Code Repo for the paper: 3D Information Augmentation with Canonical Correlation Analysis##

NeurIPS 2022 LSC for PCQM4Mv2

1. Dataset Preparation

Make sure that you have downloaded the dataset PCQM4Mv2 in advance before you begin to process the data (Quick).

cd data
python dataset.py

Hopefully this will generate the files within the processed folder under pcqm4m-v2 folder :) The processing time depends on your CPU. For example, the Intel 9 10980HK will spend approxmiately 30:00 processing the data.

2. Training process

main train.py file is located in the model folder. Begin training by chaning the current folder to bash and then run train.py.

cd model
python train.py

Hopefully this will generate several checkpoints for Canonical (pre-training) process and downstreaming training process.

3. Visualization

To be continue