1 #include <petsctaolinesearch.h> 2 #include <../src/tao/unconstrained/impls/lmvm/lmvm.h> 3 #include <../src/tao/bound/impls/blmvm/blmvm.h> 4 5 /*------------------------------------------------------------*/ 6 static PetscErrorCode TaoSolve_BLMVM(Tao tao) 7 { 8 PetscErrorCode ierr; 9 TAO_BLMVM *blmP = (TAO_BLMVM *)tao->data; 10 TaoLineSearchConvergedReason ls_status = TAOLINESEARCH_CONTINUE_ITERATING; 11 PetscReal f, fold, gdx, gnorm, gnorm2; 12 PetscReal stepsize = 1.0,delta; 13 14 PetscFunctionBegin; 15 /* Project initial point onto bounds */ 16 ierr = TaoComputeVariableBounds(tao);CHKERRQ(ierr); 17 ierr = VecMedian(tao->XL,tao->solution,tao->XU,tao->solution);CHKERRQ(ierr); 18 ierr = TaoLineSearchSetVariableBounds(tao->linesearch,tao->XL,tao->XU);CHKERRQ(ierr); 19 20 21 /* Check convergence criteria */ 22 ierr = TaoComputeObjectiveAndGradient(tao, tao->solution,&f,blmP->unprojected_gradient);CHKERRQ(ierr); 23 ierr = VecBoundGradientProjection(blmP->unprojected_gradient,tao->solution, tao->XL,tao->XU,tao->gradient);CHKERRQ(ierr); 24 25 ierr = TaoGradientNorm(tao, tao->gradient,NORM_2,&gnorm);CHKERRQ(ierr); 26 if (PetscIsInfOrNanReal(f) || PetscIsInfOrNanReal(gnorm)) SETERRQ(PETSC_COMM_SELF,1, "User provided compute function generated Inf or NaN"); 27 28 tao->reason = TAO_CONTINUE_ITERATING; 29 ierr = TaoLogConvergenceHistory(tao,f,gnorm,0.0,tao->ksp_its);CHKERRQ(ierr); 30 ierr = TaoMonitor(tao,tao->niter,f,gnorm,0.0,stepsize);CHKERRQ(ierr); 31 ierr = (*tao->ops->convergencetest)(tao,tao->cnvP);CHKERRQ(ierr); 32 if (tao->reason != TAO_CONTINUE_ITERATING) PetscFunctionReturn(0); 33 34 /* Set counter for gradient/reset steps */ 35 if (!blmP->recycle) { 36 blmP->grad = 0; 37 blmP->reset = 0; 38 ierr = MatLMVMReset(blmP->M, PETSC_FALSE);CHKERRQ(ierr); 39 } 40 41 /* Have not converged; continue with Newton method */ 42 while (tao->reason == TAO_CONTINUE_ITERATING) { 43 /* Compute direction */ 44 gnorm2 = gnorm*gnorm; 45 if (gnorm2 == 0.0) gnorm2 = PETSC_MACHINE_EPSILON; 46 if (f == 0.0) { 47 delta = 2.0 / gnorm2; 48 } else { 49 delta = 2.0 * PetscAbsScalar(f) / gnorm2; 50 } 51 ierr = MatSymBrdnSetDelta(blmP->M, delta);CHKERRQ(ierr); 52 ierr = MatLMVMUpdate(blmP->M, tao->solution, tao->gradient);CHKERRQ(ierr); 53 ierr = MatSolve(blmP->M, blmP->unprojected_gradient, tao->stepdirection);CHKERRQ(ierr); 54 ierr = VecBoundGradientProjection(tao->stepdirection,tao->solution,tao->XL,tao->XU,tao->gradient);CHKERRQ(ierr); 55 56 /* Check for success (descent direction) */ 57 ierr = VecDot(blmP->unprojected_gradient, tao->gradient, &gdx);CHKERRQ(ierr); 58 if (gdx <= 0) { 59 /* Step is not descent or solve was not successful 60 Use steepest descent direction (scaled) */ 61 ++blmP->grad; 62 63 ierr = MatLMVMReset(blmP->M, PETSC_FALSE);CHKERRQ(ierr); 64 ierr = MatLMVMUpdate(blmP->M, tao->solution, blmP->unprojected_gradient);CHKERRQ(ierr); 65 ierr = MatSolve(blmP->M,blmP->unprojected_gradient, tao->stepdirection);CHKERRQ(ierr); 66 } 67 ierr = VecScale(tao->stepdirection,-1.0);CHKERRQ(ierr); 68 69 /* Perform the linesearch */ 70 fold = f; 71 ierr = VecCopy(tao->solution, blmP->Xold);CHKERRQ(ierr); 72 ierr = VecCopy(blmP->unprojected_gradient, blmP->Gold);CHKERRQ(ierr); 73 ierr = TaoLineSearchSetInitialStepLength(tao->linesearch,1.0);CHKERRQ(ierr); 74 ierr = TaoLineSearchApply(tao->linesearch, tao->solution, &f, blmP->unprojected_gradient, tao->stepdirection, &stepsize, &ls_status);CHKERRQ(ierr); 75 ierr = TaoAddLineSearchCounts(tao);CHKERRQ(ierr); 76 77 if (ls_status != TAOLINESEARCH_SUCCESS && ls_status != TAOLINESEARCH_SUCCESS_USER) { 78 /* Linesearch failed 79 Reset factors and use scaled (projected) gradient step */ 80 ++blmP->reset; 81 82 f = fold; 83 ierr = VecCopy(blmP->Xold, tao->solution);CHKERRQ(ierr); 84 ierr = VecCopy(blmP->Gold, blmP->unprojected_gradient);CHKERRQ(ierr); 85 86 ierr = MatLMVMReset(blmP->M, PETSC_FALSE);CHKERRQ(ierr); 87 ierr = MatLMVMUpdate(blmP->M, tao->solution, blmP->unprojected_gradient);CHKERRQ(ierr); 88 ierr = MatSolve(blmP->M, blmP->unprojected_gradient, tao->stepdirection);CHKERRQ(ierr); 89 ierr = VecScale(tao->stepdirection, -1.0);CHKERRQ(ierr); 90 91 /* This may be incorrect; linesearch has values for stepmax and stepmin 92 that should be reset. */ 93 ierr = TaoLineSearchSetInitialStepLength(tao->linesearch,1.0);CHKERRQ(ierr); 94 ierr = TaoLineSearchApply(tao->linesearch,tao->solution,&f, blmP->unprojected_gradient, tao->stepdirection, &stepsize, &ls_status);CHKERRQ(ierr); 95 ierr = TaoAddLineSearchCounts(tao);CHKERRQ(ierr); 96 97 if (ls_status != TAOLINESEARCH_SUCCESS && ls_status != TAOLINESEARCH_SUCCESS_USER) { 98 tao->reason = TAO_DIVERGED_LS_FAILURE; 99 break; 100 } 101 } 102 103 /* Check for converged */ 104 ierr = VecBoundGradientProjection(blmP->unprojected_gradient, tao->solution, tao->XL, tao->XU, tao->gradient);CHKERRQ(ierr); 105 ierr = TaoGradientNorm(tao, tao->gradient, NORM_2, &gnorm);CHKERRQ(ierr); 106 107 108 if (PetscIsInfOrNanReal(f) || PetscIsInfOrNanReal(gnorm)) SETERRQ(PETSC_COMM_SELF,1, "User provided compute function generated Not-a-Number"); 109 tao->niter++; 110 ierr = TaoLogConvergenceHistory(tao,f,gnorm,0.0,tao->ksp_its);CHKERRQ(ierr); 111 ierr = TaoMonitor(tao,tao->niter,f,gnorm,0.0,stepsize);CHKERRQ(ierr); 112 ierr = (*tao->ops->convergencetest)(tao,tao->cnvP);CHKERRQ(ierr); 113 } 114 PetscFunctionReturn(0); 115 } 116 117 static PetscErrorCode TaoSetup_BLMVM(Tao tao) 118 { 119 TAO_BLMVM *blmP = (TAO_BLMVM *)tao->data; 120 PetscErrorCode ierr; 121 122 PetscFunctionBegin; 123 /* Existence of tao->solution checked in TaoSetup() */ 124 ierr = VecDuplicate(tao->solution,&blmP->Xold);CHKERRQ(ierr); 125 ierr = VecDuplicate(tao->solution,&blmP->Gold);CHKERRQ(ierr); 126 ierr = VecDuplicate(tao->solution, &blmP->unprojected_gradient);CHKERRQ(ierr); 127 128 if (!tao->stepdirection) { 129 ierr = VecDuplicate(tao->solution, &tao->stepdirection);CHKERRQ(ierr); 130 } 131 if (!tao->gradient) { 132 ierr = VecDuplicate(tao->solution,&tao->gradient);CHKERRQ(ierr); 