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{"type":"item.completed","item":{"id":"item_2","type":"agent_message","text":"```python\nimport numpy as np\nfrom scipy.linalg import svdvals\nfrom threadpoolctl import threadpool_limits\nthreadpool_limits(limits=2)\n\ndef stats(a):\n    a = np.asarray(a, dtype=np.float64)\n    return (np.linalg.norm(a), np.mean(a), np.std(a), np.min(a), np.max(a))\n\nprint(\"Available weights:\", sorted(W))\nprint(\"\\nLAYER NORMS: name, norm, mean, std, min, max; largest deviations from initialization\")\nfor l in range(4):\n    for name in [\"ln1_w\", \"ln1_b\", \"ln2_w\", \"ln2_b\"]:\n        a = np.asarray(W[f\"{name}.{l}\"], dtype=np.float64)\n        baseline = 1.0 if name.endswith(\"_w\") else 0.0\n        ix = np.argsort(np.abs(a - baseline))[-8:][::-1]\n        print(f\"{name}.{l}\", np.round(stats(a), 5),\n              [(int(i), round(float(a[i]), 5)) for i in ix])\n\nprint(\"\\nMATRIX SPECTRA: name, Frobenius norm, top 6 singular values, stable rank\")\nfor l in range(4):\n    for name in [\"W_q\", \"W_k\", \"W_v\", \"W_o\", \"W_fc\", \"W_proj\"]:\n        a = np.asarray(W[f\"{name}.{l}\"], dtype=np.float64)\n        s = svdvals(a)\n        print(f\"{name}.{l}\", round(np.linalg.norm(a), 4),\n              np.round(s[:6], 4), round(np.sum(s*s)/(s[0]*s[0]), 3))\n\nprint(\"\\nHEAD WEIGHT GEOMETRY\")\nprint(\"QK = W_q[head].T @ W_k[head]; OV = W_o[:,head] @ W_v[head].\")\nprint(\"Each line: ||Q||,||K||,||V||,||O||; QK top 5 SV, stable rank, trace/norm, symmetric-energy fraction; OV equivalents.\")\nfor l in range(4):\n    for j in range(6):\n        sl = slice(64*j, 64*(j+1))\n        q, k, v = [np.asarray(W[f\"W_{n}.{l}\"][sl], dtype=np.float64) for n in [\"q\",\"k\",\"v\"]]\n        o = np.asarray(W[f\"W_o.{l}\"][:, sl], dtype=np.float64)\n        vals = []\n        for a in [q.T @ k, o @ v]:\n            s = svdvals(a)\n            norm = np.linalg.norm(a)\n            vals.append((np.round(s[:5], 3).tolist(),\n                         round(np.sum(s*s)/(s[0]*s[0]), 3),\n                         round(np.trace(a)/norm, 3),\n                         round(np.linalg.norm((a+a.T)/2)**2/norm**2, 3)))\n        print(f\"L{l}H{j}\", np.round([np.linalg.norm(a) for a in [q,k,v,o]], 3),\n              \"QK\", vals[0], \"OV\", vals[1])\n```"}}
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