{
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  "lessonId": "performance-02",
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  "kind": "executed",
  "generatedAt": "2026-10-20T10:45:59.629728+00:00",
  "provenance": "recorded_cpu_computation",
  "environment": {
    "backend": "cpu",
    "deviceCount": 1,
    "jax": "0.9.2",
    "numpy": "2.4.4",
    "matplotlib": "3.10.8"
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  "stdout": "{\n  \"jax\": \"0.9.2\",\n  \"backend\": \"TFRT_CPU_0\",\n  \"calls\": [\n    {\n      \"label\": \"initial signature\",\n      \"shape\": [\n        8\n      ],\n      \"dtype\": \"float32\",\n      \"observed_trace_delta\": 1,\n      \"result\": 140.0\n    },\n    {\n      \"label\": \"same signature changed data\",\n      \"shape\": [\n        8\n      ],\n      \"dtype\": \"float32\",\n      \"observed_trace_delta\": 0,\n      \"result\": 204.0\n    },\n    {\n      \"label\": \"same signature changed dynamic gain\",\n      \"shape\": [\n        8\n      ],\n      \"dtype\": \"float32\",\n      \"observed_trace_delta\": 0,\n      \"result\": 560.0\n    },\n    {\n      \"label\": \"different input shape\",\n      \"shape\": [\n        12\n      ],\n      \"dtype\": \"float32\",\n      \"observed_trace_delta\": 1,\n      \"result\": 506.0\n    }\n  ],\n  \"python_trace_events\": [\n    {\n      \"shape\": [\n        8\n      ],\n      \"dtype\": \"float32\"\n    },\n    {\n      \"shape\": [\n        12\n      ],\n      \"dtype\": \"float32\"\n    }\n  ]\n}\n",
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}