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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_3.npz\",**{n:load(n) for n in names})\n\nrevision=r'''\nimport numpy as np\n_base={}\nexec(open(\"/work/design_v3.py\").read(),_base)\n\ndef construct(parameters=None):\n    changes=dict(scale=2.8, eye=25.0, capture_exemption=1.0)\n    if parameters:\n        changes.update(parameters)\n    t,p=_base[\"construct\"](changes)\n    W=t[\"L6.W\"]; b=t[\"L6.b\"]; OW=t[\"out.W\"]\n    def u(c,i): return c*81+i\n    for i in range(81):\n        # Merge the two nonnegative tactical accumulators, freeing an\n        # entire channel for explicit true-eye preservation.\n        W[:,u(1,i)]+=W[:,u(2,i)]\n        b[u(1,i)]+=b[u(2,i)]\n        W[:,u(2,i)]=0\n        b[u(2,i)]=0\n\n        r,c=divmod(i,9)\n        ns=[rr*9+cc for rr,cc in\n            ((r-1,c),(r+1,c),(r,c-1),(r,c+1))\n            if 0<=rr<9 and 0<=cc<9]\n        ds=[rr*9+cc for rr,cc in\n            ((r-1,c-1),(r-1,c+1),(r+1,c-1),(r+1,c+1))\n            if 0<=rr<9 and 0<=cc<9]\n        b[u(2,i)]=1-len(ns)\n        for j in ns:\n            W[u(0,j),u(2,i)]=1\n        for j in ds:\n            W[u(1,j),u(2,i)]=-1 if min(r,c,8-r,8-c)==0 else -0.5\n        OW[u(2,i),i]=-p[\"scale\"]*p[\"eye\"]\n    return t,p\n'''\nopen(\"/work/design_v4.py\",\"w\").write(revision)\nns={}\nexec(revision,ns)\ntensors,p=ns[\"construct\"]()\nfor name,array in tensors.items():\n    save(name,array)\njson.dump(p,open(\"/work/parameters.json\",\"w\"),indent=2)\nprint(\"Saved revision 4: explicit eye protection, less permissive\")\nprint(\"capture exemptions, and more decisive sampling.\")\n```\n"}}
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