Actual source code: owarmijo.c

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

      4: #define REPLACE_FIFO 1
      5: #define REPLACE_MRU  2

      7: #define REFERENCE_MAX  1
      8: #define REFERENCE_AVE  2
      9: #define REFERENCE_MEAN 3

     11: static PetscErrorCode ProjWork_OWLQN(Vec w, Vec x, Vec gv, PetscReal *gdx)
     12: {
     13:   const PetscReal *xptr, *gptr;
     14:   PetscReal       *wptr;
     15:   PetscInt         low, high, low1, high1, low2, high2, i;

     17:   PetscFunctionBegin;
     18:   PetscCall(VecGetOwnershipRange(w, &low, &high));
     19:   PetscCall(VecGetOwnershipRange(x, &low1, &high1));
     20:   PetscCall(VecGetOwnershipRange(gv, &low2, &high2));

     22:   *gdx = 0.0;
     23:   PetscCall(VecGetArray(w, &wptr));
     24:   PetscCall(VecGetArrayRead(x, &xptr));
     25:   PetscCall(VecGetArrayRead(gv, &gptr));

     27:   for (i = 0; i < high - low; i++) {
     28:     if (xptr[i] * wptr[i] < 0.0) wptr[i] = 0.0;
     29:     *gdx = *gdx + gptr[i] * (wptr[i] - xptr[i]);
     30:   }
     31:   PetscCall(VecRestoreArray(w, &wptr));
     32:   PetscCall(VecRestoreArrayRead(x, &xptr));
     33:   PetscCall(VecRestoreArrayRead(gv, &gptr));
     34:   PetscFunctionReturn(PETSC_SUCCESS);
     35: }

     37: static PetscErrorCode TaoLineSearchDestroy_OWArmijo(TaoLineSearch ls)
     38: {
     39:   TaoLineSearch_OWARMIJO *armP = (TaoLineSearch_OWARMIJO *)ls->data;

     41:   PetscFunctionBegin;
     42:   PetscCall(PetscFree(armP->memory));
     43:   if (armP->x) PetscCall(PetscObjectDereference((PetscObject)armP->x));
     44:   PetscCall(VecDestroy(&armP->work));
     45:   PetscCall(PetscFree(ls->data));
     46:   PetscFunctionReturn(PETSC_SUCCESS);
     47: }

     49: static PetscErrorCode TaoLineSearchSetFromOptions_OWArmijo(TaoLineSearch ls, PetscOptionItems *PetscOptionsObject)
     50: {
     51:   TaoLineSearch_OWARMIJO *armP = (TaoLineSearch_OWARMIJO *)ls->data;

     53:   PetscFunctionBegin;
     54:   PetscOptionsHeadBegin(PetscOptionsObject, "OWArmijo linesearch options");
     55:   PetscCall(PetscOptionsReal("-tao_ls_OWArmijo_alpha", "initial reference constant", "", armP->alpha, &armP->alpha, NULL));
     56:   PetscCall(PetscOptionsReal("-tao_ls_OWArmijo_beta_inf", "decrease constant one", "", armP->beta_inf, &armP->beta_inf, NULL));
     57:   PetscCall(PetscOptionsReal("-tao_ls_OWArmijo_beta", "decrease constant", "", armP->beta, &armP->beta, NULL));
     58:   PetscCall(PetscOptionsReal("-tao_ls_OWArmijo_sigma", "acceptance constant", "", armP->sigma, &armP->sigma, NULL));
     59:   PetscCall(PetscOptionsInt("-tao_ls_OWArmijo_memory_size", "number of historical elements", "", armP->memorySize, &armP->memorySize, NULL));
     60:   PetscCall(PetscOptionsInt("-tao_ls_OWArmijo_reference_policy", "policy for updating reference value", "", armP->referencePolicy, &armP->referencePolicy, NULL));
     61:   PetscCall(PetscOptionsInt("-tao_ls_OWArmijo_replacement_policy", "policy for updating memory", "", armP->replacementPolicy, &armP->replacementPolicy, NULL));
     62:   PetscCall(PetscOptionsBool("-tao_ls_OWArmijo_nondescending", "Use nondescending OWArmijo algorithm", "", armP->nondescending, &armP->nondescending, NULL));
     63:   PetscOptionsHeadEnd();
     64:   PetscFunctionReturn(PETSC_SUCCESS);
     65: }

