Code for the Discriminative Regularization for Generative Models paper.
Set up your ~/.fuelrc file:
$ echo "data_path: \"<MY_DATA_PATH>\"" > ~/.fuelrcGo to <MY_DATA_PATH>:
$ cd <MY_DATA_PATH>Download the SVHN format 2 dataset:
$ fuel-download svhn 2
$ fuel-convert svhn 2
$ fuel-download svhn 2 --clearDownload the CIFAR-10 dataset:
$ fuel-download cifar10
$ fuel-convert cifar10
$ fuel-download cifar10 --clearDownload the CelebA dataset:
$ fuel-download celeba
$ fuel-convert celeba 64
$ fuel-download celeba --clearMake sure you're in the repo's root directory.
Required for the SVHN and CIFAR10 models.
python scripts/download_vgg19Make sure you downloaded VGG19.
The SVHN experiment code will be published very soon.
Make sure you downloaded VGG19.
The CIFAR-10 experiment code will be published very soon.
Train the CelebA classifier:
$ THEANORC=theanorc python experiments/train_celeba_classifier.pyTrain a VAE without discriminative regularization:
$ THEANORC=theanorc python experiments/train_celeba_vae.pyTrain a VAE with discriminative regularization:
$ THEANORC=theanorc python experiments/train_celeba_vae.py --regularizeFine-tune the trained model:
$ THEANORC=theanorc scripts/adjust_population_statistics [trained_model.zip] [save_path.zip]e.g.
$ THEANORC=theanorc scripts/adjust_population_statistics \
celeba_vae_regularization.zip celeba_vae_regularization_adjusted.zipNote: If you run out of memory in training, a good workaround is to reduce the
training_batch_size and monitoring_batch_size.
$ THEANORC=theanorc scripts/sample [trained_model.zip]e.g.
$ THEANORC=theanorc scripts/sample celeba_vae_regularization_adjusted.zip
$ THEANORC=theanorc scripts/reconstruct [which_dataset] [trained_model.zip]e.g.
$ THEANORC=theanorc scripts/reconstruct celeba celeba_vae_regularization_adjusted.zip
$ THEANORC=theanorc scripts/interpolate [which_dataset] [trained_model.zip]e.g.
$ THEANORC=theanorc scripts/interpolate celeba celeba_vae_regularization_adjusted.zip
Note: All evaluation scripts use ipython. But this behavior can be overridden by explicitly using python on the command line along with a save path. For example:
THEANORC=theanorc python scripts/sample --save-path sample_no_reg.png celeba_vae_no_regularization.zip
$ THEANORC=theanorc scripts/compute_nll_approximation [which_dataset] [trained_model.zip]Note: this takes a long time.