#include #include <../src/tao/linesearch/impls/owarmijo/owarmijo.h> #define REPLACE_FIFO 1 #define REPLACE_MRU 2 #define REFERENCE_MAX 1 #define REFERENCE_AVE 2 #define REFERENCE_MEAN 3 static PetscErrorCode ProjWork_OWLQN(Vec w,Vec x,Vec gv,PetscReal *gdx) { const PetscReal *xptr,*gptr; PetscReal *wptr; PetscErrorCode ierr; PetscInt low,high,low1,high1,low2,high2,i; PetscFunctionBegin; ierr=VecGetOwnershipRange(w,&low,&high);CHKERRQ(ierr); ierr=VecGetOwnershipRange(x,&low1,&high1);CHKERRQ(ierr); ierr=VecGetOwnershipRange(gv,&low2,&high2);CHKERRQ(ierr); *gdx=0.0; ierr = VecGetArray(w,&wptr);CHKERRQ(ierr); ierr = VecGetArrayRead(x,&xptr);CHKERRQ(ierr); ierr = VecGetArrayRead(gv,&gptr);CHKERRQ(ierr); for (i=0;idata; PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscFree(armP->memory);CHKERRQ(ierr); if (armP->x) { ierr = PetscObjectDereference((PetscObject)armP->x);CHKERRQ(ierr); } ierr = VecDestroy(&armP->work);CHKERRQ(ierr); ierr = PetscFree(ls->data);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "TaoLineSearchSetFromOptions_OWArmijo" static PetscErrorCode TaoLineSearchSetFromOptions_OWArmijo(PetscOptions *PetscOptionsObject,TaoLineSearch ls) { TaoLineSearch_OWARMIJO *armP = (TaoLineSearch_OWARMIJO *)ls->data; PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscOptionsHead(PetscOptionsObject,"OWArmijo linesearch options");CHKERRQ(ierr); ierr = PetscOptionsReal("-tao_ls_OWArmijo_alpha", "initial reference constant", "", armP->alpha, &armP->alpha,NULL);CHKERRQ(ierr); ierr = PetscOptionsReal("-tao_ls_OWArmijo_beta_inf", "decrease constant one", "", armP->beta_inf, &armP->beta_inf,NULL);CHKERRQ(ierr); ierr = PetscOptionsReal("-tao_ls_OWArmijo_beta", "decrease constant", "", armP->beta, &armP->beta,NULL);CHKERRQ(ierr); ierr = PetscOptionsReal("-tao_ls_OWArmijo_sigma", "acceptance constant", "", armP->sigma, &armP->sigma,NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-tao_ls_OWArmijo_memory_size", "number of historical elements", "", armP->memorySize, &armP->memorySize,NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-tao_ls_OWArmijo_reference_policy", "policy for updating reference value", "", armP->referencePolicy, &armP->referencePolicy,NULL);CHKERRQ(ierr); ierr = PetscOptionsInt("-tao_ls_OWArmijo_replacement_policy", "policy for updating memory", "", armP->replacementPolicy, &armP->replacementPolicy,NULL);CHKERRQ(ierr); ierr = PetscOptionsBool("-tao_ls_OWArmijo_nondescending","Use nondescending OWArmijo algorithm","",armP->nondescending,&armP->nondescending,NULL);CHKERRQ(ierr); ierr = PetscOptionsTail();CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "TaoLineSearchView_OWArmijo" static PetscErrorCode TaoLineSearchView_OWArmijo(TaoLineSearch ls, PetscViewer pv) { TaoLineSearch_OWARMIJO *armP = (TaoLineSearch_OWARMIJO *)ls->data; PetscBool isascii; PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscObjectTypeCompare((PetscObject)pv, PETSCVIEWERASCII, &isascii);CHKERRQ(ierr); if (isascii) { ierr = PetscViewerASCIIPrintf(pv," maxf=%D, ftol=%g, gtol=%g\n",ls->max_funcs, (double)ls->rtol, (double)ls->ftol);CHKERRQ(ierr); ierr=PetscViewerASCIIPrintf(pv," OWArmijo linesearch",armP->alpha);CHKERRQ(ierr); if (armP->nondescending) { ierr = PetscViewerASCIIPrintf(pv, " (nondescending)");CHKERRQ(ierr); } ierr=PetscViewerASCIIPrintf(pv,": alpha=%g beta=%g ",(double)armP->alpha,(double)armP->beta);CHKERRQ(ierr); ierr=PetscViewerASCIIPrintf(pv,"sigma=%g ",(double)armP->sigma);CHKERRQ(ierr); ierr=PetscViewerASCIIPrintf(pv,"memsize=%D\n",armP->memorySize);CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "TaoLineSearchApply_OWArmijo" /* @ TaoApply_OWArmijo - This routine performs a linesearch. It backtracks until the (nonmonotone) OWArmijo conditions are satisfied. Input Parameters: + tao - TAO_SOLVER context . X - current iterate (on output X contains new iterate, X + step*S) . S - search direction . f - merit function evaluated at X . G - gradient of merit function evaluated at X . W - work vector - step - initial estimate of step length Output parameters: + f - merit function evaluated at new iterate, X + step*S . G - gradient of merit function evaluated at new iterate, X + step*S . X - new iterate - step - final step length Info is set to one of: . 