Graph compression for graph learning systems
Conda commands to recreate the virtual enviroment I am using
conda env create -f ${CUDA}/environment.yml
conda activate glzip_${CUDA}
pip install -r ${CUDA}/requirements.txt
where ${CUDA} should be replaced by cpu, cu102 or cu113 depending
on your device.
If you need to make changes to the environemnt. First clear the environment:
conda deactivate
conda env remove -n glzip_${CUDA}
then rebuild it.
With the environment active run maturin develop. That will install
the glzip module into the environment. maturin develop --release will build the
module with optimizations turned on which makes everything run much, much faster so
if you are not developing the library and do not need debug symbols, I recommend building
with --release.
Just run maturin develop or maturin develop --release again after making the changes.