- Do README <---
conda create -n py310ESRGAN python=3.10 anacond
input_file=test-img-lowres.jpg | |
output_base=_test-img-lowres-upres-gia | |
model_name="realesrgan-x4plus-anime" | |
#Init | |
sudo mkdir -p -m 777 /repos | |
cd /repos && git clone https://github.com/GuillaumeAI/giar-Real-ESRGAN.git \ | |
&& cd giar-Real-ESRGAN | |
conda create -n py310ESRGAN python=3.10 anacond
cdir=$(pwd);for d in $(cat _dist.txt);do cd $d;for f in *;do echo $f;fx1=${f//\(/_};fx=${fx1//\)/};mv "$f" "$fx";done;cd $cdir;done |
cat Dockerfile.tmp | \ | |
sed 's/\# RUN/#ABC/g' | \ | |
sed 's/\#RUN/#ABC/g'| awk '/RUN apt/' | \ | |
sed 's/RUN apt-get -y install//g' | \ | |
sed 's/RUN apt-get install -y//g' | \ | |
awk '/RUN apt/' | \ | |
sed 's/RUN apt -y install//g' | \ | |
sed 's/RUN apt install -y//g' | \ | |
sed 's/--fix-missing//g' | |
##>> Dockerfile |
--[[ json.lua | |
A compact pure-Lua JSON library. | |
The main functions are: json.stringify, json.parse. | |
## json.stringify: | |
This expects the following to be true of any tables being encoded: | |
* They only have string or number keys. Number keys must be represented as | |
strings in json; this is part of the json spec. |
#!/bin/bash | |
cat _srrun_221109.sh | awk '/ bg/ { print "tail -f conf/logs/"$2".log &" }' |
Docker Desktop WSL 2 backend is not supported yet with GPUs. You will have to install Docker as you would traditionally in Linux for WSL 2 and then install NVIDIA Container Toolkit (or nvidia-docker2) for now. nvidia-container-toolkit and nvidia-docker2 in the end are just wrappers. There is a slight variation depending on which version of Docker you use (19.03 vs. 18.09), but if you chose to install nvidia-docker2, then that works across both releases of Docker. I’ll look into making that more clear in the documentation. nvidia-smi does not work because we don’t support NVML in WSL 2 yet - this is part of the Known Limitations in the user-guide. We will be adding support for it in the near future. >https://forums.developer.nvidia.com/t/hiccups-setting-up-wsl2-cuda/128641
docker pull guillaumeai/server:ast-210606-singleone-v1-dev |
# Inspired from :https://ubuntu.com/tutorials/enabling-gpu-acceleration-on-ubuntu-on-wsl2-with-the-nvidia-cuda-platform#3-install-nvidia-cuda-on-ubuntu | |
# Notes: the steps did not worked as written | |
# here is my order: | |
wget https://developer.download.nvidia.com/compute/cuda/repos/wsl-ubuntu/x86_64/cuda-wsl-ubuntu.pin | |
sudo mv cuda-wsl-ubuntu.pin /etc/apt/preferences.d/cuda-repository-pin-600 | |
wget https://developer.download.nvidia.com/compute/cuda/11.4.0/local_installers/cuda-repo-wsl-ubuntu-11-4-local_11.4.0-1_amd64.deb |