AI-ML-HPC-Workflows/workflows/pytorch_GAN_zoo/README.md

PyTorch GAN Zoo

This example builds a singularity container for Facebook Research's PyTorch GAN Zoo.

The singularity container will allow you to call all the scripts from the project and includes are requirements. The container supports CUDA versions 10.1, 10.2 and 11.1 on the host.

Building

To build the singularity container use the build script in this directory.

./build.sh

This script will try to use singularities fakeroot support if you run as a non-root user. If this is not supported on your system you can run the script as root.

When the script is finished you will find the container (pytorch_GAN_zoo.sif) in you current working directory.

Usage

The scripts from PyTorch GAN Zoo can be called with singularity exec pytorch_GAN_zoo.sif <script name>, for example

singularity exec pytorch_GAN_zoo.sif eval.py

Any flags or command line arguments can be declared after the script name.

When training, you will need to supply the --nv flag to singularity so that the host GPU may be used. You will also need to select a singularity app, using the --app flag to select the appropriate CUDA version. The available apps are cu101, cu102, and cu111 for CUDA 10.1, 10.2 and 11.1 respectively.

For example, to pre-process the celeba dataset and train a PGAN model on a host with CUDA 10.2 you could run the following commands.

singularity exec pytorch_GAN_zoo.sif datasets.py celeba_cropped <path to celeba dataset>/img_align_celeba/ -o celeba
singularity exec pytorch_GAN_zoo.sif --nv --app cu102 train.py PGAN -c config_celeba_cropped.json --restart -n celeba_cropped