0 - the line search succeeds; the sufficient decrease condition and the directional derivative condition hold negative number if an input parameter is invalid - -1 - step < 0 positive number > 1 if the line search otherwise terminates + 1 - Step is at the lower bound, stepmin. @ */ static PetscErrorCode TaoLineSearchApply_OWArmijo(TaoLineSearch ls, Vec x, PetscReal *f, Vec g, Vec s) { TaoLineSearch_OWARMIJO *armP = (TaoLineSearch_OWARMIJO *)ls->data; PetscErrorCode ierr; PetscInt i; PetscReal fact, ref, gdx; PetscInt idx; PetscBool g_computed=PETSC_FALSE; /* to prevent extra gradient computation */ Vec g_old; PetscReal owlqn_minstep=0.005; PetscReal partgdx; MPI_Comm comm; PetscFunctionBegin; ierr = PetscObjectGetComm((PetscObject)ls,&comm);CHKERRQ(ierr); fact = 0.0; ls->nfeval=0; ls->reason = TAOLINESEARCH_CONTINUE_ITERATING; if (!armP->work) { ierr = VecDuplicate(x,&armP->work);CHKERRQ(ierr); armP->x = x; ierr = PetscObjectReference((PetscObject)armP->x);CHKERRQ(ierr); } else if (x != armP->x) { ierr = VecDestroy(&armP->work);CHKERRQ(ierr); ierr = VecDuplicate(x,&armP->work);CHKERRQ(ierr); ierr = PetscObjectDereference((PetscObject)armP->x);CHKERRQ(ierr); armP->x = x; ierr = PetscObjectReference((PetscObject)armP->x);CHKERRQ(ierr); } /* Check linesearch parameters */ if (armP->alpha < 1) { ierr = PetscInfo1(ls,"OWArmijo line search error: alpha (%g) < 1\n", (double)armP->alpha);CHKERRQ(ierr); ls->reason=TAOLINESEARCH_FAILED_BADPARAMETER; } else if ((armP->beta <= 0) || (armP->beta >= 1)) { ierr = PetscInfo1(ls,"OWArmijo line search error: beta (%g) invalid\n", (double)armP->beta);CHKERRQ(ierr); ls->reason=TAOLINESEARCH_FAILED_BADPARAMETER; } else if ((armP->beta_inf <= 0) || (armP->beta_inf >= 1)) { ierr = PetscInfo1(ls,"OWArmijo line search error: beta_inf (%g) invalid\n", (double)armP->beta_inf);CHKERRQ(ierr); ls->reason=TAOLINESEARCH_FAILED_BADPARAMETER; } else if ((armP->sigma <= 0) || (armP->sigma >= 0.5)) { ierr = PetscInfo1(ls,"OWArmijo line search error: sigma (%g) invalid\n", (double)armP->sigma);CHKERRQ(ierr); ls->reason=TAOLINESEARCH_FAILED_BADPARAMETER; } else if (armP->memorySize < 1) { ierr = PetscInfo1(ls,"OWArmijo line search error: memory_size (%D) < 1\n", armP->memorySize);CHKERRQ(ierr); ls->reason=TAOLINESEARCH_FAILED_BADPARAMETER; } else if ((armP->referencePolicy != REFERENCE_MAX) && (armP->referencePolicy != REFERENCE_AVE) && (armP->referencePolicy != REFERENCE_MEAN)) { ierr = PetscInfo(ls,"OWArmijo line search error: reference_policy invalid\n");CHKERRQ(ierr); ls->reason=TAOLINESEARCH_FAILED_BADPARAMETER; } else if ((armP->replacementPolicy != REPLACE_FIFO) && (armP->replacementPolicy != REPLACE_MRU)) { ierr = PetscInfo(ls,"OWArmijo line search error: replacement_policy invalid\n");CHKERRQ(ierr); ls->reason=TAOLINESEARCH_FAILED_BADPARAMETER; } else if (PetscIsInfOrNanReal(*f)) { ierr = PetscInfo(ls,"OWArmijo line search error: initial function inf or nan\n");CHKERRQ(ierr); ls->reason=TAOLINESEARCH_FAILED_BADPARAMETER; } if (ls->reason != TAOLINESEARCH_CONTINUE_ITERATING) PetscFunctionReturn(0); /* Check to see of the memory has been allocated. If not, allocate the historical array and populate it with the initial function values. */ if (!armP->memory) { ierr = PetscMalloc1(armP->memorySize, &armP->memory );CHKERRQ(ierr); } if (!armP->memorySetup) { for (i = 0; i < armP->memorySize; i++) { armP->memory[i] = armP->alpha*(*f); } armP->current = 0; armP->lastReference = armP->memory[0]; armP->memorySetup=PETSC_TRUE; } /* Calculate reference value (MAX) */ ref = armP->memory[0]; idx = 0; for (i = 1; i < armP->memorySize; i++) { if (armP->memory[i] > ref) { ref = armP->memory[i]; idx = i; } } if (armP->referencePolicy == REFERENCE_AVE) { ref = 0; for (i = 0; i < armP->memorySize; i++) { ref += armP->memory[i]; } ref = ref / armP->memorySize; ref = PetscMax(ref, armP->memory[armP->current]); } else if (armP->referencePolicy == REFERENCE_MEAN) { ref = PetscMin(ref, 0.5*(armP->lastReference + armP->memory[armP->current])); } if (armP->nondescending) { fact = armP->sigma; } ierr = VecDuplicate(g,&g_old);CHKERRQ(ierr); ierr = VecCopy(g,g_old);CHKERRQ(ierr); ls->step = ls->initstep; while (ls->step >= owlqn_minstep && ls->nfeval < ls->max_funcs) { /* Calculate iterate */ ierr = VecCopy(x,armP->work);CHKERRQ(ierr); ierr = VecAXPY(armP->work,ls->step,s);CHKERRQ(ierr); partgdx=0.0; ierr = ProjWork_OWLQN(armP->work,x,g_old,&partgdx);CHKERRQ(ierr); ierr = MPI_Allreduce(&partgdx,&gdx,1,MPIU_REAL,MPIU_SUM,comm);CHKERRQ(ierr); /* Check the condition of gdx */ if (PetscIsInfOrNanReal(gdx)) { ierr = PetscInfo1(ls,"Initial Line Search step * g is Inf or Nan (%g)\n",(double)gdx);CHKERRQ(ierr); ls->reason=TAOLINESEARCH_FAILED_INFORNAN; PetscFunctionReturn(0); } if (gdx >= 0.0) { ierr = PetscInfo1(ls,"Initial Line Search step is not descent direction (g's=%g)\n",(double)gdx);CHKERRQ(ierr); ls->reason = TAOLINESEARCH_FAILED_ASCENT; PetscFunctionReturn(0); } /* Calculate function at new iterate */ ierr = TaoLineSearchComputeObjectiveAndGradient(ls,armP->work,f,g);CHKERRQ(ierr); g_computed=PETSC_TRUE; if (ls->step == ls->initstep) { ls->f_fullstep = *f; } if (PetscIsInfOrNanReal(*f)) { ls->step *= armP->beta_inf; } else { /* Check descent condition */ if (armP->nondescending && *f <= ref - ls->step*fact*ref) break; if (!armP->nondescending && *f <= ref + armP->sigma * gdx) break; ls->step *= armP->beta; } } ierr = VecDestroy(&g_old);CHKERRQ(ierr); /* Check termination */ if (PetscIsInfOrNanReal(*f)) { ierr = PetscInfo(ls, "Function is inf or nan.\n");CHKERRQ(ierr); ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER; } else if (ls->step < owlqn_minstep) { ierr = PetscInfo(ls, "Step length is below tolerance.\n");CHKERRQ(ierr); ls->reason = TAOLINESEARCH_HALTED_RTOL; } else if (ls->nfeval >= ls->max_funcs) { ierr = PetscInfo2(ls, "Number of line search function evals (%D) > maximum allowed (%D)\n",ls->nfeval, ls->max_funcs);CHKERRQ(ierr); ls->reason = TAOLINESEARCH_HALTED_MAXFCN; } if (ls->reason) PetscFunctionReturn(0); /* Successful termination, update memory */ armP->lastReference = ref; if (armP->replacementPolicy == REPLACE_FIFO) { armP->memory[armP->current++] = *f; if (armP->current >= armP->memorySize) { armP->current = 0; } } else { armP->current = idx; armP->memory[idx] = *f; } /* Update iterate and compute gradient */ ierr = VecCopy(armP->work,x);CHKERRQ(ierr); if (!g_computed) { ierr = TaoLineSearchComputeGradient(ls, x, g);CHKERRQ(ierr); } ierr = PetscInfo2(ls, "%D function evals in line search, step = %10.4f\n",ls->nfeval, (double)ls->step);CHKERRQ(ierr); PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "TaoLineSearchCreate_OWArmijo" PETSC_EXTERN PetscErrorCode TaoLineSearchCreate_OWArmijo(TaoLineSearch ls) { TaoLineSearch_OWARMIJO *armP; PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(ls,TAOLINESEARCH_CLASSID,1); ierr = PetscNewLog(ls,&armP);CHKERRQ(ierr); armP->memory = NULL; armP->alpha = 1.0; armP->beta = 0.25; armP->beta_inf = 0.25; armP->sigma = 1e-4; armP->memorySize = 1; armP->referencePolicy = REFERENCE_MAX; armP->replacementPolicy = REPLACE_MRU; armP->nondescending=PETSC_FALSE; ls->data = (void*)armP; ls->initstep=0.1; ls->ops->setup=0; ls->ops->reset=0; ls->ops->apply=TaoLineSearchApply_OWArmijo; ls->ops->view = TaoLineSearchView_OWArmijo; ls->ops->destroy = TaoLineSearchDestroy_OWArmijo; ls->ops->setfromoptions = TaoLineSearchSetFromOptions_OWArmijo; PetscFunctionReturn(0); }