{
  "schemaVersion": 1,
  "lessonId": "performance-03",
  "contentHash": "8035a6f01d72cddc68632f648e4e09b96b1e34f69f29a1d0bd99144f3f418f5f",
  "executedAt": "2026-10-20T10:47:37.536684+00:00",
  "environment": {
    "backend": "cpu",
    "deviceCount": 1,
    "python": "3.14.3",
    "jax": "0.9.2",
    "numpy": "2.4.4",
    "matplotlib": "3.10.8"
  },
  "stdout": "Trace directory: /private/var/folders/mp/_mq7srqx2y10p5nhjz9m7hj40000gn/T/jax-course-trace-l3tdro07\n{\n  \"input_wait_us\": [\n    1263,\n    1253,\n    1269,\n    1271\n  ],\n  \"model_and_wait_us\": [\n    108,\n    137,\n    74,\n    140\n  ],\n  \"step_us\": [\n    1393,\n    1406,\n    1354,\n    1423\n  ]\n}\nFour named steps verified; host annotations are not isolated device kernels.\nTrace directory: /private/var/folders/mp/_mq7srqx2y10p5nhjz9m7hj40000gn/T/jax-course-trace-g8x32sim\n{\n  \"input_wait_us\": [\n    1263,\n    1279,\n    1265,\n    1275\n  ],\n  \"model_and_wait_us\": [\n    82,\n    136,\n    62,\n    122\n  ],\n  \"step_us\": [\n    1350,\n    1429,\n    1335,\n    1407\n  ]\n}\nFour named steps verified; host annotations are not isolated device kernels.\nUnattributed outer time, microseconds: [5, 14, 8, 10]\nWrong double-counted totals: [2695, 2844, 2662, 2804]\n{'minimum_ms': 0.062, 'median_ms': 0.10200000000000001, 'maximum_ms': 0.136}\nHypothetical union: 12 microseconds; summed duration: 19.\nPASS: performance-03\n",
  "notebookCells": [
    {
      "sourceHash": "39d5338b3ee681b065f5bcdfbfb7f394f84bb97e39b84272e93d192b79a7cfa9",
      "outputs": []
    },
    {
      "sourceHash": "6150a8cc46de875b6651dfd996e50b468c6374edfae2d3d9c997050f7a0d1621",
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Trace directory: /private/var/folders/mp/_mq7srqx2y10p5nhjz9m7hj40000gn/T/jax-course-trace-h9f0ujkm\n",
            "{\n",
            "  \"input_wait_us\": [\n",
            "    1264,\n",
            "    1283,\n",
            "    1262,\n",
            "    1258\n",
            "  ],\n",
            "  \"model_and_wait_us\": [\n",
            "    83,\n",
            "    150,\n",
            "    50,\n",
            "    83\n",
            "  ],\n",
            "  \"step_us\": [\n",
            "    1356,\n",
            "    1453,\n",
            "    1318,\n",
            "    1345\n",
            "  ]\n",
            "}\n",
            "Four named steps verified; host annotations are not isolated device kernels.\n"
          ]
        }
      ]
    },
    {
      "sourceHash": "3b0879708af5f068c79cd7d10dcf7f3da1025a6e260907ed6ad555360b8d383e",
      "outputs": []
    },
    {
      "sourceHash": "a4f49e8af969d44ce725ec8ec6bf5da3b4d85faa8d9d47ccded8665cd5b3ce27",
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Trace directory: /private/var/folders/mp/_mq7srqx2y10p5nhjz9m7hj40000gn/T/jax-course-trace-wb1u_1nc\n",
            "{\n",
            "  \"input_wait_us\": [\n",
            "    1269,\n",
            "    1266,\n",
            "    1266,\n",
            "    1265\n",
            "  ],\n",
            "  \"model_and_wait_us\": [\n",
            "    82,\n",
            "    117,\n",
            "    76,\n",
            "    46\n",
            "  ],\n",
            "  \"step_us\": [\n",
            "    1371,\n",
            "    1402,\n",
            "    1350,\n",
            "    1315\n",
            "  ]\n",
            "}\n",
            "Four named steps verified; host annotations are not isolated device kernels.\n"
          ]
        }
      ]
    },
    {
      "sourceHash": "112f7a1394bf97cecb2c586d491a647098322ae27612b9eef430a9efba477b98",
      "outputs": []
    },
    {
      "sourceHash": "25df6d662f9d3f0c4e984c6a201f79fa0cfd7a2633dc4b0773dfba6c2dd4ee6c",
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "image/png": "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",
            "text/plain": [
              "Executed Matplotlib figure"
            ]
          }
        }
      ]
    },
    {
      "sourceHash": "734f4008927c881a1fdc389f3e4c85845c48f92dea0c491c4416134e68ada554",
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Unattributed outer time, microseconds: [20, 19, 8, 4]\n",
            "Wrong double-counted totals: [2722, 2785, 2692, 2626]\n"
          ]
        }
      ]
    },
    {
      "sourceHash": "58ba93ef233188772daa150c317026276b188f367859290cb5a859b210863438",
      "outputs": []
    },
    {
      "sourceHash": "58a351944c99fd974430cab404b309858cb4bfb551cfb2b1ab49166baaff7af8",
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'minimum_ms': 0.046, 'median_ms': 0.079, 'maximum_ms': 0.117}\n"
          ]
        }
      ]
    },
    {
      "sourceHash": "a3b580713624d955747a68f3cd3347715c23f6c643de63c8b7adfb2fa717405e",
      "outputs": []
    },
    {
      "sourceHash": "6ba15124e99340aa941110a549b2299a568cb6983a9bfcd96fc418cec179e518",
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Hypothetical union: 12 microseconds; summed duration: 19.\n"
          ]
        }
      ]
    }
  ],
  "scope": "Recorded instructor reference run; all script assertions and notebook code cells passed. No accelerator performance claim."
}
