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ubuntu 20.04 LTS fresh install guide

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Mackenzie Mathis edited this page Jul 1, 2021 · 10 revisions

Hello!

Another cookbook entry on how to install your freshly installed 20.04 LTS system for DLC use! Namely, CUDA, drivers, Docker, and anaconda!

Let's start with CUDA support for your GPU:

sudo apt install gcc

then:

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin
sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda-repo-ubuntu2004-11-3-local_11.3.1-465.19.01-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu2004-11-3-local_11.3.1-465.19.01-1_amd64.deb
sudo apt-key add /var/cuda-repo-ubuntu2004-11-3-local/7fa2af80.pub
sudo apt-get update
sudo apt-get -y install cuda

Then:

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update
sudo ubuntu-drivers autoinstall

then:

reboot

re-open terminal and check gcc version:

gcc --version

output:

gcc --version
gcc (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Copyright (C) 2019 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

Then finish installation:

sudo apt install nvidia-cuda-toolkit gcc-9

Then check:

nvcc --version

All set! If error messages, read them carefully as they often tell you how to fix it, or what to google :D

Now you can see CUDA, DRIVER, GPU(s):

nvidia-smi

output:

nvidia-smi
Tue Jun 22 18:46:26 2021       
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 465.19.01    Driver Version: 465.19.01    CUDA Version: 11.3     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA GeForce ...  On   | 00000000:0B:00.0  On |                  N/A |
|  0%   46C    P8    11W / 200W |    252MiB /  8116MiB |      5%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

Next, Docker!

sudo apt-get install \
    apt-transport-https \
    ca-certificates \
    curl \
    gnupg \
    lsb-release

add key: curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /usr/share/keyrings/docker-archive-keyring.gpg

echo \
  "deb [arch=amd64 signed-by=/usr/share/keyrings/docker-archive-keyring.gpg] https://download.docker.com/linux/ubuntu \
  $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null

Then:

sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io

some clean up: sudo apt autoremove

now you can run sudo docker run hello-world

and get:

Hello from Docker!
This message shows that your installation appears to be working correctly.

To generate this message, Docker took the following steps:
 1. The Docker client contacted the Docker daemon.
 2. The Docker daemon pulled the "hello-world" image from the Docker Hub.
    (amd64)
 3. The Docker daemon created a new container from that image which runs the
    executable that produces the output you are currently reading.
 4. The Docker daemon streamed that output to the Docker client, which sent it
    to your terminal.

To try something more ambitious, you can run an Ubuntu container with:
 $ docker run -it ubuntu bash

Share images, automate workflows, and more with a free Docker ID:
 https://hub.docker.com/

For more examples and ideas, visit:
 https://docs.docker.com/get-started/

Next, Anaconda!

Click here to get the ubuntu/linux package: https://www.anaconda.com/products/individual#linux

this downloads a file, save it (I save into downloads)

then cd Downloads:

and run:

bash Anaconda3-2021.05-Linux-x86_64.sh

and you get:

Welcome to Anaconda3 2021.05

In order to continue the installation process, please review the license
agreement.
Please, press ENTER to continue
>>>

Follow prompts!

Next, DeepLabCut!

Given this is a totally fresh install, here are a few things that I also needed: sudo apt install libcanberra-gtk-module libcanberra-gtk3-module Then I proceeded below:

I grab the conda file from the website at www.deeplabcut.org. Simply click to download (DEEPLABCUT). For me, this goes into Downloads.

So, I open a terminal, cd Downloads, and then run: conda env create -f DEEPLABCUT.yaml

Follow prompts!

Troubleshooting: Note, if you get a failed build due to wxPython, i.e.:

ERROR: Command errored out with exit status 1: /home/mackenzie/anaconda3/envs/DLC-GPU/bin/python -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-0jsmkrr1/wxpython_aeff462b2060421a9cf65df55f63a126/setup.py'"'"'; __file__='"'"'/tmp/pip-install-0jsmkrr1/wxpython_aeff462b2060421a9cf65df55f63a126/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(__file__) if os.path.exists(__file__) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-pzy9q5u2/install-record.txt --single-version-externally-managed --compile --install-headers /home/mackenzie/anaconda3/envs/DLC-GPU/include/python3.7m/wxpython Check the logs for full command output.

failed

CondaEnvException: Pip failed

remove conda env: conda remove --name DLC-GPU --all, open the DLC-GPU.yaml file (any text editor!) and change deeplabcut[gui] to deeplabcut. Then run: conda env create -f DLC-GPU.yaml again...

then you will get:

 Successfully uninstalled decorator-5.0.9
Successfully installed PyWavelets-1.1.1 absl-py-0.13.0 astor-0.8.1 bayesian-optimization-1.2.0 chardet-4.0.0 click-8.0.1 cycler-0.10.0 cython-0.29.23 decorator-4.4.2 deeplabcut-2.1.10.4 filterpy-1.4.5 gast-0.2.2 google-pasta-0.2.0 grpcio-1.38.1 h5py-2.10.0 idna-2.10 imageio-2.9.0 imageio-ffmpeg-0.4.4 imgaug-0.4.0 intel-openmp-2021.2.0 joblib-1.0.1 keras-applications-1.0.8 keras-preprocessing-1.1.2 kiwisolver-1.3.1 llvmlite-0.34.0 markdown-3.3.4 matplotlib-3.1.3 moviepy-1.0.1 msgpack-1.0.2 msgpack-numpy-0.4.7.1 networkx-2.5.1 numba-0.51.1 numexpr-2.7.3 numpy-1.17.5 opencv-python-4.5.2.54 opencv-python-headless-3.4.9.33 opt-einsum-3.3.0 pandas-1.2.5 patsy-0.5.1 pillow-8.2.0 proglog-0.1.9 protobuf-3.17.3 psutil-5.8.0 pytz-2021.1 pyyaml-5.4.1 requests-2.25.1 ruamel.yaml-0.17.9 ruamel.yaml.clib-0.2.2 scikit-image-0.18.1 scikit-learn-0.24.2 scipy-1.7.0 statsmodels-0.12.2 tables-3.6.1 tabulate-0.8.9 tensorboard-1.15.0 tensorflow-estimator-1.15.1 tensorflow-gpu-1.15.5 tensorpack-0.9.8 termcolor-1.1.0 threadpoolctl-2.1.0 tifffile-2021.6.14 tqdm-4.61.1 urllib3-1.26.5 werkzeug-2.0.1 wrapt-1.12.1

done
#
# To activate this environment, use
#
#     $ conda activate DLC-GPU
#
# To deactivate an active environment, use
#
#     $ conda deactivate

Activate! conda activate DLC-GPU and then run: conda install -c conda-forge wxpython ... after this finishes, run: pip install deeplabcut[gui]

Now you might get some warnings, but for me it was then totally fine to run python -m deeplabcut which launches the DLC GUI!

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