https://namvu.net/2021/07/setup-a-family-printer-with-a-raspberry-pi-1-and-canon-lbp-2900/

sudo apt install git build-essential automake cups libcups2-dev
git clone https://github.com/mounaiban/captdriver.git
cd captdriver
aclocal
autoconf
automake --add-missing
./configure
make
make ppd
sudo make install
sudo cp -p /usr/local/bin/rastertocapt /usr/lib/cups/filter/
sudo cp ppd/*.ppd /usr/share/ppd/custom/

• https://andreafortuna.org/2017/06/25/volatility-my-own-cheatsheet-part-1-image-identification/
• https://andreafortuna.org/2017/07/03/volatility-my-own-cheatsheet-part-2-processes-and-dlls/
• https://andreafortuna.org/2017/07/10/volatility-my-own-cheatsheet-part-3-process-memory/
• https://andreafortuna.org/2017/07/17/volatility-my-own-cheatsheet-part-4-kernel-memory-and-objects/
• https://andreafortuna.org/2017/07/24/volatility-my-own-cheatsheet-part-5-networking/
• https://andreafortuna.org/2017/07/31/volatility-my-own-cheatsheet-part-6-windows-registry/
• https://andreafortuna.org/2017/08/07/volatility-my-own-cheatsheet-part-7-analyze-and-convert-crash-dumps-and-hibernation-files/
• https://andreafortuna.org/2017/08/21/volatility-my-own-cheatsheet-part-8-filesystem/
• https://github.com/volatilityfoundation/volatility

Compile the kernel

# Install the needed packages
sudo apt install -y build-essential bison dwarves flex libssl-dev libelf-dev

# Clone kernel source
git clone https://github.com/microsoft/WSL2-Linux-Kernel.git
cd WSL2-Linux-Kernel

# Config kernel
cp Microsoft/config-wsl .config
sed -i 's/microsoft-standard-WSL2/generic/' .config # Change the LOCALVERSION value
sed -i 's/# CONFIG_SOUND is not set/CONFIG_SOUND=y\nCONFIG_SND=y/' .config # Enable sound modules
make olddefconfig

# Now that everything is ready, let's compile the kernel
make -j $(nproc)

# Copy the kernel into a directory in the Windows filesystem 
mkdir /mnt/c/wslkernel
cp arch/x86/boot/bzImage /mnt/c/wslkernel/custom_kernel

# Last step, the kernel needs to be referenced in the file .wslconfig 
nano /mnt/c/Users/<your username>/.wslconfig

The content of the .wslconfig should look like this:

[wsl2]
kernel = c:\\wslkernel\\custom_kernel

Now, reboot WSL by running the following command in PowerShell:

wsl --shutdown

Launch again a terminal with your WSL2 distro and confirm the new kernel is now being the one used:

uname -a

You should see generic in the output.

Install headers (for developing kernel modules)

sed -i 's/SPDX-License-Identifier: GPL-2.0/SPDX-License-Identifier: GPL-2.0 WITH Linux-syscall-note/g' include/uapi/misc/d3dkmthk.h
sudo make headers_install INSTALL_HDR_PATH=/usr

sudo mkdir -p /lib/modules/$(uname -r)
sudo ln -s <path to WSL2-Linux-Kernel> /lib/modules/$(uname -r)/build

1. Follow this instruction from NVIDIA to install CUDA drivers for WSL.

DO NOT install CUDA Toolkit yet. The version in that instruction is not compatible with current version of Tensorflow/Pytorch.

2. Install CUDA Toolkit 11.8.0 for WSL:

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/11.8.0/local_installers/cuda-repo-wsl-ubuntu-11-8-local_11.8.0-1_amd64.deb
sudo dpkg -i cuda-repo-wsl-ubuntu-11-8-local_11.8.0-1_amd64.deb
sudo cp /var/cuda-repo-wsl-ubuntu-11-8-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get -y install cuda

Add CUDA to path:

echo 'export PATH=/usr/local/cuda/bin:$PATH' >> ~/.zshrc
echo 'export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH' >> ~/.zshrc

Symlink libcuda (needed for building darknet):

sudo ln -s /usr/lib/wsl/lib/libcuda.so.1 /usr/local/cuda/lib64/libcuda.so

3. Install cuDNN

Go to https://developer.nvidia.com/rdp/cudnn-download and download cuDNN for CUDA 11.x for Linux.
Filename: cudnn-linux-x86_64-8.9.4.25_cuda11-archive.tar.xz

tar -xvf cudnn-linux-x86_64-8.9.4.25_cuda11-archive.tar.xz
cd cudnn-linux-x86_64-8.9.4.25_cuda11-archive
sudo cp -P include/* /usr/local/cuda/include/
sudo cp -P lib/* /usr/local/cuda/lib64/
sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*
sudo ldconfig /usr/local/cuda/lib64

4. Install pyenv and create a virtual environment

5. Install Tensorflow and Pytorch:

pip install --upgrade pip setuptools wheel
pip install torch torchvision torchaudio
pip install tensorflow

6. Install additional packages (optional):

pip install jupyterlab

In a nutshell: to avoid your shell character set from messing with imports, use -r to export and SOURCE when importing.

Dumping safely

# Do not do this, since it might screw up encoding
mysqldump -uroot -p database > utf8.dump # this is bad

Better do:

mysqldump -uroot -p database -r utf8.dump

Note that when your MySQL server is not set to UTF-8 you need to do mysqldump --default-character-set=latin1 (!) to get a correctly encoded dump. In that case, you will also need to remove the SET NAMES='latin1' comment at the top of the dump, so the target machine won't change its UTF-8 charset when sourcing.

If you only want to dump the structure without data, use

mysqldump -uroot -p --no-data database -r utf8.dump

Importing a dump safely

# Do not do this, since it might screw up encoding
mysql -u username -p database < dump_file # this is bad

Better do:

mysql -uroot -p --default-character-set=utf8mb4 database
mysql> SET names 'utf8';
mysql> SOURCE utf8.dump;

Ref: https://makandracards.com/makandra/595-dumping-and-importing-from-to-mysql-in-an-utf-8-safe-way