Fix evaluation metric of ogbg-molpcba

This release is mainly for changing the evaluation metric of ogbg-molpcba from PRC-AUC to Average Precision (AP). AP is shown to be more appropriate to summarize the non-convex nature of the Precision Recall Curve [1]. The leaderboard and our paper have been updated accordingly.

We also fix an issue and add a feature:

• Fixed an issue for saving a large library-agnostic data object. #48
• Added automatic version check feature so that users will get notified when the package version is outdated.

[1] Jesse Davis and Mark Goadrich. The relationship between precision-recall and roc curves. InInternational Conference on Machine Learning (ICML), pp. 233–240, 2006.

Minor fix and update

This release fixes bugs in a dataset, evaluator, and data loader.

• Duplicated edges in ogbn-mag are removed. The updated dataset will be downloaded and processed automatically as you run your script for ogbn-mag. #40
• Evaluators for ogbl-collab and ogbl-ddi are updated. Specifically, ogbl-collab now uses Hits@50, and ogbl-ddi now uses Hits@20.
• DGL data loader bug for ogbn-mag and ogbl-biokg is fixed. #36

Second major release

This is the second major release of OGB, in which we have curated many more exciting graph datasets, including heterogeneous graphs and a web-scale gigantic graph (100+ million nodes, 1+ billion edges).

First, we note that there is no change in the datasets released in version 1.1.1. Therefore, any experimental results obtained using 1.1.1 on the existing datasets are compatible to version 1.2.0.

In this new release, we have additionally released 5 new datasets listed below.

• ogbn-papers100M: Web-scale gigantic paper citation network.
• ogbn-mag: Heterogeneous academic graph.
• ogbl-biokg: Heterogeneous biomedical knowledge graph.
• ogbl-ddi: Drug-drug interaction network.
• ogbg-code: Source code Abstract Syntax Trees.

Automatic dataset update

OGB package can now automatically fetch the datasets if they have been updated.

First major release

First Major Release

This is the first major release of OGB.
A number of changes have been made to the datasets, which are summarized below.

1. Re-indexed all the nodes in the node/link datasets (The graphs remain essentially the same).
2. In dataset folders for all the datasets, added mapping/ directory that contains information to map node/edge/graph/label indices to real-world entities (e.g., mapping from nodes in PPA to unique protein identifiers, mapping from molecular graphs into the SMILES strings.)
3. Deleted the ogbn-proteins node features, and put them in the species variable.
4. Deleted ogbl-reviews datasets.
5. Added 4 datasets: ogbn-arxiv, ogbl-citation, ogbl-collab, ogbl-wikikg.
6. Renamed ogbg-ppi to ogbg-ppa.
7. Renamed ogbg-mol-hiv and ogbg-mol-pcba to ogbg-molhiv and ogbg-molpcba, respectively.
8. Changed the evaluation metric of imbalanced molecule dataset (e.g., pcba) from ROC-AUC to PRC-AUC.
9. Changed the get_split_edge() interface in LinkPropPredDataset. The downloaded dataset files are also changed accordingly.
10. Added num_classes attribute for multi-class classification datasets.

1.0.1

Minor Changes

OGB datasets can now be imported more conveniently, e.g.:

from ogb.graphproppred import GraphPropPredDataset
from ogb.graphproppred import PygGraphPropPredDataset
from ogb.graphproppred import DglGraphPropPredDataset

Note that this will throw an ImportError if OGB can not find installations of Pyg or DGL, respectively.