Date: 2016-07-24T17:16:05+00:00

Actual source code: gpcglinesearch.c
petsc-3.7.3 2016-07-24
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      1: #include <petsc/private/taolinesearchimpl.h>
      2: #include <../src/tao/linesearch/impls/gpcglinesearch/gpcglinesearch.h>

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

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

     14:   VecDestroy(&ctx->W1);
     15:   VecDestroy(&ctx->W2);
     16:   VecDestroy(&ctx->Gold);
     17:   VecDestroy(&ctx->x);
     18:   PetscFree(ls->data);
     19:   return(0);
     20: }

     23: /*------------------------------------------------------------*/
     26: static PetscErrorCode TaoLineSearchView_GPCG(TaoLineSearch ls, PetscViewer viewer)
     27: {
     28:   PetscBool      isascii;

     32:   PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&isascii);
     33:   if (isascii) {
     34:     PetscViewerASCIIPrintf(viewer," GPCG Line search");
     35:   }
     36:   return(0);
     37: }

     39: /*------------------------------------------------------------*/
     42: static PetscErrorCode TaoLineSearchApply_GPCG(TaoLineSearch ls, Vec x, PetscReal *f, Vec g, Vec s)
     43: {
     44:   TaoLineSearch_GPCG *neP = (TaoLineSearch_GPCG *)ls->data;
     45:   PetscErrorCode     ierr;
     46:   PetscInt           i;
     47:   PetscBool          g_computed=PETSC_FALSE; /* to prevent extra gradient computation */
     48:   PetscReal          d1,finit,actred,prered,rho, gdx;

     51:   /* ls->stepmin - lower bound for step */
     52:   /* ls->stepmax - upper bound for step */
     53:   /* ls->rtol     - relative tolerance for an acceptable step */
     54:   /* ls->ftol     - tolerance for sufficient decrease condition */
     55:   /* ls->gtol     - tolerance for curvature condition */
     56:   /* ls->nfeval   - number of function evaluations */
     57:   /* ls->nfeval   - number of function/gradient evaluations */
     58:   /* ls->max_funcs  - maximum number of function evaluations */

     60:   ls->reason = TAOLINESEARCH_CONTINUE_ITERATING;
     61:   ls->step = ls->initstep;
     62:   if (!neP->W2) {
     63:     VecDuplicate(x,&neP->W2);
     64:     VecDuplicate(x,&neP->W1);
     65:     VecDuplicate(x,&neP->Gold);
     66:     neP->x = x;
     67:     PetscObjectReference((PetscObject)neP->x);
     68:   } else if (x != neP->x) {
     69:     VecDestroy(&neP->x);
     70:     VecDestroy(&neP->W1);
     71:     VecDestroy(&neP->W2);
     72:     VecDestroy(&neP->Gold);
     73:     VecDuplicate(x,&neP->W1);
     74:     VecDuplicate(x,&neP->W2);
     75:     VecDuplicate(x,&neP->Gold);
     76:     PetscObjectDereference((PetscObject)neP->x);
     77:     neP->x = x;
     78:     PetscObjectReference((PetscObject)neP->x);
     79:   }

     81:   VecDot(g,s,&gdx);
     82:    if (gdx > 0) {
     83:      PetscInfo1(ls,"Line search error: search direction is not descent direction. dot(g,s) = %g\n",(double)gdx);
     84:     ls->reason = TAOLINESEARCH_FAILED_ASCENT;
     85:     return(0);
     86:   }
     87:   VecCopy(x,neP->W2);
     88:   VecCopy(g,neP->Gold);
     89:   if (ls->bounded) {
     90:     /* Compute the smallest steplength that will make one nonbinding variable  equal the bound */
     91:     VecStepBoundInfo(x,s,ls->lower,ls->upper,&rho,&actred,&d1);
     92:     ls->step = PetscMin(ls->step,d1);
     93:   }
     94:   rho=0; actred=0;

     96:   if (ls->step < 0) {
     97:     PetscInfo1(ls,"Line search error: initial step parameter %g< 0\n",(double)ls->step);
     98:     ls->reason = TAOLINESEARCH_HALTED_OTHER;
     99:     return(0);
    100:   }

    102:   /* Initialization */
    103:   finit = *f;
    104:   for (i=0; i< ls->max_funcs; i++) {
    105:     /* Force the step to be within the bounds */
    106:     ls->step = PetscMax(ls->step,ls->stepmin);
    107:     ls->step = PetscMin(ls->step,ls->stepmax);

    109:     VecCopy(x,neP->W2);
    110:     VecAXPY(neP->W2,ls->step,s);
    111:     if (ls->bounded) {
    112:       /* Make sure new vector is numerically within bounds */
    113:       VecMedian(neP->W2,ls->lower,ls->upper,neP->W2);
    114:     }

