OGB

Use this skill for the Open Graph Benchmark package when the task is about loading OGB datasets, choosing an evaluator, converting molecules or code into OGB graphs, or packaging a new OGB-style dataset.

Read this skill when

• The request names ogb, ogbg-*, ogbn-*, ogbl-*, PCQM4M, MAG240M, WikiKG90M, or DatasetSaver.
• The task asks for GraphPropPredDataset, NodePropPredDataset, LinkPropPredDataset, PCQM4MDataset, PCQM4Mv2Dataset, MAG240MDataset, WikiKG90MDataset, or the matching evaluator.
• The task mentions smiles2graph, py2graph, meta_dict.pt, mapping/, split_dict.pt, test-dev, test-challenge, or OGB submission files.
• The task asks for PyG or DGL dataset wrappers and the corresponding backend packages are installed.

Install

python -m pip install -e .

If you need the molecular helper, install rdkit as well. If you need the PyG or DGL wrapper classes, install the matching optional backend package too.

Start here

1. Read references/api-overview.md for the public class map and the common loader/evaluator shapes.
2. Read references/installation.md for the package install command and the optional backend notes.
3. Read references/dataset-catalog.md when you need the exact dataset names or metrics.
4. Read references/troubleshooting.md when imports fail, downloads are interrupted, or shapes do not match.

Route by task family

• Use sub-skills/graph-property-prediction/SKILL.md for ogbg-*, molecular graph workflows, smiles2graph, and ogbg-code2.
• Use sub-skills/node-property-prediction/SKILL.md for ogbn-* datasets and node-level evaluators.
• Use sub-skills/link-property-prediction/SKILL.md for ogbl-* datasets, ranking metrics, and knowledge-graph completion.
• Use sub-skills/lsc-benchmarks/SKILL.md for PCQM4M, MAG240M, WikiKG90M, submission files, and large-scale benchmark notes.
• Use sub-skills/dataset-contribution/SKILL.md for DatasetSaver and OGB-compatible dataset packaging.

Quick install check

After installing the package, run the bundled smoke helper:

python scripts/check-install.py

If you need the molecule helper, also run:

python scripts/smiles2graph-smoke.py

What this skill does not do

• It does not tell you to run the original repository's heavy training examples as the runtime skill.
• It does not depend on the source checkout remaining available once the skill is generated.
• It does not treat the vendored WikiKG90M external framework tree as bundled runtime content.

Useful bundled helpers

• scripts/check-install.py: verifies the installed package, optional backend presence, and core imports.
• scripts/list-datasets.py: prints the dataset catalog from the installed package metadata.
• scripts/smiles2graph-smoke.py: runs a tiny molecule-to-graph smoke check.

Provenance and routing

Read references/repo-provenance.md to see which repo state this skill was distilled from, and references/repo-routing-metadata.json for the router scenario metadata used during import.