Refactor sparse Cholesky factorization into symbolic and numeric phases.

The new symbolic function is a generalization of the function it replaces. In this CL it takes two unused temp arrays. The actual change in behavior happens in the followup.

New benchmark test output below ("L" is 2 humanoids and 100 free objects, "XL" is 100 humanoids). Note that `symbolic` is only ever called once per Newton iteration, while `numeric` is sometimes called multiple times (when the rank-1 update fails), hence timing them separately is valuable.

```
Benchmark               Time(ns)        CPU(ns)     Iterations
--------------------------------------------------------------
BM_old_L_mean              84382          84703          19547  11.807k items/s
BM_symbolic_L_mean         16345          16381          88414  61.055k items/s
BM_numeric_L_mean          10986          10994         120000  90.999k items/s
BM_old_XL_mean           1241208        1244212           1200  803.924 items/s
BM_symbolic_XL_mean       130917         131042          12720  7.631k items/s
BM_numeric_XL_mean         77004          76767          21116  13.029k items/s
```

PiperOrigin-RevId: 846704054
Change-Id: Ib0c365724d63bf2b81606ca5353756a6496c3a26

src/engine/engine_solver.c

@@ -1558,16 +1558,14 @@ static void MakeHessian(mjData* d, mjCGContext* ctx) {
                         HT_rownnz, HT_rowadr, HT_colind, NULL,
                         ctx->H_rownnz, ctx->H_rowadr, ctx->H_colind);
 
-    // count total and row non-zeros of reverse-Cholesky factor L
-    ctx->nL = mju_cholFactorCount(ctx->L_rownnz, HT_rownnz, HT_rowadr, HT_colind, nv, d);
+    // count total and row non-zeros of reverse-Cholesky factors L and LT
+    int* LT_rownnz_temp = mjSTACKALLOC(d, nv, int);
+    int* LT_rowadr_temp = mjSTACKALLOC(d, nv, int);
+    ctx->nL = mju_cholFactorSymbolic(NULL, ctx->L_rownnz, ctx->L_rowadr, NULL,
+                                     LT_rownnz_temp, LT_rowadr_temp, NULL,
+                                     HT_rownnz, HT_rowadr, HT_colind, nv, d);
     mj_freeStack(d);
 
-    // compute L row addresses: rowadr = cumsum(rownnz)
-    ctx->L_rowadr[0] = 0;
-    for (int r=1; r < nv; r++) {
-      ctx->L_rowadr[r] = ctx->L_rowadr[r-1] + ctx->L_rownnz[r-1];
-    }
-
     // allocate L_colind, L, Lcone
     ctx->L_colind = mjSTACKALLOC(d, ctx->nL, int);
     ctx->L = mjSTACKALLOC(d, ctx->nL, mjtNum);