     67: static PetscErrorCode TaoLineSearchView_OWArmijo(TaoLineSearch ls, PetscViewer pv)
     68: {
     69:   TaoLineSearch_OWARMIJO *armP = (TaoLineSearch_OWARMIJO *)ls->data;
     70:   PetscBool               isascii;

     72:   PetscFunctionBegin;
     73:   PetscCall(PetscObjectTypeCompare((PetscObject)pv, PETSCVIEWERASCII, &isascii));
     74:   if (isascii) {
     75:     PetscCall(PetscViewerASCIIPrintf(pv, "  OWArmijo linesearch"));
     76:     if (armP->nondescending) PetscCall(PetscViewerASCIIPrintf(pv, " (nondescending)"));
     77:     PetscCall(PetscViewerASCIIPrintf(pv, ": alpha=%g beta=%g ", (double)armP->alpha, (double)armP->beta));
     78:     PetscCall(PetscViewerASCIIPrintf(pv, "sigma=%g ", (double)armP->sigma));
     79:     PetscCall(PetscViewerASCIIPrintf(pv, "memsize=%" PetscInt_FMT "\n", armP->memorySize));
     80:   }
     81:   PetscFunctionReturn(PETSC_SUCCESS);
     82: }

     84: /* @ TaoApply_OWArmijo - This routine performs a linesearch. It
     85:    backtracks until the (nonmonotone) OWArmijo conditions are satisfied.

     87:    Input Parameters:
     88: +  tao - TAO_SOLVER context
     89: .  X - current iterate (on output X contains new iterate, X + step*S)
     90: .  S - search direction
     91: .  f - merit function evaluated at X
     92: .  G - gradient of merit function evaluated at X
     93: .  W - work vector
     94: -  step - initial estimate of step length

     96:    Output parameters:
     97: +  f - merit function evaluated at new iterate, X + step*S
     98: .  G - gradient of merit function evaluated at new iterate, X + step*S
     99: .  X - new iterate
    100: -  step - final step length

    102:    Info is set to one of:
    103: .   0 - the line search succeeds; the sufficient decrease
    104:    condition and the directional derivative condition hold

    106:    negative number if an input parameter is invalid
    107: -   -1 -  step < 0

    109:    positive number > 1 if the line search otherwise terminates
    110: +    1 -  Step is at the lower bound, stepmin.
    111: @ */
    112: static PetscErrorCode TaoLineSearchApply_OWArmijo(TaoLineSearch ls, Vec x, PetscReal *f, Vec g, Vec s)
    113: {
    114:   TaoLineSearch_OWARMIJO *armP = (TaoLineSearch_OWARMIJO *)ls->data;
    115:   PetscInt                i, its = 0;
    116:   PetscReal               fact, ref, gdx;
    117:   PetscInt                idx;
    118:   PetscBool               g_computed = PETSC_FALSE; /* to prevent extra gradient computation */
    119:   Vec                     g_old;
    120:   PetscReal               owlqn_minstep = 0.005;
    121:   PetscReal               partgdx;
    122:   MPI_Comm                comm;

    124:   PetscFunctionBegin;
    125:   PetscCall(PetscObjectGetComm((PetscObject)ls, &comm));
    126:   fact       = 0.0;
    127:   ls->nfeval = 0;
    128:   ls->reason = TAOLINESEARCH_CONTINUE_ITERATING;
    129:   if (!armP->work) {
    130:     PetscCall(VecDuplicate(x, &armP->work));
    131:     armP->x = x;
    132:     PetscCall(PetscObjectReference((PetscObject)armP->x));
    133:   } else if (x != armP->x) {
    134:     PetscCall(VecDestroy(&armP->work));
    135:     PetscCall(VecDuplicate(x, &armP->work));
    136:     PetscCall(PetscObjectDereference((PetscObject)armP->x));
    137:     armP->x = x;
    138:     PetscCall(PetscObjectReference((PetscObject)armP->x));
    139:   }

    141:   PetscCall(TaoLineSearchMonitor(ls, 0, *f, 0.0));

