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name: open-alpha-tensor description: "Guides OpenAlphaTensor training, configuration, checkpointing, and troubleshooting for matrix-multiplication search runs." disable-model-invocation: true metadata: disco-role: operating license: NO_LICENSE

OpenAlphaTensor

Use this sub-skill when the user wants to train OpenAlphaTensor, tune the JSON/CLI configuration, manage checkpoints, or understand the outputs written by the training pipeline.

Triggers

• Run python main.py or call train_alpha_tensor(...).
• Map config.json keys to the public API.
• Tune checkpoint, save, or output directories.
• Debug optimizer selection or device placement.

Read next

• references/api-reference.md for the public training function and grouped parameters.
• references/configuration.md for JSON and CLI configuration keys.
• references/workflows.md for the training, checkpoint, and save flow.
• references/troubleshooting.md for long-run, path, and checkpoint recovery.
• scripts/open_alpha_tensor_probe.py for a safe signature and config-validation check.

What to include

• The train_alpha_tensor(...) entry point.
• CLI-to-API mapping from main.py.
• JSON config defaults and runtime overrides.
• Checkpoint and save-directory behavior.
• Device and optimizer selection.

What to exclude

• Long training runs by default.
• Generated data or artifact downloads.
• Source-repo path links in runtime guidance.

Quick decision rule

If the user asks “how do I launch or tune OpenAlphaTensor?”, start here. If the request is only about the underlying matrix-search paper or benchmark results, use the references rather than the script.