Date: 2022-03-04T17:39:55+00:00

Actual source code: gpcglinesearch.c

      1: #include <petsc/private/taolinesearchimpl.h>
      2: #include <../src/tao/linesearch/impls/gpcglinesearch/gpcglinesearch.h>

      4: /* ---------------------------------------------------------- */

      6: static PetscErrorCode TaoLineSearchDestroy_GPCG(TaoLineSearch ls)
      7: {
      8:   PetscErrorCode     ierr;
      9:   TaoLineSearch_GPCG *ctx = (TaoLineSearch_GPCG *)ls->data;

     12:   VecDestroy(&ctx->W1);
     13:   VecDestroy(&ctx->W2);
     14:   VecDestroy(&ctx->Gold);
     15:   VecDestroy(&ctx->x);
     16:   PetscFree(ls->data);
     17:   return(0);
     18: }

     20: /*------------------------------------------------------------*/
     21: static PetscErrorCode TaoLineSearchView_GPCG(TaoLineSearch ls, PetscViewer viewer)
     22: {
     23:   PetscBool      isascii;

     27:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
     28:   if (isascii) {
     29:     PetscViewerASCIIPrintf(viewer," GPCG Line search");
     30:   }
     31:   return(0);
     32: }

     34: /*------------------------------------------------------------*/
     35: static PetscErrorCode TaoLineSearchApply_GPCG(TaoLineSearch ls, Vec x, PetscReal *f, Vec g, Vec s)
     36: {
     37:   TaoLineSearch_GPCG *neP = (TaoLineSearch_GPCG *)ls->data;
     38:   PetscErrorCode     ierr;
     39:   PetscInt           i;
     40:   PetscBool          g_computed=PETSC_FALSE; /* to prevent extra gradient computation */
     41:   PetscReal          d1,finit,actred,prered,rho, gdx;

     44:   /* ls->stepmin - lower bound for step */
     45:   /* ls->stepmax - upper bound for step */
     46:   /* ls->rtol     - relative tolerance for an acceptable step */
     47:   /* ls->ftol     - tolerance for sufficient decrease condition */
     48:   /* ls->gtol     - tolerance for curvature condition */
     49:   /* ls->nfeval   - number of function evaluations */
     50:   /* ls->nfeval   - number of function/gradient evaluations */
     51:   /* ls->max_funcs  - maximum number of function evaluations */

     53:   TaoLineSearchMonitor(ls, 0, *f, 0.0);

     55:   ls->reason = TAOLINESEARCH_CONTINUE_ITERATING;
     56:   ls->step = ls->initstep;
     57:   if (!neP->W2) {
     58:     VecDuplicate(x,&neP->W2);
     59:     VecDuplicate(x,&neP->W1);
     60:     VecDuplicate(x,&neP->Gold);
     61:     neP->x = x;
     62:     PetscObjectReference((PetscObject)neP->x);
     63:   } else if (x != neP->x) {
     64:     VecDestroy(&neP->x);
     65:     VecDestroy(&neP->W1);
     66:     VecDestroy(&neP->W2);
     67:     VecDestroy(&neP->Gold);
     68:     VecDuplicate(x,&neP->W1);
     69:     VecDuplicate(x,&neP->W2);
     70:     VecDuplicate(x,&neP->Gold);
     71:     PetscObjectDereference((PetscObject)neP->x);
     72:     neP->x = x;
     73:     PetscObjectReference((PetscObject)neP->x);
     74:   }

     76:   VecDot(g,s,&gdx);
     77:   if (gdx > 0) {
     78:      PetscInfo1(ls,"Line search error: search direction is not descent direction. dot(g,s) = %g\n",(double)gdx);
     79:     ls->reason = TAOLINESEARCH_FAILED_ASCENT;
     80:     return(0);
     81:   }
     82:   VecCopy(x,neP->W2);
     83:   VecCopy(g,neP->Gold);
     84:   if (ls->bounded) {
     85:     /* Compute the smallest steplength that will make one nonbinding variable  equal the bound */
     86:     VecStepBoundInfo(x,s,ls->lower,ls->upper,&rho,&actred,&d1);
     87:     ls->step = PetscMin(ls->step,d1);
     88:   }
     89:   rho=0; actred=0;

     91:   if (ls->step < 0) {
     92:     PetscInfo1(ls,"Line search error: initial step parameter %g< 0\n",(double)ls->step);
     93:     ls->reason = TAOLINESEARCH_HALTED_OTHER;
     94:     return(0);
     95:   }

     97:   /* Initialization */
     98:   finit = *f;
     99:   for (i=0; i< ls->max_funcs; i++) {
    100:     /* Force the step to be within the bounds */
    101:     ls->step = PetscMax(ls->step,ls->stepmin);
    102:     ls->step = PetscMin(ls->step,ls->stepmax);

    104:     VecCopy(x,neP->W2);
    105:     VecAXPY(neP->W2,ls->step,s);
    106:     if (ls->bounded) {
    107:       /* Make sure new vector is numerically within bounds */
    108:       VecMedian(neP->W2,ls->lower,ls->upper,neP->W2);
    109:     }

