{
  "schemaVersion": 1,
  "lessonId": "welcome-cpu",
  "contentHash": "733a1d70e7c11d1340a2a478102aed48eef83dc5f8dc9679741d851a71426806",
  "rendererHash": "a1bd5b648f4731ae5d5f0a24811c2540d1a0a132149ce589d17c4113509cbedf",
  "kind": "executed",
  "generatedAt": "2026-10-20T10:45:06.292248+00:00",
  "provenance": "recorded_cpu_computation",
  "environment": {
    "backend": "cpu",
    "deviceCount": 4,
    "jax": "0.9.2",
    "numpy": "2.4.4",
    "matplotlib": "3.10.8"
  },
  "stdout": "JAX version: 0.9.2\nCPU devices: 4\nDevice 0 index (slice(0, 1, None), slice(None, None, None)) values [[0. 1.]]\nDevice 1 index (slice(1, 2, None), slice(None, None, None)) values [[2. 3.]]\nDevice 2 index (slice(2, 3, None), slice(None, None, None)) values [[4. 5.]]\nDevice 3 index (slice(3, 4, None), slice(None, None, None)) values [[6. 7.]]\nGlobal shape: (4, 2) result: [[1.0, 3.0], [5.0, 7.0], [9.0, 11.0], [13.0, 15.0]]\n",
  "data": {
    "kind": "heatmap",
    "values": [
      [
        0,
        0
      ],
      [
        1,
        1
      ],
      [
        2,
        2
      ],
      [
        3,
        3
      ]
    ],
    "unit": "logical CPU device ID",
    "rows": [
      "row 0",
      "row 1",
      "row 2",
      "row 3"
    ],
    "columns": [
      "feature 0",
      "feature 1"
    ]
  }
}