)]}'
{
  "commit": "806af056feb22a1236baca247b4f4b6e1ea911e5",
  "tree": "122d9d77bcc1fb89896b8a0be99f297f52398e58",
  "parents": [
    "41958f3fcc6e62aebabb4de8360ed28910d903ca"
  ],
  "author": {
    "name": "Pez Firoozfam",
    "email": "pezhman@google.com",
    "time": "Mon Mar 23 20:35:24 2026 +0000"
  },
  "committer": {
    "name": "Pez Firoozfam",
    "email": "pezhman@google.com",
    "time": "Tue Apr 07 23:16:48 2026 -0700"
  },
  "message": "Add support for maximum matrix sizes to TinySolver.\n\nThis change restructures the `TinySolver` template and its associated\nadapters (`AutoDiff` and `CostFunction`) to make maximum sizing\nattributes first-class parameters. This enables the entire `TinySolver`\nstack to be used in restricted environments (e.g., small MCUs) without\ndynamic memory allocation, even when the number of residuals or\nparameters is only known at runtime (`Eigen::Dynamic`).\n\nSpecifically:\n- Adds `kMaxResiduals` and `kMaxParameters` template parameters to\n  `TinySolver`.\n- Updated `TinySolverAutoDiffFunction` and\n  `TinySolverCostFunctionAdapter` to support optional maximum size\n  template parameters for their internal buffers.\n- The new API maintains backward compatibility for existing users by\n  defaulting to the sizes defined in the `Function`\u0027s enums.\n- This structure also supports reducing code bloat by allowing\n  `TinySolver` to be instantiated with an abstract base class, using\n  dynamic dispatch for cost function evaluation.\n\nNew test cases for `TinySolver` and its adapters verify the\nzero-allocation behavior and the unified API flexibility.\n\nChange-Id: Ic6f43984d384dbe71472b31c5ebd2b538d61f19d\n",
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