    111:     /* Gradient is not needed here.  Unless there is a separate
    112:        gradient routine, compute it here anyway to prevent recomputing at
    113:        the end of the line search */
    114:     if (ls->hasobjective) {
    115:       TaoLineSearchComputeObjective(ls,neP->W2,f);
    116:       g_computed=PETSC_FALSE;
    117:     } else if (ls->usegts) {
    118:       TaoLineSearchComputeObjectiveAndGTS(ls,neP->W2,f,&gdx);
    119:       g_computed=PETSC_FALSE;
    120:     } else {
    121:       TaoLineSearchComputeObjectiveAndGradient(ls,neP->W2,f,g);
    122:       g_computed=PETSC_TRUE;
    123:     }

    125:     TaoLineSearchMonitor(ls, i+1, *f, ls->step);

    127:     if (0 == i) {
    128:         ls->f_fullstep = *f;
    129:     }

    131:     actred = *f - finit;
    132:     VecCopy(neP->W2,neP->W1);
    133:     VecAXPY(neP->W1,-1.0,x);    /* W1 = W2 - X */
    134:     VecDot(neP->W1,neP->Gold,&prered);

    136:     if (PetscAbsReal(prered)<1.0e-100) prered=1.0e-12;
    137:     rho = actred/prered;

    139:     /*
    140:        If sufficient progress has been obtained, accept the
    141:        point.  Otherwise, backtrack.
    142:     */

    144:     if (actred > 0) {
    145:       PetscInfo(ls,"Step resulted in ascent, rejecting.\n");
    146:       ls->step = (ls->step)/2;
    147:     } else if (rho > ls->ftol) {
    148:       break;
    149:     } else{
    150:       ls->step = (ls->step)/2;
    151:     }

    153:     /* Convergence testing */

    155:     if (ls->step <= ls->stepmin || ls->step >= ls->stepmax) {
    156:       ls->reason = TAOLINESEARCH_HALTED_OTHER;
    157:       PetscInfo(ls,"Rounding errors may prevent further progress.  May not be a step satisfying\n");
    158:       PetscInfo(ls,"sufficient decrease and curvature conditions. Tolerances may be too small.\n");
    159:      break;
    160:     }
    161:     if (ls->step == ls->stepmax) {
    162:       PetscInfo1(ls,"Step is at the upper bound, stepmax (%g)\n",(double)ls->stepmax);
    163:       ls->reason = TAOLINESEARCH_HALTED_UPPERBOUND;
    164:       break;
    165:     }
    166:     if (ls->step == ls->stepmin) {
    167:       PetscInfo1(ls,"Step is at the lower bound, stepmin (%g)\n",(double)ls->stepmin);
    168:       ls->reason = TAOLINESEARCH_HALTED_LOWERBOUND;
    169:       break;
    170:     }
    171:     if ((ls->nfeval+ls->nfgeval) >= ls->max_funcs) {
    172:       PetscInfo2(ls,"Number of line search function evals (%D) > maximum (%D)\n",ls->nfeval+ls->nfgeval,ls->max_funcs);
    173:       ls->reason = TAOLINESEARCH_HALTED_MAXFCN;
    174:       break;
    175:     }
    176:     if ((neP->bracket) && (ls->stepmax - ls->stepmin <= ls->rtol*ls->stepmax)) {
    177:       PetscInfo1(ls,"Relative width of interval of uncertainty is at most rtol (%g)\n",(double)ls->rtol);
    178:       ls->reason = TAOLINESEARCH_HALTED_RTOL;
    179:       break;
    180:     }
    181:   }
    182:   PetscInfo2(ls,"%D function evals in line search, step = %g\n",ls->nfeval+ls->nfgeval,(double)ls->step);
    183:   /* set new solution vector and compute gradient if necessary */
    184:   VecCopy(neP->W2, x);
    185:   if (ls->reason == TAOLINESEARCH_CONTINUE_ITERATING) {
    186:     ls->reason = TAOLINESEARCH_SUCCESS;
    187:   }
    188:   if (!g_computed) {
    189:     TaoLineSearchComputeGradient(ls,x,g);
    190:   }
    191:   return(0);
    192: }

    194: /* ---------------------------------------------------------- */

    196: /*MC
    197:    TAOLINESEARCHGPCG - Special line-search method for the Gradient-Projected Conjugate Gradient (TAOGPCG) algorithm.
    198:    Should not be used with any other algorithm.

    200:    Level: developer

    202: .keywords: Tao, linesearch
    203: M*/
    204: PETSC_EXTERN PetscErrorCode TaoLineSearchCreate_GPCG(TaoLineSearch ls)
    205: {
    206:   PetscErrorCode     ierr;
    207:   TaoLineSearch_GPCG *neP;

    210:   ls->ftol                = 0.05;
    211:   ls->rtol                = 0.0;
    212:   ls->gtol                = 0.0;
    213:   ls->stepmin             = 1.0e-20;
    214:   ls->stepmax             = 1.0e+20;
    215:   ls->nfeval              = 0;
    216:   ls->max_funcs           = 30;
    217:   ls->step                = 1.0;

    219:   PetscNewLog(ls,&neP);
    220:   neP->bracket            = 0;
    221:   neP->infoc              = 1;
    222:   ls->data = (void*)neP;

    224:   ls->ops->setup = NULL;
    225:   ls->ops->reset = NULL;
    226:   ls->ops->apply = TaoLineSearchApply_GPCG;
    227:   ls->ops->view  = TaoLineSearchView_GPCG;
    228:   ls->ops->destroy = TaoLineSearchDestroy_GPCG;
    229:   ls->ops->setfromoptions = NULL;
    230:   ls->ops->monitor = NULL;
    231:   return(0);
    232: }