Actual source code: armijo.c
1: #include <petsc/private/taolinesearchimpl.h>
2: #include <../src/tao/linesearch/impls/armijo/armijo.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 TaoLineSearchDestroy_Armijo(TaoLineSearch ls)
12: {
13: TaoLineSearch_ARMIJO *armP = (TaoLineSearch_ARMIJO *)ls->data;
15: PetscFree(armP->memory);
16: VecDestroy(&armP->x);
17: VecDestroy(&armP->work);
18: PetscFree(ls->data);
19: return 0;
20: }
22: static PetscErrorCode TaoLineSearchReset_Armijo(TaoLineSearch ls)
23: {
24: TaoLineSearch_ARMIJO *armP = (TaoLineSearch_ARMIJO *)ls->data;
26: PetscFree(armP->memory);
27: armP->memorySetup = PETSC_FALSE;
28: return 0;
29: }
31: static PetscErrorCode TaoLineSearchSetFromOptions_Armijo(TaoLineSearch ls, PetscOptionItems *PetscOptionsObject)
32: {
33: TaoLineSearch_ARMIJO *armP = (TaoLineSearch_ARMIJO *)ls->data;
35: PetscOptionsHeadBegin(PetscOptionsObject, "Armijo linesearch options");
36: PetscOptionsReal("-tao_ls_armijo_alpha", "initial reference constant", "", armP->alpha, &armP->alpha, NULL);
37: PetscOptionsReal("-tao_ls_armijo_beta_inf", "decrease constant one", "", armP->beta_inf, &armP->beta_inf, NULL);
38: PetscOptionsReal("-tao_ls_armijo_beta", "decrease constant", "", armP->beta, &armP->beta, NULL);
39: PetscOptionsReal("-tao_ls_armijo_sigma", "acceptance constant", "", armP->sigma, &armP->sigma, NULL);
40: PetscOptionsInt("-tao_ls_armijo_memory_size", "number of historical elements", "", armP->memorySize, &armP->memorySize, NULL);
41: PetscOptionsInt("-tao_ls_armijo_reference_policy", "policy for updating reference value", "", armP->referencePolicy, &armP->referencePolicy, NULL);
42: PetscOptionsInt("-tao_ls_armijo_replacement_policy", "policy for updating memory", "", armP->replacementPolicy, &armP->replacementPolicy, NULL);
43: PetscOptionsBool("-tao_ls_armijo_nondescending", "Use nondescending armijo algorithm", "", armP->nondescending, &armP->nondescending, NULL);
44: PetscOptionsHeadEnd();
45: return 0;
46: }
48: static PetscErrorCode TaoLineSearchView_Armijo(TaoLineSearch ls, PetscViewer pv)
49: {
50: TaoLineSearch_ARMIJO *armP = (TaoLineSearch_ARMIJO *)ls->data;
51: PetscBool isascii;
53: PetscObjectTypeCompare((PetscObject)pv, PETSCVIEWERASCII, &isascii);
54: if (isascii) {
55: PetscViewerASCIIPrintf(pv, " Armijo linesearch");
56: if (armP->nondescending) PetscViewerASCIIPrintf(pv, " (nondescending)");
57: if (ls->bounded) PetscViewerASCIIPrintf(pv, " (projected)");
58: PetscViewerASCIIPrintf(pv, ": alpha=%g beta=%g ", (double)armP->alpha, (double)armP->beta);
59: PetscViewerASCIIPrintf(pv, "sigma=%g ", (double)armP->sigma);
60: PetscViewerASCIIPrintf(pv, "memsize=%" PetscInt_FMT "\n", armP->memorySize);
61: }
62: return 0;
63: }
65: /* @ TaoApply_Armijo - This routine performs a linesearch. It
66: backtracks until the (nonmonotone) Armijo conditions are satisfied.
