Add WIP draft about installing tensorflow

2017-06-20 01:49:23 -04:00 · 2017-06-20 01:49:23 -04:00 · 1511b102ca
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+---
+title: How to Install TensorFlow on Ubuntu 16.04 with GPU Support
+layout: post
+---
+
+I found the [tensorflow
+documentation](https://www.tensorflow.org/install/install_linux) rather lacking
+for installation instructions, especially in regards to getting GPU support.
+I'm going to write down my notes from wrangling with the installation here for
+future reference and hopefully this helps someone else too.
+
+This will invariably go out-of-date at some point, so be mindful of the publish
+date of this post. Make sure to cross-reference other documentation that has
+more up-to-date information.
+
+## Assumptions
+
+These instructions are very specific to my environment, so this is what I am
+assuming:
+
+1. You are running Ubuntu 16.04. (I have 16.04.1)
+    - You can check this in the output of `uname -a`
+2. You have a 64 bit machine.
+    - You can check this with `uname -m`. (should say `x86_64`)
+2. You have an NVIDIA GPU that has CUDA Compute Capability 3.0 or higher.
+[NVIDIA documentation] has a full table of cards and their Compute Capabilities.
+(I have a GeForce GTX 980 Ti)
+    - You can check what card you have in Settings > Details under the label
+      "Graphics"
+    - You can also check by verifying there is any output when you run `lspci |
+      grep -i nvidia`
+3. You have a linux kernel version 4.4.0 or higher. (I have 4.8.0)
+    - You can check this by running `uname -r`
+4. You have gcc version 5.3.1 or higher installed. (I have 5.4.0)
+    - You can check this by running `gcc --version`
+5. You have the latest [proprietary](https://i.imgur.com/8osspXj.jpg) NVIDIA
+drivers installed.
+    - You can check this and install it if you haven't in the "Additional
+      Drivers" tab in the "Software & Updates" application (`update-manager`).
+      (I have version 375.66 installed)
+6. You have the kernel headers installed.
+    - Just run `sudo apt-get install linux-headers-$(uname -r)` to install them
+      if you don't have them installed already.
+7. You have Python installed. The exact version shouldn't matter, but for the
+rest of this post I'm going to assume you have `python3` installed.
+    - You can install `python3` by running `sudo apt-get install python3`. This
+      will install Python 3.5.
+    - Bonus points: you can install Python 3.6 by following [this
+      answer](https://askubuntu.com/a/865569), but Python 3.5 should be fine.
+
+## Install the CUDA Toolkit 8.0
+
+NVIDIA has [a big scary documentation
+page](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/) on this, but I
+will summarize the only the parts you need to know here.
+
+Go to the [CUDA Toolkit Download](https://developer.nvidia.com/cuda-downloads)
+page. Click Linux > x86_64 > Ubuntu > 16.04 > deb (network).
+
+Click download and then follow the instructions, copied here:
+
+1. `sudo dpkg -i cuda-repo-ubuntu1604_8.0.61-1_amd64.deb`
+2. `sudo apt-get update`
+3. `sudo apt-get install cuda`
+
+This will install CUDA 8.0. It installed it to the directory
+`/usr/local/cuda-8.0/` on my machine.
+
+There are some [post-install
+actions](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#post-installation-actions)
+we must follow:
+
+1. Edit your `~/.bashrc`
+    - Use your favorite editor `gedit ~/.bashrc`, `nano ~/.bashrc`, `vim
+      ~/.bashrc`, whatever.
+2. Add the following lines to the end of the file:
+```bash
+# CUDA 8.0 (nvidia) paths
+export CUDA_HOME=/usr/local/cuda-8.0
+export PATH=/usr/local/cuda-8.0/bin${PATH:+:${PATH}}
+export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
+```
+3. Save and exit.
+4. Run `source ~/.bashrc`.
+5. Install writable samples by running the script `cuda-install-samples-8.0.sh
+~/`.
+   - If the script cannot be found, the above steps didn't work :(
+   - I don't actually know if the samples are absolutely required for what I'm
+     using CUDA for, but it's recommended according to NVIDIA, and compiling
+     them will output a nifty `deviceQuery` binary which can be ran to test if
+     everything is working properly.
+6. Make sure `nvcc -V` outputs something.
+   - If an error, the above steps 1-4 didn't work :(
+7. `cd ~/NVIDIA_CUDA-8.0_Samples`, cross your fingers, and run `make`
+   - The compile will take a while
+   - My compile actually errored near the end with an error about `/usr/bin/ld:
+     cannot find -lcudart`. I *think* that doesn't really matter because the
+     binary files where still output.
+8. Try running `~/NVIDIA_CUDA-8.0_Samples/bin/x86_64/linux/release/deviceQuery`
+to see if you get any output. Hopefully you will see your GPU listed.
+
+## Install cuDNN v5.1
+
+## Install libcupti-dev
+
+## Create a Virtualenv
+
+## Install the TensorFlow with GPU support