Package requirements for running the code:

• Pytorch
• TensorBoardX
• rdkit
• numpy
• matplotlib

File Navigator:

GAN_selfies:
- 2RGSMILES_QM9.txt : Dearomatized QM9 dataset (selfies representation, from alphabet described in the main text (symbols shortened for simplicity))
- GAN.py: Code for running the generative adversarial network
- one_hot_converter.py: Code for creating one-hot-encodings of molecular strings
- adjusted_selfies_fcts.py: SMILES to SELFIES conversion file
- GPlus2S.py: SMILES to SELFIES conversion file
- translate.py: General helper functions file

GAN_smiles:
- GAN.py: Code for running the generative adversarial network
- one_hot_converter.py: Code for creating one-hot-encodings of molecular strings
- smiles_qm9.txt: Dearomatized QM9 dataset (smiles representation)

How to Run the code:?

Step1: cd inside either 'GAN_selfies' or 'GAN_smiles' depending on which type of molecular representation you would like to run the GAN

Step2: run ./GAN.
The code will automatically detect the availability of a GPU on your device, and run multiple models with different hyperparameters