133 } 134 if (!tao->XL) { 135 ierr = VecDuplicate(tao->solution,&tao->XL);CHKERRQ(ierr); 136 ierr = VecSet(tao->XL,PETSC_NINFINITY);CHKERRQ(ierr); 137 } 138 if (!tao->XU) { 139 ierr = VecDuplicate(tao->solution,&tao->XU);CHKERRQ(ierr); 140 ierr = VecSet(tao->XU,PETSC_INFINITY);CHKERRQ(ierr); 141 } 142 /* Allocate matrix for the limited memory approximation */ 143 ierr = MatLMVMAllocate(blmP->M,tao->solution,blmP->unprojected_gradient);CHKERRQ(ierr); 144 145 /* If the user has set a matrix to solve as the initial H0, set the options prefix here, and set up the KSP */ 146 if (blmP->H0) { 147 ierr = MatLMVMSetJ0(blmP->M, blmP->H0);CHKERRQ(ierr); 148 } 149 PetscFunctionReturn(0); 150 } 151 152 /* ---------------------------------------------------------- */ 153 static PetscErrorCode TaoDestroy_BLMVM(Tao tao) 154 { 155 TAO_BLMVM *blmP = (TAO_BLMVM *)tao->data; 156 PetscErrorCode ierr; 157 158 PetscFunctionBegin; 159 if (tao->setupcalled) { 160 ierr = VecDestroy(&blmP->unprojected_gradient);CHKERRQ(ierr); 161 ierr = VecDestroy(&blmP->Xold);CHKERRQ(ierr); 162 ierr = VecDestroy(&blmP->Gold);CHKERRQ(ierr); 163 } 164 ierr = MatDestroy(&blmP->M);CHKERRQ(ierr); 165 if (blmP->H0) { 166 PetscObjectDereference((PetscObject)blmP->H0); 167 } 168 ierr = PetscFree(tao->data);CHKERRQ(ierr); 169 PetscFunctionReturn(0); 170 } 171 172 /*------------------------------------------------------------*/ 173 static PetscErrorCode TaoSetFromOptions_BLMVM(PetscOptionItems* PetscOptionsObject,Tao tao) 174 { 175 TAO_BLMVM *blmP = (TAO_BLMVM *)tao->data; 176 PetscErrorCode ierr; 177 PetscBool is_spd; 178 179 PetscFunctionBegin; 180 ierr = PetscOptionsHead(PetscOptionsObject,"Limited-memory variable-metric method for bound constrained optimization");CHKERRQ(ierr); 181 ierr = PetscOptionsBool("-tao_blmvm_recycle","enable recycling of the BFGS matrix between subsequent TaoSolve() calls","",blmP->recycle,&blmP->recycle,NULL);CHKERRQ(ierr); 182 ierr = PetscOptionsTail();CHKERRQ(ierr); 183 ierr = TaoLineSearchSetFromOptions(tao->linesearch);CHKERRQ(ierr); 184 ierr = MatSetFromOptions(blmP->M);CHKERRQ(ierr); 185 ierr = MatGetOption(blmP->M, MAT_SPD, &is_spd);CHKERRQ(ierr); 186 if (!is_spd) SETERRQ(PetscObjectComm((PetscObject)tao), PETSC_ERR_ARG_INCOMP, "LMVM matrix must be symmetric positive-definite"); 187 PetscFunctionReturn(0); 188 } 189 190 191 /*------------------------------------------------------------*/ 192 static int TaoView_BLMVM(Tao tao, PetscViewer viewer) 193 { 194 TAO_BLMVM *lmP = (TAO_BLMVM *)tao->data; 195 PetscBool isascii; 196 PetscErrorCode ierr; 197 198 PetscFunctionBegin; 199 ierr = PetscObjectTypeCompare((PetscObject)viewer, PETSCVIEWERASCII, &isascii);CHKERRQ(ierr); 200 if (isascii) { 201 ierr = PetscViewerASCIIPrintf(viewer, "Gradient steps: %D\n", lmP->grad);CHKERRQ(ierr); 202 ierr = PetscViewerPushFormat(viewer, PETSC_VIEWER_ASCII_INFO);CHKERRQ(ierr); 203 ierr = MatView(lmP->M, viewer);CHKERRQ(ierr); 204 ierr = PetscViewerPopFormat(viewer);CHKERRQ(ierr); 