The styleGAN3 model is trained on the Cedar platform. This model supports three configs: StyleGAN3-T (translation equiv.), StyleGAN3-R (translation and rotation equiv.), or StyleGAN2.
Refer to this documentation to prepare the image set for this training.
Step 1: Use rsync or other commands to transfer transformed Bliss
images to Cedar
Step 2. Login to the Cedar and fetch stylegan3 source code
mkdir stylegan3
cd stylegan3
git clone https://github.com/NVlabs/stylegan3
Step 3. Creating a zip archive of Bliss images will lead to a better performance
cd stylegan3
python dataset_tool.py --source=../bliss_single_chars_final --dest=../datasets/bliss-256x256.zip
Step 4: Submit Job
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Copy requirements.txt to stylegan3 source code root directory.
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Copy job_stylegan3.sh to the `scratch/' directory in your home directory
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Submit the job
cd ~/scratch
sbatch job_stylegan3.sh
Use sq to check the status of the job. Use scancel to cancel a running job.
The Bliss images were first trained using stylegan3-r config (translation and rotation equiv.). This job had to be
cancelled after running 2.5 days because the cluster the job was running on is a shared resource that was waited by
another team. Before the cancellation, the job had generated some training result that can be found at
this repository.
reals.png is a collection of real Bliss symobles
fakes*.png are random image grids exported from the training loop at regular intervals.
training_options.json contains training options used for this round of training.
metric-fid50k_full.jsonl logs the result and records` FID evaluated by the training loop for every export.
Looking at metric-fid50k_full.jsonl, network-snapshot-004160.pkl model has the lowest FID value. Run this command
to submit a job to generate an image using this model:
sbatch job_stylegan3-t_gen_images.sh
job_stylegan3-t_gen_images.sh can be located here.
After studying the training results and images generated by a trained model. Generated images are not good enough for brainstorming new Bliss symbols. The decision is not to continue explore this model.