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{"type":"item.completed","item":{"id":"item_2","type":"agent_message","text":"```python\nimport numpy as np,json\nnames=[f\"L{k}.{s}\" for k in range(1,7) for s in (\"W\",\"b\")]+[\"out.W\",\"out.b\"]\nnp.savez_compressed(\"/work/version_19.npz\",**{n:load(n) for n in names})\n\narchive=np.load(\"/work/version_13.npz\")\nfor name in names:\n    save(name,archive[name])\n\nnamespace={}\nexec(open(\"/work/design_v13.py\").read(),namespace)\nconstructed,parameters=namespace[\"construct\"]()\nassert all(np.array_equal(constructed[n],archive[n]) for n in names)\njson.dump(parameters,open(\"/work/parameters.json\",\"w\"),indent=2)\nprint(\"Restored the archived revision 13 for an independent confirmation batch.\")\nprint(\"Its weights exactly match its analytic constructor.\")\n```\n"}}
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