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{"type":"item.completed","item":{"id":"item_1","type":"agent_message","text":"```python\nimport numpy as np\nfrom threadpoolctl import threadpool_limits\nthreadpool_limits(4)\n\ndef summary(a):\n    return \"norm=%.3f mean=%.5f std=%.5f min=%.4f max=%.4f\" % (\n        np.linalg.norm(a), a.mean(), a.std(), a.min(), a.max())\n\nfor l in range(4):\n    print(\"\\nLAYER\", l)\n    for name in [\"ln1_w\", \"ln1_b\", \"ln2_w\", \"ln2_b\", \"W_q\", \"W_k\", \"W_v\", \"W_o\", \"W_fc\", \"W_proj\"]:\n        print(name, summary(W[f\"{name}.{l}\"]))\n    print(\"head: Qnorm Knorm Vnorm Onorm | QK sv(top6), top1_energy, symmetry, trace/norm | OV sv(top4), trace/norm\")\n    for j in range(6):\n        s = slice(j*64, (j+1)*64)\n        q = W[f\"W_q.{l}\"][s].astype(float)\n        k = W[f\"W_k.{l}\"][s].astype(float)\n        v = W[f\"W_v.{l}\"][s].astype(float)\n        o = W[f\"W_o.{l}\"][:, s].astype(float)\n        g = W[f\"ln1_w.{l}\"]\n        A = (q*g).T @ (k*g) / 8\n        B = o @ (v*g)\n        sa = np.linalg.svd(A, compute_uv=False)[:64]\n        sb = np.linalg.svd(B, compute_uv=False)[:64]\n        print(\"L%dH%d\" % (l,j),\n              np.round([np.linalg.norm(z) for z in [q,k,v,o]], 3),\n              \"|\", np.round(sa[:6],3), \"E1=%.3f sym=%.3f tr=%.3f\" %\n              (sa[0]**2/(sa@sa), np.sum(A*A.T)/np.sum(A*A), np.trace(A)/np.linalg.norm(A)),\n              \"|\", np.round(sb[:4],3), \"tr=%.3f\" % (np.trace(B)/np.linalg.norm(B)))\n```\n"}}
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