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Testing the robustness of Graph Transformers.

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TODO: update README

Python environment setup with Conda

conda create -n gtr python=3.11
conda activate gtr

# install the version of pytorch that is compatible with your system
# e.g.:
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
# or for cpu only:
# conda install pytorch torchvision torchaudio cpuonly -c pytorch

conda install -c pyg pyg pytorch-sparse

conda install -c conda-forge yacs tensorboardx lightning torchmetrics performer-pytorch ogb wandb opt_einsum

pip install seml

# RDKit is required for OGB-LSC PCQM4Mv2 and datasets derived from it.  
# conda install openbabel fsspec rdkit -c conda-forge

conda clean --all

W&B logging

To use W&B logging, set wandb.use True and have a gtransformers entity set-up in your W&B account (or change it to whatever else you like by setting wandb.entity).

Unit tests

To run all unit tests, execute from the project root directory:

python -m unittest -v

Or specify a particular test module, e.g.:

python -m unittest -v unittests.test_eigvecs

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