You can either run the respective files in an interactive window, e.g. in VS Code or via commandline: e.g.
ipython 02_GLVM_paper_figures.py
Prior to running any of the experiments, first generate the GLVM training, test and validation dataset, that will then be used when running ../scripts/run_GLVM.py
.
Run the ipython files in the following order:
- generate the dataset using
00_GLVM_generate_dataset.py
- start the actual training run by starting the bash script
bash run_GLVM_many_seeds.sh
in thebash
folder or simply via runningpython scripts/run_GLVM.py
from the base directory. - aggegrate the data across many runs using
01_GLVM_data_aggregation.py
- Finally, you can run the paper analysis with
02_GLVM_paper_figures.py
To gain an intuition for the steps required when training masked VAEs, see 03_GLVM_example_masked_VAE.ipynb
.
Note: Scripts for training the VAEs and generating the figures and download links to the data will come soon!