205 } 206 PetscFunctionReturn(0); 207 } 208 209 static PetscErrorCode TaoComputeDual_BLMVM(Tao tao, Vec DXL, Vec DXU) 210 { 211 TAO_BLMVM *blm = (TAO_BLMVM *) tao->data; 212 PetscErrorCode ierr; 213 214 PetscFunctionBegin; 215 PetscValidHeaderSpecific(tao,TAO_CLASSID,1); 216 PetscValidHeaderSpecific(DXL,VEC_CLASSID,2); 217 PetscValidHeaderSpecific(DXU,VEC_CLASSID,3); 218 if (!tao->gradient || !blm->unprojected_gradient) SETERRQ(PETSC_COMM_SELF,PETSC_ERR_ORDER,"Dual variables don't exist yet or no longer exist.\n"); 219 220 ierr = VecCopy(tao->gradient,DXL);CHKERRQ(ierr); 221 ierr = VecAXPY(DXL,-1.0,blm->unprojected_gradient);CHKERRQ(ierr); 222 ierr = VecSet(DXU,0.0);CHKERRQ(ierr); 223 ierr = VecPointwiseMax(DXL,DXL,DXU);CHKERRQ(ierr); 224 225 ierr = VecCopy(blm->unprojected_gradient,DXU);CHKERRQ(ierr); 226 ierr = VecAXPY(DXU,-1.0,tao->gradient);CHKERRQ(ierr); 227 ierr = VecAXPY(DXU,1.0,DXL);CHKERRQ(ierr); 228 PetscFunctionReturn(0); 229 } 230 231 /* ---------------------------------------------------------- */ 232 /*MC 233 TAOBLMVM - Bounded limited memory variable metric is a quasi-Newton method 234 for nonlinear minimization with bound constraints. It is an extension 235 of TAOLMVM 236 237 Options Database Keys: 238 . -tao_lmm_recycle - enable recycling of LMVM information between subsequent TaoSolve calls 239 240 Level: beginner 241 M*/ 242 PETSC_EXTERN PetscErrorCode TaoCreate_BLMVM(Tao tao) 243 { 244 TAO_BLMVM *blmP; 245 const char *morethuente_type = TAOLINESEARCHMT; 246 PetscErrorCode ierr; 247 248 PetscFunctionBegin; 249 tao->ops->setup = TaoSetup_BLMVM; 250 tao->ops->solve = TaoSolve_BLMVM; 251 tao->ops->view = TaoView_BLMVM; 252 tao->ops->setfromoptions = TaoSetFromOptions_BLMVM; 253 tao->ops->destroy = TaoDestroy_BLMVM; 254 tao->ops->computedual = TaoComputeDual_BLMVM; 255 256 ierr = PetscNewLog(tao,&blmP);CHKERRQ(ierr); 257 blmP->H0 = NULL; 258 blmP->recycle = PETSC_FALSE; 259 tao->data = (void*)blmP; 260 261 /* Override default settings (unless already changed) */ 262 if (!tao->max_it_changed) tao->max_it = 2000; 263 if (!tao->max_funcs_changed) tao->max_funcs = 4000; 264 265 ierr = TaoLineSearchCreate(((PetscObject)tao)->comm, &tao->linesearch);CHKERRQ(ierr); 266 ierr = PetscObjectIncrementTabLevel((PetscObject)tao->linesearch, (PetscObject)tao, 1);CHKERRQ(ierr); 267 ierr = TaoLineSearchSetType(tao->linesearch, morethuente_type);CHKERRQ(ierr); 268 ierr = TaoLineSearchUseTaoRoutines(tao->linesearch,tao);CHKERRQ(ierr); 269 ierr = TaoLineSearchSetOptionsPrefix(tao->linesearch,tao->hdr.prefix);CHKERRQ(ierr); 270 271 ierr = KSPInitializePackage();CHKERRQ(ierr); 272 ierr = MatCreate(((PetscObject)tao)->comm, &blmP->M);CHKERRQ(ierr); 273 ierr = MatSetType(blmP->M, MATLMVMBFGS);CHKERRQ(ierr); 274 ierr = PetscObjectIncrementTabLevel((PetscObject)blmP->M, (PetscObject)tao, 1);CHKERRQ(ierr); 275 ierr = MatSetOptionsPrefix(blmP->M, "tao_blmvm_");CHKERRQ(ierr); 276 PetscFunctionReturn(0); 277 } 278 279 PetscErrorCode TaoLMVMRecycle(Tao tao, PetscBool