    143:   /* Check linesearch parameters */
    144:   if (armP->alpha < 1) {
    145:     PetscCall(PetscInfo(ls, "OWArmijo line search error: alpha (%g) < 1\n", (double)armP->alpha));
    146:     ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
    147:   } else if ((armP->beta <= 0) || (armP->beta >= 1)) {
    148:     PetscCall(PetscInfo(ls, "OWArmijo line search error: beta (%g) invalid\n", (double)armP->beta));
    149:     ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
    150:   } else if ((armP->beta_inf <= 0) || (armP->beta_inf >= 1)) {
    151:     PetscCall(PetscInfo(ls, "OWArmijo line search error: beta_inf (%g) invalid\n", (double)armP->beta_inf));
    152:     ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
    153:   } else if ((armP->sigma <= 0) || (armP->sigma >= 0.5)) {
    154:     PetscCall(PetscInfo(ls, "OWArmijo line search error: sigma (%g) invalid\n", (double)armP->sigma));
    155:     ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
    156:   } else if (armP->memorySize < 1) {
    157:     PetscCall(PetscInfo(ls, "OWArmijo line search error: memory_size (%" PetscInt_FMT ") < 1\n", armP->memorySize));
    158:     ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
    159:   } else if ((armP->referencePolicy != REFERENCE_MAX) && (armP->referencePolicy != REFERENCE_AVE) && (armP->referencePolicy != REFERENCE_MEAN)) {
    160:     PetscCall(PetscInfo(ls, "OWArmijo line search error: reference_policy invalid\n"));
    161:     ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
    162:   } else if ((armP->replacementPolicy != REPLACE_FIFO) && (armP->replacementPolicy != REPLACE_MRU)) {
    163:     PetscCall(PetscInfo(ls, "OWArmijo line search error: replacement_policy invalid\n"));
    164:     ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
    165:   } else if (PetscIsInfOrNanReal(*f)) {
    166:     PetscCall(PetscInfo(ls, "OWArmijo line search error: initial function inf or nan\n"));
    167:     ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
    168:   }

    170:   if (ls->reason != TAOLINESEARCH_CONTINUE_ITERATING) PetscFunctionReturn(PETSC_SUCCESS);

    172:   /* Check to see of the memory has been allocated.  If not, allocate
    173:      the historical array and populate it with the initial function
    174:      values. */
    175:   if (!armP->memory) PetscCall(PetscMalloc1(armP->memorySize, &armP->memory));

    177:   if (!armP->memorySetup) {
    178:     for (i = 0; i < armP->memorySize; i++) armP->memory[i] = armP->alpha * (*f);
    179:     armP->current       = 0;
    180:     armP->lastReference = armP->memory[0];
    181:     armP->memorySetup   = PETSC_TRUE;
    182:   }

    184:   /* Calculate reference value (MAX) */
    185:   ref = armP->memory[0];
    186:   idx = 0;

    188:   for (i = 1; i < armP->memorySize; i++) {
    189:     if (armP->memory[i] > ref) {
    190:       ref = armP->memory[i];
    191:       idx = i;
    192:     }
    193:   }

    195:   if (armP->referencePolicy == REFERENCE_AVE) {
    196:     ref = 0;
    197:     for (i = 0; i < armP->memorySize; i++) ref += armP->memory[i];
    198:     ref = ref / armP->memorySize;
    199:     ref = PetscMax(ref, armP->memory[armP->current]);
    200:   } else if (armP->referencePolicy == REFERENCE_MEAN) {
    201:     ref = PetscMin(ref, 0.5 * (armP->lastReference + armP->memory[armP->current]));
    202:   }

    204:   if (armP->nondescending) fact = armP->sigma;

    206:   PetscCall(VecDuplicate(g, &g_old));
    207:   PetscCall(VecCopy(g, g_old));

    209:   ls->step = ls->initstep;
    210:   while (ls->step >= owlqn_minstep && ls->nfeval < ls->max_funcs) {
    211:     /* Calculate iterate */
    212:     ++its;
    213:     PetscCall(VecWAXPY(armP->work, ls->step, s, x));

    215:     partgdx = 0.0;
    216:     PetscCall(ProjWork_OWLQN(armP->work, x, g_old, &partgdx));
    217:     PetscCallMPI(MPIU_Allreduce(&partgdx, &gdx, 1, MPIU_REAL, MPIU_SUM, comm));

    219:     /* Check the condition of gdx */
    220:     if (PetscIsInfOrNanReal(gdx)) {
    221:       PetscCall(PetscInfo(ls, "Initial Line Search step * g is Inf or Nan (%g)\n", (double)gdx));
    222:       ls->reason = TAOLINESEARCH_FAILED_INFORNAN;
    223:       PetscFunctionReturn(PETSC_SUCCESS);
    224:     }
    225:     if (gdx >= 0.0) {
    226:       PetscCall(PetscInfo(ls, "Initial Line Search step is not descent direction (g's=%g)\n", (double)gdx));
    227:       ls->reason = TAOLINESEARCH_FAILED_ASCENT;
    228:       PetscFunctionReturn(PETSC_SUCCESS);
    229:     }