    116:     /* Gradient is not needed here.  Unless there is a separate
    117:        gradient routine, compute it here anyway to prevent recomputing at
    118:        the end of the line search */
    119:     if (ls->hasobjective) {
    120:       TaoLineSearchComputeObjective(ls,neP->W2,f);
    121:       g_computed=PETSC_FALSE;
    122:     } else if (ls->usegts){
    123:       TaoLineSearchComputeObjectiveAndGTS(ls,neP->W2,f,&gdx);
    124:       g_computed=PETSC_FALSE;
    125:     } else {
    126:       TaoLineSearchComputeObjectiveAndGradient(ls,neP->W2,f,g);
    127:       g_computed=PETSC_TRUE;
    128:     }

    130:     if (0 == i) {
    131:         ls->f_fullstep = *f;
    132:     }

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

    139:     if (fabs(prered)<1.0e-100) prered=1.0e-12;
    140:     rho = actred/prered;

    142:     /*
    143:        If sufficient progress has been obtained, accept the
    144:        point.  Otherwise, backtrack.
    145:     */

    147:     if (actred > 0) {
    148:       PetscInfo(ls,"Step resulted in ascent, rejecting.\n");
    149:       ls->step = (ls->step)/2;
    150:     } else if (rho > ls->ftol){
    151:       break;
    152:     } else{
    153:       ls->step = (ls->step)/2;
    154:     }

    156:     /* Convergence testing */

    158:     if (ls->step <= ls->stepmin || ls->step >= ls->stepmax) {
    159:       ls->reason = TAOLINESEARCH_HALTED_OTHER;
    160:       PetscInfo(ls,"Rounding errors may prevent further progress.  May not be a step satisfying\n");
    161:       PetscInfo(ls,"sufficient decrease and curvature conditions. Tolerances may be too small.\n");
    162:      break;
    163:     }
    164:     if (ls->step == ls->stepmax) {
    165:       PetscInfo1(ls,"Step is at the upper bound, stepmax (%g)\n",(double)ls->stepmax);
    166:       ls->reason = TAOLINESEARCH_HALTED_UPPERBOUND;
    167:       break;
    168:     }
    169:     if (ls->step == ls->stepmin) {
    170:       PetscInfo1(ls,"Step is at the lower bound, stepmin (%g)\n",(double)ls->stepmin);
    171:       ls->reason = TAOLINESEARCH_HALTED_LOWERBOUND;
    172:       break;
    173:     }
    174:     if ((ls->nfeval+ls->nfgeval) >= ls->max_funcs) {
    175:       PetscInfo2(ls,"Number of line search function evals (%D) > maximum (%D)\n",ls->nfeval+ls->nfgeval,ls->max_funcs);
    176:       ls->reason = TAOLINESEARCH_HALTED_MAXFCN;
    177:       break;
    178:     }
    179:     if ((neP->bracket) && (ls->stepmax - ls->stepmin <= ls->rtol*ls->stepmax)){
    180:       PetscInfo1(ls,"Relative width of interval of uncertainty is at most rtol (%g)\n",(double)ls->rtol);
    181:       ls->reason = TAOLINESEARCH_HALTED_RTOL;
    182:       break;
    183:     }
    184:   }
    185:   PetscInfo2(ls,"%D function evals in line search, step = %g\n",ls->nfeval+ls->nfgeval,(double)ls->step);
    186:   /* set new solution vector and compute gradient if necessary */
    187:   VecCopy(neP->W2, x);
    188:   if (ls->reason == TAOLINESEARCH_CONTINUE_ITERATING) {
    189:     ls->reason = TAOLINESEARCH_SUCCESS;
    190:   }
    191:   if (!g_computed) {
    192:     TaoLineSearchComputeGradient(ls,x,g);
    193:   }
    194:   return(0);
    195: }

    197: /* ---------------------------------------------------------- */
    200: PETSC_EXTERN PetscErrorCode TaoLineSearchCreate_GPCG(TaoLineSearch ls)
    201: {
    202:   PetscErrorCode     ierr;
    203:   TaoLineSearch_GPCG *neP;

    206:   ls->ftol                = 0.05;
    207:   ls->rtol                = 0.0;
    208:   ls->gtol                = 0.0;
    209:   ls->stepmin             = 1.0e-20;
    210:   ls->stepmax             = 1.0e+20;
    211:   ls->nfeval              = 0;
    212:   ls->max_funcs           = 30;
    213:   ls->step                = 1.0;

    215:   PetscNewLog(ls,&neP);
    216:   neP->bracket            = 0;
    217:   neP->infoc              = 1;
    218:   ls->data = (void*)neP;

    220:   ls->ops->setup = 0;
    221:   ls->ops->reset = 0;
    222:   ls->ops->apply=TaoLineSearchApply_GPCG;
    223:   ls->ops->view =TaoLineSearchView_GPCG;
    224:   ls->ops->destroy=TaoLineSearchDestroy_GPCG;
    225:   ls->ops->setfromoptions=0;
    226:   return(0);
    227: }