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name: lsc-benchmarks description: "Routes OGB-LSC workflows for PCQM4M, MAG240M, WikiKG90M, and submission helpers." metadata: disco-role: operating disable-model-invocation: true license: MIT

LSC Benchmarks

Use this subskill for the OGB-LSC family: PCQM4M, PCQM4Mv2, MAG240M, WikiKG90M, WikiKG90Mv2, submission files, and evaluator smoke checks.

Use this subskill when

• The task names PCQM4M, PCQM4Mv2, MAG240M, WikiKG90M, WikiKG90Mv2, or OGB-LSC.
• The task asks for test-dev, test-challenge, submission filenames, or evaluator-specific smoke checks.
• The task mentions only_smiles, to_pyg_hetero_data, split_test, or checkpointed inference helpers.

First decisions

1. Read references/workflows.md for the dataset families and the main execution flow.
2. Read references/api-reference.md for the public class names and evaluator expectations.
3. Read references/submission.md when the task is about output filenames or submission shapes.
4. Read references/troubleshooting.md when a dataset is deprecated, a checkpoint is missing, or a shape assertion fails.
5. If you only need to verify evaluator shapes without downloading a dataset, run scripts/lsc-smoke.py.

Main workflow

• Decide which LSC dataset family the request targets.
• Check whether the request is a data-loading task, an evaluator task, or a submission-format task.
• Use only_smiles=True when you only need the molecular strings for the PCQM4M family.
• Use to_pyg_hetero_data() when you need a PyG hetero representation for MAG240M.
• Treat WikiKG90M as deprecated and prefer the v2 workflow for new work.

Common routing choices

• PCQM4M / PCQM4Mv2 -> molecular regression and submission helpers.
• MAG240M -> large heterogeneous node classification.
• WikiKG90M / WikiKG90Mv2 -> knowledge-graph completion and top-10 submission arrays.

Optional backend note

The LSC examples may rely on PyG, DGL, or external frameworks such as DGL-KE/SMORE. Those are optional or external to the core OGB package. If they are missing, keep the workflow to the core dataset and evaluator surface unless those extras are explicitly requested.

What not to do here

• Do not run the full heavyweight benchmark training loops as the runtime answer.
• Do not treat PCQM4M or WikiKG90M as preferred starting points for new work.
• Do not depend on the source checkout for the final skill content.

Related references

• ../../references/api-overview.md
• ../../references/dataset-catalog.md
• ../../references/troubleshooting.md