flg) 280 { 281 TAO_LMVM *lmP; 282 TAO_BLMVM *blmP; 283 TaoType type; 284 PetscBool is_lmvm, is_blmvm; 285 PetscErrorCode ierr; 286 287 PetscFunctionBegin; 288 ierr = TaoGetType(tao, &type);CHKERRQ(ierr); 289 ierr = PetscStrcmp(type, TAOLMVM, &is_lmvm);CHKERRQ(ierr); 290 ierr = PetscStrcmp(type, TAOBLMVM, &is_blmvm);CHKERRQ(ierr); 291 292 if (is_lmvm) { 293 lmP = (TAO_LMVM *)tao->data; 294 lmP->recycle = flg; 295 } else if (is_blmvm) { 296 blmP = (TAO_BLMVM *)tao->data; 297 blmP->recycle = flg; 298 } else SETERRQ(PetscObjectComm((PetscObject)tao), PETSC_ERR_ARG_WRONGSTATE, "This routine applies to TAO_LMVM and TAO_BLMVM."); 299 PetscFunctionReturn(0); 300 } 301 302 PetscErrorCode TaoLMVMSetH0(Tao tao, Mat H0) 303 { 304 TAO_LMVM *lmP; 305 TAO_BLMVM *blmP; 306 TaoType type; 307 PetscBool is_lmvm, is_blmvm; 308 PetscErrorCode ierr; 309 310 PetscFunctionBegin; 311 ierr = TaoGetType(tao, &type);CHKERRQ(ierr); 312 ierr = PetscStrcmp(type, TAOLMVM, &is_lmvm);CHKERRQ(ierr); 313 ierr = PetscStrcmp(type, TAOBLMVM, &is_blmvm);CHKERRQ(ierr); 314 315 if (is_lmvm) { 316 lmP = (TAO_LMVM *)tao->data; 317 ierr = PetscObjectReference((PetscObject)H0);CHKERRQ(ierr); 318 lmP->H0 = H0; 319 } else if (is_blmvm) { 320 blmP = (TAO_BLMVM *)tao->data; 321 ierr = PetscObjectReference((PetscObject)H0);CHKERRQ(ierr); 322 blmP->H0 = H0; 323 } else SETERRQ(PetscObjectComm((PetscObject)tao), PETSC_ERR_ARG_WRONGSTATE, "This routine applies to TAO_LMVM and TAO_BLMVM."); 324 PetscFunctionReturn(0); 325 } 326 327 PetscErrorCode TaoLMVMGetH0(Tao tao, Mat *H0) 328 { 329 TAO_LMVM *lmP; 330 TAO_BLMVM *blmP; 331 TaoType type; 332 PetscBool is_lmvm, is_blmvm; 333 Mat M; 334 335 PetscErrorCode ierr; 336 337 PetscFunctionBegin; 338 ierr = TaoGetType(tao, &type);CHKERRQ(ierr); 339 ierr = PetscStrcmp(type, TAOLMVM, &is_lmvm);CHKERRQ(ierr); 340 ierr = PetscStrcmp(type, TAOBLMVM, &is_blmvm);CHKERRQ(ierr); 341 342 if (is_lmvm) { 343 lmP = (TAO_LMVM *)tao->data; 344 M = lmP->M; 345 } else if (is_blmvm) { 346 blmP = (TAO_BLMVM *)tao->data; 347 M = blmP->M; 348 } else SETERRQ(PetscObjectComm((PetscObject)tao), PETSC_ERR_ARG_WRONGSTATE, "This routine applies to TAO_LMVM and TAO_BLMVM."); 349 ierr = MatLMVMGetJ0(M, H0);CHKERRQ(ierr); 350 PetscFunctionReturn(0); 351 } 352 353 PetscErrorCode TaoLMVMGetH0KSP(Tao tao, KSP *ksp) 354 { 355 TAO_LMVM *lmP; 356 TAO_BLMVM *blmP; 357 TaoType type; 358 PetscBool is_lmvm, is_blmvm; 359 Mat M; 360 PetscErrorCode ierr; 361 362 ierr = TaoGetType(tao, &type);CHKERRQ(ierr); 363 ierr = PetscStrcmp(type, TAOLMVM, &is_lmvm);CHKERRQ(ierr); 364 ierr = PetscStrcmp(type, TAOBLMVM, &is_blmvm);CHKERRQ(ierr); 365 366 if (is_lmvm) { 367 lmP = (TAO_LMVM *)tao->data; 368 M = lmP->M; 369 } else if (is_blmvm) { 370 blmP = (TAO_BLMVM *)tao->data; 371 M = blmP->M; 372 } else SETERRQ(PetscObjectComm((PetscObject)tao), PETSC_ERR_ARG_WRONGSTATE, "This routine applies to TAO_LMVM and TAO_BLMVM."); 373 ierr = MatLMVMGetJ0KSP(M, ksp);CHKERRQ(ierr); 374 PetscFunctionReturn(0); 375 } 376