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- collect_games_batch(): run N games in parallel with single batched forward pass per step
- evaluate_vs_greedy_batch(): batched evaluation replacing sequential eval
- Add --collect_batch CLI arg for configurable parallel game count
- Use torch.inference_mode() for faster collection
- Update Colab notebook: GPU info, --collect_batch, log download cell
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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- README: document current game rules (SWAP inheritance, free draw, Q removal)
- README: add versus.py usage, training features (warmup, CSV log, CPU/GPU)
- Colab: update training commands, add log display, fix eval device
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Clone → train on GPU → download or push model back to GitHub.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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