-get install nvidia-375
+sudo reboot
+```
+
+(optional)To install latest drivers add PPA:
+
+```
+sudo apt-get purge nvidia-*
+sudo add-apt-repository ppa:graphics-drivers/ppa
+sudo apt-get update
+sudo apt-get install nvidia-3xx
+```
+
+Then, you can use ``nvidia-smi`` to get the GPU info.
+
+## STEP 2: Install CUDA 8.0
+
+- Download setup file from [official website][1]
+- The latest release version is 9.0, but we use [CUDA 8.0][2] ``cuda_8.0.61_375.26_linux.run``
+
+
+```
+cd Downloads/
+sudo chmod a+x cuda_8.0.61_375.26_linux.run
+sudo ./cuda_8.0.61_375.26_linux.run
+```
+
+- Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 375.26?
+- (**Attention!**) Please input **no** 
+
+```
+Do you accept the previously read EULA?
+accept/decline/quit: accept
+
+Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 375.26?
+(y)es/(n)o/(q)uit: no
+
+Install the CUDA 8.0 Toolkit?
+(y)es/(n)o/(q)uit: y
+Enter Toolkit Location
+ [ default is /usr/local/cuda-8.0 ]: 
+Do you want to install a symbolic link at /usr/local/cuda?
+(y)es/(n)o/(q)uit: y
+Install the CUDA 8.0 Samples?
+(y)es/(n)o/(q)uit: y
+Enter CUDA Samples Location
+ [ default is /home/bg ]: 
+
+```
+
+- Set up the environment
+
+```
+sudo vi ~/.bashrc  
+//insert the following lines
+export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64
+export CUDA_HOME=/usr/local/cuda-8.0
+```
+
+- Reload .bashrc
+
+```
+source ~/.bashrc
+```
+
+- (optional)You can also test CUDA Samples
+
+```
+cd /usr/local/cuda-8.0/samples/1_Utilities/deviceQuery
+sudo make
+sudo ./deviceQuery
+```
+
+## STEP 3: Install Cudnn
+
+
+- Download cuDNN files from [official website][3] (need to login, ``cuDNN v6.0 for CUDA 8.0`` in this tutorial)
+
+```
+cd Downloads/
+tar -zxvf cudnn-8.0-linux-x64-v6.0.tgz
+sudo cp cuda/include/cudnn.h /usr/local/cuda-8.0/include
+sudo cp cuda/lib64/libcudnn* /usr/local/cuda-8.0/lib64
+sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda-8.0/lib64/libcudnn*
+```
+
+## STEP 4-1: Install [PyTorch][4] via virtualenv
+
+----------
+
+[virtualenv][5] is a tool to create isolated Python environments.  
+We recommend you to use it instead of "native" pip.
+
+- 1) Install pip and virtualenv(python3)
+
+```
+sudo apt-get install python3-pip python3-dev python-virtualenv
+```
+
+- 2) Create a virtualenv environment:
+```
+virtualenv --system-site-packages -p python3 targetDirectory 
+```
+where ``targetDirectory`` specifies the top of the virtualenv tree, our instructions assume that ``targetDirectory`` is ``~/deeplearning``, but you may choose any directory.
+
+- 3) Activate the virtualenv environment:
+
+```
+source ~/deeplearning/bin/activate
+```
+
+The preceding source command should change your prompt to the following:
+
+```
+(deeplearning) bg@bg-cgi:~$
+```
+
+- 4) Ensure pip ≥8.1 is installed:
+
+```
+(deeplearning) bg@bg-cgi:~$ easy_install -U pip
+```
+
+- 5) Run this command to install Pytorch(python3.5):
+
+```
+pip3 install http://download.pytorch.org/whl/cu80/torch-0.2.0.post3-cp35-cp35m-manylinux1_x86_64.whl 
+pip3 install torchvision
+```
+
+Then, just test the Warm Up demo:
+
+```
+(deeplearning) bg@bg-cgi:~$ git clone https://github.com/2017-fall-DL-training-program/PyTorchWarmUp.git
+(deeplearning) bg@bg-cgi:~$ cd PyTorchWarmUp/
+(deeplearning) bg@bg-cgi:~/PyTorchWarmUp$ python3 CNN_MNIST_pytorch.py
+```
+
+After training(a few mins), you can see the following result:
+
+```
+Train Epoch: 20 [58496/60000 (97%)] Loss: 0.012621
+Train Epoch: 20 [58624/60000 (98%)] Loss: 0.011611
+Train Epoch: 20 [58752/60000 (98%)] Loss: 0.010518
+Train Epoch: 20 [58880/60000 (98%)] Loss: 0.008049
+Train Epoch: 20 [59008/60000 (98%)] Loss: 0.042140
+Train Epoch: 20 [59136/60000 (99%)] Loss: 0.002592
+Train Epoch: 20 [59264/60000 (99%)] Loss: 0.003716
+Train Epoch: 20 [59392/60000 (99%)] Loss: 0.006034
+Train Epoch: 20 [59520/60000 (99%)] Loss: 0.015948
+Train Epoch: 20 [59648/60000 (99%)] Loss: 0.005287
+Train Epoch: 20 [59776/60000 (100%)]    Loss: 0.039094
+Train Epoch: 20 [44928/60000 (100%)]    Loss: 0.005245
+
+Test set: Average loss: 0.0271, Accuracy: 9908/10000 (99%)
+
+```
+
+## STEP 4-2: Install [TensorFlow][6] via virtualenv
+
+
+- 1 - 4: same as PyTorch
+
+- 5) Issue one of the following commands to install TensorFlow(GPU) in the active virtualenv environment:
+
+```
+(deeplearning) bg@bg-cgi:~$ pip install --upgrade tensorflow      # for Python 2.7
+(deeplearning) bg@bg-cgi:~$ pip3 install --upgrade tensorflow     # for Python 3.n
+(deeplearning) bg@bg-cgi:~$ pip install --upgrade tensorflow-gpu  # for Python 2.7 and GPU
+(deeplearning) bg@bg-cgi:~$ pip3 install --upgrade tensorflow-gpu # for Python 3.n and GPU
+
+```
+
+- 6) When you are done using Pytorch(TensorFlow), you may deactivate the environment by invoking the deactivate function as follows:
+
+```
+(deeplearning) bg@bg-cgi:~$ deactivate 
+```
+
+
+- 7) Uninstalling Pytorch(TensorFlow)
+
+To uninstall Pytorch(TensorFlow), simply remove the tree you created. For example:
+
+```
+rm -r ~/deeplearning
+```
+
+## Reference
+
+- [pytorch.org][7]
+- [tensorflow install][8]
+
+
+  [1]: https://developer.nvidia.com/cuda-downloads
+  [2]: https://developer.nvidia.com/cuda-toolkit-archive
+  [3]: https://developer.nvidia.com/rdp/cudnn-download
+  [4]: http://pytorch.org/
+  [5]: https://github.com/pypa/virtualenv
+  [6]: https://www.tensorflow.org/install/
+  [7]: http://pytorch.org/
+  [8]: https://www.tensorflow.org/install/install_linux