#include "taolinesearch.h" #include "../src/tao/matrix/lmvmmat.h" #include "blmvm.h" /*------------------------------------------------------------*/ #undef __FUNCT__ #define __FUNCT__ "TaoSolve_BLMVM" static PetscErrorCode TaoSolve_BLMVM(TaoSolver tao) { PetscErrorCode ierr; TAO_BLMVM *blmP = (TAO_BLMVM *)tao->data; TaoSolverTerminationReason reason = TAO_CONTINUE_ITERATING; TaoLineSearchTerminationReason ls_status = TAOLINESEARCH_CONTINUE_ITERATING; PetscReal f, fold, gdx, gnorm; PetscReal stepsize = 1.0,delta; PetscInt iter = 0; PetscFunctionBegin; /* Project initial point onto bounds */ ierr = TaoComputeVariableBounds(tao); CHKERRQ(ierr); ierr = VecMedian(tao->XL,tao->solution,tao->XU,tao->solution); CHKERRQ(ierr); ierr = TaoLineSearchSetVariableBounds(tao->linesearch,tao->XL,tao->XU); CHKERRQ(ierr); /* Check convergence criteria */ ierr = TaoComputeObjectiveAndGradient(tao, tao->solution,&f,blmP->unprojected_gradient); CHKERRQ(ierr); ierr = VecBoundGradientProjection(blmP->unprojected_gradient,tao->solution, tao->XL,tao->XU,tao->gradient); CHKERRQ(ierr); ierr = VecNorm(tao->gradient,NORM_2,&gnorm); CHKERRQ(ierr); if (PetscIsInfOrNanReal(f) || PetscIsInfOrNanReal(gnorm)) { SETERRQ(PETSC_COMM_SELF,1, "User provided compute function generated Inf pr NaN"); } ierr = TaoMonitor(tao, iter, f, gnorm, 0.0, stepsize, &reason); CHKERRQ(ierr); if (reason != TAO_CONTINUE_ITERATING) { PetscFunctionReturn(0); } /* Set initial scaling for the function */ if (f != 0.0) { delta = 2.0*PetscAbsScalar(f) / (gnorm*gnorm); } else { delta = 2.0 / (gnorm*gnorm); } ierr = MatLMVMSetDelta(blmP->M,delta); CHKERRQ(ierr); /* Set counter for gradient/reset steps */ blmP->grad = 0; blmP->reset = 0; /* Have not converged; continue with Newton method */ while (reason == TAO_CONTINUE_ITERATING) { /* Compute direction */ ierr = MatLMVMUpdate(blmP->M, tao->solution, tao->gradient); CHKERRQ(ierr); ierr = MatLMVMSolve(blmP->M, blmP->unprojected_gradient, tao->stepdirection); CHKERRQ(ierr); ierr = VecBoundGradientProjection(tao->stepdirection,tao->solution,tao->XL,tao->XU,tao->gradient); CHKERRQ(ierr); /* Check for success (descent direction) */ ierr = VecDot(blmP->unprojected_gradient, tao->gradient, &gdx); CHKERRQ(ierr); if (gdx <= 0) { /* Step is not descent or solve was not successful Use steepest descent direction (scaled) */ ++blmP->grad; if (f != 0.0) { delta = 2.0*PetscAbsScalar(f) / (gnorm*gnorm); } else { delta = 2.0 / (gnorm*gnorm); } ierr = MatLMVMSetDelta(blmP->M,delta); CHKERRQ(ierr); ierr = MatLMVMReset(blmP->M); CHKERRQ(ierr); ierr = MatLMVMUpdate(blmP->M, tao->solution, blmP->unprojected_gradient); CHKERRQ(ierr); ierr = MatLMVMSolve(blmP->M,blmP->unprojected_gradient, tao->stepdirection); CHKERRQ(ierr); } ierr = VecScale(tao->stepdirection,-1.0); CHKERRQ(ierr); /* Perform the linesearch */ fold = f; ierr = VecCopy(tao->solution, blmP->Xold); CHKERRQ(ierr); ierr = VecCopy(blmP->unprojected_gradient, blmP->Gold); CHKERRQ(ierr); ierr = TaoLineSearchSetInitialStepLength(tao->linesearch,1.0); CHKERRQ(ierr); ierr = TaoLineSearchApply(tao->linesearch, tao->solution, &f, blmP->unprojected_gradient, tao->stepdirection, &stepsize, &ls_status); CHKERRQ(ierr); ierr = TaoAddLineSearchCounts(tao); CHKERRQ(ierr); if (ls_status != TAOLINESEARCH_SUCCESS && ls_status != TAOLINESEARCH_SUCCESS_USER) { /* Linesearch failed Reset factors and use scaled (projected) gradient step */ ++blmP->reset; f = fold; ierr = VecCopy(blmP->Xold, tao->solution); CHKERRQ(ierr); ierr = VecCopy(blmP->Gold, blmP->unprojected_gradient); CHKERRQ(ierr); if (f != 0.0) { delta = 2.0* PetscAbsScalar(f) / (gnorm*gnorm); } else { delta = 2.0/ (gnorm*gnorm); } ierr = MatLMVMSetDelta(blmP->M,delta); CHKERRQ(ierr); ierr = MatLMVMReset(blmP->M); CHKERRQ(ierr); ierr = MatLMVMUpdate(blmP->M, tao->solution, blmP->unprojected_gradient); CHKERRQ(ierr); ierr = MatLMVMSolve(blmP->M, blmP->unprojected_gradient, tao->stepdirection); CHKERRQ(ierr); ierr = VecScale(tao->stepdirection, -1.0); CHKERRQ(ierr); /* This may be incorrect; linesearch has values fo stepmax and stepmin that should be reset. */ ierr = TaoLineSearchSetInitialStepLength(tao->linesearch,1.0); ierr = TaoLineSearchApply(tao->linesearch,tao->solution,&f, blmP->unprojected_gradient, tao->stepdirection, &stepsize, &ls_status); CHKERRQ(ierr); ierr = TaoAddLineSearchCounts(tao); CHKERRQ(ierr); if (ls_status != TAOLINESEARCH_SUCCESS && ls_status != TAOLINESEARCH_SUCCESS_USER) { tao->reason = TAO_DIVERGED_LS_FAILURE; break; } } /* Check for termination */ ierr = VecBoundGradientProjection(blmP->unprojected_gradient, tao->solution, tao->XL, tao->XU, tao->gradient); CHKERRQ(ierr); ierr = VecNorm(tao->gradient, NORM_2, &gnorm); CHKERRQ(ierr); if (PetscIsInfOrNanReal(f) || PetscIsInfOrNanReal(gnorm)) { SETERRQ(PETSC_COMM_SELF,1, "User provided compute function generated Not-a-Number"); } iter++; ierr = TaoMonitor(tao, iter, f, gnorm, 0.0, stepsize, &reason); CHKERRQ(ierr); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "TaoSetup_BLMVM" static PetscErrorCode TaoSetup_BLMVM(TaoSolver tao) { TAO_BLMVM *blmP = (TAO_BLMVM *)tao->data; PetscInt n,N; PetscErrorCode ierr; PetscFunctionBegin; /* Existence of tao->solution checked in TaoSetup() */ ierr = VecDuplicate(tao->solution,&blmP->Xold); CHKERRQ(ierr); ierr = VecDuplicate(tao->solution,&blmP->Gold); CHKERRQ(ierr); ierr = VecDuplicate(tao->solution, &blmP->unprojected_gradient); if (!tao->stepdirection) { ierr = VecDuplicate(tao->solution, &tao->stepdirection); CHKERRQ(ierr); } if (!tao->gradient) { ierr = VecDuplicate(tao->solution,&tao->gradient); CHKERRQ(ierr); } if (!tao->XL) { ierr = VecDuplicate(tao->solution,&tao->XL); CHKERRQ(ierr); ierr = VecSet(tao->XL,TAO_NINFINITY); CHKERRQ(ierr); } if (!tao->XU) { ierr = VecDuplicate(tao->solution,&tao->XU); CHKERRQ(ierr); ierr = VecSet(tao->XU,TAO_INFINITY); CHKERRQ(ierr); } /* Create matrix for the limited memory approximation */ ierr = VecGetLocalSize(tao->solution,&n); CHKERRQ(ierr); ierr = VecGetSize(tao->solution,&N); CHKERRQ(ierr); ierr = MatCreateLMVM(((PetscObject)tao)->comm,n,N,&blmP->M); CHKERRQ(ierr); ierr = MatLMVMAllocateVectors(blmP->M,tao->solution); CHKERRQ(ierr); PetscFunctionReturn(0); } /* ---------------------------------------------------------- */ #undef __FUNCT__ #define __FUNCT__ "TaoDestroy_BLMVM" static PetscErrorCode TaoDestroy_BLMVM(TaoSolver tao) { TAO_BLMVM *blmP = (TAO_BLMVM *)tao->data; PetscErrorCode ierr; PetscFunctionBegin; if (tao->setupcalled) { ierr = MatDestroy(&blmP->M); CHKERRQ(ierr); ierr = VecDestroy(&blmP->unprojected_gradient); CHKERRQ(ierr); ierr = VecDestroy(&blmP->Xold); CHKERRQ(ierr); ierr = VecDestroy(&blmP->Gold); CHKERRQ(ierr); } ierr = PetscFree(tao->data); CHKERRQ(ierr); tao->data = PETSC_NULL; PetscFunctionReturn(0); } /*------------------------------------------------------------*/ #undef __FUNCT__ #define __FUNCT__ "TaoSetFromOptions_BLMVM" static PetscErrorCode TaoSetFromOptions_BLMVM(TaoSolver tao) { PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscOptionsHead("Limited-memory variable-metric method for bound constrained optimization"); CHKERRQ(ierr); ierr = TaoLineSearchSetFromOptions(tao->linesearch);CHKERRQ(ierr); ierr = PetscOptionsTail();CHKERRQ(ierr); PetscFunctionReturn(0); } /*------------------------------------------------------------*/ #undef __FUNCT__ #define __FUNCT__ "TaoView_BLMVM" static int TaoView_BLMVM(TaoSolver tao, PetscViewer viewer) { TAO_BLMVM *lmP = (TAO_BLMVM *)tao->data; PetscBool isascii; PetscErrorCode ierr; PetscFunctionBegin; ierr = PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii); CHKERRQ(ierr); if (isascii) { ierr = PetscViewerASCIIPushTab(viewer); CHKERRQ(ierr); ierr = PetscViewerASCIIPrintf(viewer, "Gradient steps: %D\n", lmP->grad); CHKERRQ(ierr); ierr = PetscViewerASCIIPopTab(viewer); CHKERRQ(ierr); } else { SETERRQ1(((PetscObject)tao)->comm,PETSC_ERR_SUP,"Viewer type %s not supported for TAO BLMVM",((PetscObject)viewer)->type_name); } PetscFunctionReturn(0); } #undef __FUNCT__ #define __FUNCT__ "TaoComputeDual_BLMVM" static PetscErrorCode TaoComputeDual_BLMVM(TaoSolver tao, Vec DXL, Vec DXU) { TAO_BLMVM *blm = (TAO_BLMVM *) tao->data; PetscErrorCode ierr; PetscFunctionBegin; PetscValidHeaderSpecific(tao,TAOSOLVER_CLASSID,1); PetscValidHeaderSpecific(DXL,VEC_CLASSID,2); PetscValidHeaderSpecific(DXU,VEC_CLASSID,3); if (!tao->gradient || !blm->unprojected_gradient) { SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Dual variables don't exist yet or no longer exist.\n"); } ierr = VecCopy(tao->gradient,DXL); CHKERRQ(ierr); ierr = VecAXPY(DXL,-1.0,blm->unprojected_gradient); CHKERRQ(ierr); ierr = VecSet(DXU,0.0); CHKERRQ(ierr); ierr = VecPointwiseMax(DXL,DXL,DXU); CHKERRQ(ierr); ierr = VecCopy(blm->unprojected_gradient,DXU); CHKERRQ(ierr); ierr = VecAXPY(DXU,-1.0,tao->gradient); CHKERRQ(ierr); ierr = VecAXPY(DXU,1.0,DXL); CHKERRQ(ierr); PetscFunctionReturn(0); } /* ---------------------------------------------------------- */ EXTERN_C_BEGIN #undef __FUNCT__ #define __FUNCT__ "TaoCreate_BLMVM" PetscErrorCode TaoCreate_BLMVM(TaoSolver tao) { TAO_BLMVM *blmP; const char *morethuente_type = TAOLINESEARCH_MT; PetscErrorCode ierr; PetscFunctionBegin; tao->ops->setup = TaoSetup_BLMVM; tao->ops->solve = TaoSolve_BLMVM; tao->ops->view = TaoView_BLMVM; tao->ops->setfromoptions = TaoSetFromOptions_BLMVM; tao->ops->destroy = TaoDestroy_BLMVM; tao->ops->computedual = TaoComputeDual_BLMVM; ierr = PetscNewLog(tao, TAO_BLMVM, &blmP); CHKERRQ(ierr); tao->data = (void*)blmP; tao->max_it = 2000; tao->max_funcs = 4000; tao->fatol = 1e-4; tao->frtol = 1e-4; ierr = TaoLineSearchCreate(((PetscObject)tao)->comm, &tao->linesearch); CHKERRQ(ierr); ierr = TaoLineSearchSetType(tao->linesearch, morethuente_type); CHKERRQ(ierr); ierr = TaoLineSearchUseTaoSolverRoutines(tao->linesearch,tao); CHKERRQ(ierr); PetscFunctionReturn(0); } EXTERN_C_END