Evidential deep learning and other feature requests

[schinto]

Dear Graphormer authors,

thanks for this great piece of software!
I have some feature requests.

Can you please add the functionality for evidential deep learning?
See article:
ACS Cent. Sci. 2021, 7, 8, 1356–1367

Please add the 10 smaller datasets from MoleculeNet to the benchmarks. They are ogbg-moltox21, ogbg-molbace, ogbg-molbbbp, ogbg-molclintox, ogbg-molmuv, ogbg-molsider, and ogbg-moltoxcast for (multi-task) binary classification, and ogbg-molesol, ogbg-molfreesolv, and ogbg-mollipo for regression.
See https://ogb.stanford.edu/docs/graphprop/

Please add functionality for molecular representation pre-training via attribute masking
See Strategies for Pre-training Graph Neural Networks

Please add metrics described in the Regression Metrics Guide

As the manual selection of parameters for a graph neural network is difficult, please add support
for some of the automated machine learning techniques.
See for example techniques described in AutoGL

Many thanks.