Code for PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction

Environment

We used the following Python packages for core development. We tested on Python 3.7.

- pytorch 1.7.0
- torch-geometric 1.7.0

MolecularNet

Datasets

Tox21, SIDER, MUV and ToxCast are previously downloaded from SNAP. You can download the data here, unzip the file and put the resultant ``muv, sider, tox21, and toxcast" in the data folder.

Experiments

To run the experiments, use the command (please check and tune the hyper-parameters in parser.py):

python main.py

quick reproduce results on Tox-21 10-shot:

bash script_train.sh

FS-MOL

Get dataset and pipeline from https://github.com/Wenlin-Chen/ADKF-IFT#

Copy "./graph_feature_extractor.py" and "./gnn.py" into "ADKF-IFT/fs_mol/modules". Copy "./pacia_adkt_train.py" and "./pacia_adkt_test.py" into "ADKF-IFT/fs_mol". Copy "./pacia_adkt_utils.py" into "ADKF-IFT/fs_mol/utils"

Run "pacia_adkt_train.py" and "pacia_adkt_test.py" following instructions in "ADKF-IFT/README.md".