{
  "schemaVersion": 1,
  "lessonId": "recovery-05",
  "contentHash": "53af93b1c6c37ad3ae60af050b3fbce1aec596ad453fe6c06ad32042e883b6b8",
  "executedAt": "2026-10-20T10:46:54.698510+00:00",
  "environment": {
    "backend": "cpu",
    "deviceCount": 1,
    "python": "3.14.3",
    "jax": "0.9.2",
    "numpy": "2.4.4",
    "matplotlib": "3.10.8"
  },
  "stdout": "Checkpoint workspace: /var/folders/mp/_mq7srqx2y10p5nhjz9m7hj40000gn/T/jax-async-lesson-9ibeu4bo\n{\n  \"save_call_seconds\": 0.0035320832394063473,\n  \"remaining_work_and_wait_seconds\": 0.017399583011865616,\n  \"accepted_step\": 1,\n  \"live_step\": 2\n}\nUnpublished step 2 exists; application recovery still selects verified step 1.\nCheckpoint workspace: /var/folders/mp/_mq7srqx2y10p5nhjz9m7hj40000gn/T/jax-async-lesson-xq01n_nx\n{\n  \"save_call_seconds\": 0.0024104579351842403,\n  \"remaining_work_and_wait_seconds\": 0.009226541966199875,\n  \"accepted_step\": 1,\n  \"live_step\": 2\n}\nUnpublished step 2 exists; application recovery still selects verified step 1.\nExpected background failure surfaced: injected finalization callback failure\nStep two verified and accepted; next transition agrees.\nMissing target rejected; accepted checkpoint unchanged.\nPASS: recovery-05\n",
  "notebookCells": [
    {
      "sourceHash": "0dcc4f3bb149a884182f537fcfa52f2cfe36ab19536027a9b4725c28b77ecf46",
      "outputs": []
    },
    {
      "sourceHash": "cc09625a3d1884683201fde08fa3e04c770e0a04cde85656d17a36a082d47f16",
      "outputs": []
    },
    {
      "sourceHash": "5809d538fea550451089375fb5fa091598587397f38e39cf8b7550c4957ff338",
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Checkpoint workspace: /var/folders/mp/_mq7srqx2y10p5nhjz9m7hj40000gn/T/jax-async-lesson-uymdp95k\n",
            "{\n",
            "  \"save_call_seconds\": 0.0035863746888935566,\n",
            "  \"remaining_work_and_wait_seconds\": 0.016371500212699175,\n",
            "  \"accepted_step\": 1,\n",
            "  \"live_step\": 2\n",
            "}\n",
            "Unpublished step 2 exists; application recovery still selects verified step 1.\n"
          ]
        }
      ]
    },
    {
      "sourceHash": "f93dc5604fd5502c6f580d8255891bd01a9022870220599716c0bd03b2f4f16b",
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Checkpoint workspace: /var/folders/mp/_mq7srqx2y10p5nhjz9m7hj40000gn/T/jax-async-lesson-tye9awlc\n",
            "{\n",
            "  \"save_call_seconds\": 0.002461958210915327,\n",
            "  \"remaining_work_and_wait_seconds\": 0.0092058340087533,\n",
            "  \"accepted_step\": 1,\n",
            "  \"live_step\": 2\n",
            "}\n",
            "Unpublished step 2 exists; application recovery still selects verified step 1.\n"
          ]
        }
      ]
    },
    {
      "sourceHash": "8f926cf6730c8a62c2d616594b5c92a0cfa8d51af2ab2e554d4b54a0b2d13435",
      "outputs": []
    },
    {
      "sourceHash": "25df6d662f9d3f0c4e984c6a201f79fa0cfd7a2633dc4b0773dfba6c2dd4ee6c",
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
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",
            "text/plain": [
              "Executed Matplotlib figure"
            ]
          }
        }
      ]
    },
    {
      "sourceHash": "15d785502495cf7afd39b11f48e4d9d2f56ae08e5c7f9cdcf3a9486b77962e37",
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Expected background failure surfaced: injected finalization callback failure\n"
          ]
        }
      ]
    },
    {
      "sourceHash": "e7852da2712b40bee9e98f915d3c043eae0883f885a6360cdeb47b656cc39451",
      "outputs": []
    },
    {
      "sourceHash": "193d5beb3e27d975d6d537f18ba541eb582802ed3226dc4deb6bc24d318b2bce",
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Step two verified and accepted; next transition agrees.\n"
          ]
        }
      ]
    },
    {
      "sourceHash": "be097e4cef609c684e9c6d1767804298108dcb948f81fb702f2904ec50c3d42b",
      "outputs": []
    },
    {
      "sourceHash": "45386a6cb99124e42081ad9ef69c57df0b5759ab3466d0b4e5b2224c29592fc0",
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Missing target rejected; accepted checkpoint unchanged.\n"
          ]
        }
      ]
    }
  ],
  "scope": "Recorded instructor reference run; all script assertions and notebook code cells passed. No accelerator performance claim."
}