So finally get the grit to try some deep learning framework. This post tries to cover the basic installation tips to install Ubuntu 16+ on a ASUS ROG laptop with Torch deep learning framework so we can try the facebook’s DeepMask+SharpMask.
- Install Ubuntu. I choose to create a USB installer for this. Win32DiskImager is a good tool to create the install image.
- For ASUS ROG, some fast boot feature needs to be off so linux can be boot up. Please check online to set the bios.
- Look at this post from Taiwan for tips especially about installing Video card driver. Just in case, I leave the code for the Nvidia driver here:
sudo apt-get purge nvidia*
sudo apt-get purge bumblebee* primus
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
sudo apt-get install nvidia-352 nvidia-prime
sudo add-apt-repository -r ppa:bumblebee/stable
- On Youtube, there is a very good tutorial about how to install dual boot system so Ubuntu and Win 10 can run together. In my case, I have the Win 10 installed on the 500G SSD so I get the entire linux on a 200 GB partition of my 1TB data disk. My experience proves that following this video tutorial you should be OK to get a dual boot-able system after that. Since I don’t need to hibernate linux normally and I have enough RAM, I set swap as 2GB and just keep all the other 198 GB for the system.
- Do remember to follow the post in 3 for the Video card update since the facebook deepmask needs Nvidia GPU with compute power 3.5+, by default, Ubuntu will use the Intel integrated graphics card so install the Nvidia driver is necessary.
- Now you can follow the Torch web page to install Torch, just like the facebook deep mask page suggests.
- Notice that even after you installed the torch, you need CUDA package and other stuff to run the demo.
- First, you need to install the CUDA SDK so the cutorch can be installed. Follow the link here at Nvidia for how to install CUDA SDK. Then you just need to go to torch folder in your system and type : luarocks install cutorch, it should work like charm. Please follow the pre and pose installation guide since the command will be different based on your system. To get the correct CUDA SDK, go to here.