    231:     /* Calculate function at new iterate */
    232:     PetscCall(TaoLineSearchComputeObjectiveAndGradient(ls, armP->work, f, g));
    233:     g_computed = PETSC_TRUE;

    235:     PetscCall(TaoLineSearchMonitor(ls, its, *f, ls->step));

    237:     if (ls->step == ls->initstep) ls->f_fullstep = *f;

    239:     if (PetscIsInfOrNanReal(*f)) {
    240:       ls->step *= armP->beta_inf;
    241:     } else {
    242:       /* Check descent condition */
    243:       if (armP->nondescending && *f <= ref - ls->step * fact * ref) break;
    244:       if (!armP->nondescending && *f <= ref + armP->sigma * gdx) break;
    245:       ls->step *= armP->beta;
    246:     }
    247:   }
    248:   PetscCall(VecDestroy(&g_old));

    250:   /* Check termination */
    251:   if (PetscIsInfOrNanReal(*f)) {
    252:     PetscCall(PetscInfo(ls, "Function is inf or nan.\n"));
    253:     ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
    254:   } else if (ls->step < owlqn_minstep) {
    255:     PetscCall(PetscInfo(ls, "Step length is below tolerance.\n"));
    256:     ls->reason = TAOLINESEARCH_HALTED_RTOL;
    257:   } else if (ls->nfeval >= ls->max_funcs) {
    258:     PetscCall(PetscInfo(ls, "Number of line search function evals (%" PetscInt_FMT ") > maximum allowed (%" PetscInt_FMT ")\n", ls->nfeval, ls->max_funcs));
    259:     ls->reason = TAOLINESEARCH_HALTED_MAXFCN;
    260:   }
    261:   if (ls->reason) PetscFunctionReturn(PETSC_SUCCESS);

    263:   /* Successful termination, update memory */
    264:   ls->reason          = TAOLINESEARCH_SUCCESS;
    265:   armP->lastReference = ref;
    266:   if (armP->replacementPolicy == REPLACE_FIFO) {
    267:     armP->memory[armP->current++] = *f;
    268:     if (armP->current >= armP->memorySize) armP->current = 0;
    269:   } else {
    270:     armP->current     = idx;
    271:     armP->memory[idx] = *f;
    272:   }

    274:   /* Update iterate and compute gradient */
    275:   PetscCall(VecCopy(armP->work, x));
    276:   if (!g_computed) PetscCall(TaoLineSearchComputeGradient(ls, x, g));
    277:   PetscCall(PetscInfo(ls, "%" PetscInt_FMT " function evals in line search, step = %10.4f\n", ls->nfeval, (double)ls->step));
    278:   PetscFunctionReturn(PETSC_SUCCESS);
    279: }

    281: /*MC
    282:    TAOLINESEARCHOWARMIJO - Special line-search type for the Orthant-Wise Limited Quasi-Newton (`TAOOWLQN`) algorithm.
    283:    Should not be used with any other algorithm.

    285:    Level: developer

    287: .seealso: `TaoLineSearch`, `TAOOWLQN`, `Tao`
    288: M*/
    289: PETSC_EXTERN PetscErrorCode TaoLineSearchCreate_OWArmijo(TaoLineSearch ls)
    290: {
    291:   TaoLineSearch_OWARMIJO *armP;

    293:   PetscFunctionBegin;
    295:   PetscCall(PetscNew(&armP));

    297:   armP->memory            = NULL;
    298:   armP->alpha             = 1.0;
    299:   armP->beta              = 0.25;
    300:   armP->beta_inf          = 0.25;
    301:   armP->sigma             = 1e-4;
    302:   armP->memorySize        = 1;
    303:   armP->referencePolicy   = REFERENCE_MAX;
    304:   armP->replacementPolicy = REPLACE_MRU;
    305:   armP->nondescending     = PETSC_FALSE;
    306:   ls->data                = (void *)armP;
    307:   ls->initstep            = 0.1;
    308:   ls->ops->monitor        = NULL;
    309:   ls->ops->setup          = NULL;
    310:   ls->ops->reset          = NULL;
    311:   ls->ops->apply          = TaoLineSearchApply_OWArmijo;
    312:   ls->ops->view           = TaoLineSearchView_OWArmijo;
    313:   ls->ops->destroy        = TaoLineSearchDestroy_OWArmijo;
    314:   ls->ops->setfromoptions = TaoLineSearchSetFromOptions_OWArmijo;
    315:   PetscFunctionReturn(PETSC_SUCCESS);
    316: }