68: Input Parameters:
69: + tao - Tao context
70: . X - current iterate (on output X contains new iterate, X + step*S)
71: . S - search direction
72: . f - merit function evaluated at X
73: . G - gradient of merit function evaluated at X
74: . W - work vector
75: - step - initial estimate of step length
77: Output parameters:
78: + f - merit function evaluated at new iterate, X + step*S
79: . G - gradient of merit function evaluated at new iterate, X + step*S
80: . X - new iterate
81: - step - final step length
83: @ */
84: static PetscErrorCode TaoLineSearchApply_Armijo(TaoLineSearch ls, Vec x, PetscReal *f, Vec g, Vec s)
85: {
86: TaoLineSearch_ARMIJO *armP = (TaoLineSearch_ARMIJO *)ls->data;
87: PetscInt i, its = 0;
88: PetscReal fact, ref, gdx;
89: PetscInt idx;
90: PetscBool g_computed = PETSC_FALSE; /* to prevent extra gradient computation */
92: TaoLineSearchMonitor(ls, 0, *f, 0.0);
94: ls->reason = TAOLINESEARCH_CONTINUE_ITERATING;
95: if (!armP->work) {
96: VecDuplicate(x, &armP->work);
97: armP->x = x;
98: PetscObjectReference((PetscObject)armP->x);
99: } else if (x != armP->x) {
100: /* If x has changed, then recreate work */
101: VecDestroy(&armP->work);
102: VecDuplicate(x, &armP->work);
103: PetscObjectDereference((PetscObject)armP->x);
104: armP->x = x;
105: PetscObjectReference((PetscObject)armP->x);
106: }
108: /* Check linesearch parameters */
109: if (armP->alpha < 1) {
110: PetscInfo(ls, "Armijo line search error: alpha (%g) < 1\n", (double)armP->alpha);
111: ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
112: } else if ((armP->beta <= 0) || (armP->beta >= 1)) {
113: PetscInfo(ls, "Armijo line search error: beta (%g) invalid\n", (double)armP->beta);
114: ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
115: } else if ((armP->beta_inf <= 0) || (armP->beta_inf >= 1)) {
116: PetscInfo(ls, "Armijo line search error: beta_inf (%g) invalid\n", (double)armP->beta_inf);
117: ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
118: } else if ((armP->sigma <= 0) || (armP->sigma >= 0.5)) {
119: PetscInfo(ls, "Armijo line search error: sigma (%g) invalid\n", (double)armP->sigma);
120: ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
121: } else if (armP->memorySize < 1) {
122: PetscInfo(ls, "Armijo line search error: memory_size (%" PetscInt_FMT ") < 1\n", armP->memorySize);
123: ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
124: } else if ((armP->referencePolicy != REFERENCE_MAX) && (armP->referencePolicy != REFERENCE_AVE) && (armP->referencePolicy != REFERENCE_MEAN)) {
125: PetscInfo(ls, "Armijo line search error: reference_policy invalid\n");
126: ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
127: } else if ((armP->replacementPolicy != REPLACE_FIFO) && (armP->replacementPolicy != REPLACE_MRU)) {
128: PetscInfo(ls, "Armijo line search error: replacement_policy invalid\n");
129: ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
130: } else if (PetscIsInfOrNanReal(*f)) {
131: PetscInfo(ls, "Armijo line search error: initial function inf or nan\n");
132: ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER;
133: }
135: if (ls->reason != TAOLINESEARCH_CONTINUE_ITERATING) return 0;
137: /* Check to see of the memory has been allocated. If not, allocate
138: the historical array and populate it with the initial function
139: values. */
140: if (!armP->memory) PetscMalloc1(armP->memorySize, &armP->memory);
142: if (!armP->memorySetup) {
143: for (i = 0; i < armP->memorySize; i++) armP->memory[i] = armP->alpha * (*f);
145: armP->current = 0;
146: armP->lastReference = armP->memory[0];
147: armP->memorySetup = PETSC_TRUE;
148: }
150: /* Calculate reference value (MAX) */
151: ref = armP->memory[0];
152: idx = 0;
154: for (i = 1; i < armP->memorySize; i++) {
155: if (armP->memory[i] > ref) {
156: ref = armP->memory[i];
157: idx = i;
158: }
159: }
161: if (armP->referencePolicy == REFERENCE_AVE) {
162: ref = 0;
163: for (i = 0; i < armP->memorySize; i++) ref += armP->memory[i];
164: ref = ref / armP->memorySize;
165: ref = PetscMax(ref, armP->memory[armP->current]);
166: } else if (armP->referencePolicy == REFERENCE_MEAN) {
167: ref = PetscMin(ref, 0.5 * (armP->lastReference + armP->memory[armP->current]));
168: }
169: VecDot(g, s, &gdx);
171: if (PetscIsInfOrNanReal(gdx)) {
172: PetscInfo(ls, "Initial Line Search step * g is Inf or Nan (%g)\n", (double)gdx);
173: ls->reason = TAOLINESEARCH_FAILED_INFORNAN;
174: return 0;
175: }
176: if (gdx >= 0.0) {
177: PetscInfo(ls, "Initial Line Search step is not descent direction (g's=%g)\n", (double)gdx);
178: ls->reason = TAOLINESEARCH_FAILED_ASCENT;
179: return 0;
180: }
182: if (armP->nondescending) {
183: fact = armP->sigma;
184: } else {
185: fact = armP->sigma * gdx;
186: }
187: ls->step = ls->initstep;
188: while (ls->step >= ls->stepmin && (ls->nfeval + ls->nfgeval) < ls->max_funcs) {
189: /* Calculate iterate */
190: ++its;
191: VecWAXPY(armP->work, ls->step, s, x);
192: if (ls->bounded) VecMedian(ls->lower, armP->work, ls->upper, armP->work);
194: /* Calculate function at new iterate */
195: if (ls->hasobjective) {
196: TaoLineSearchComputeObjective(ls, armP->work, f);
197: g_computed = PETSC_FALSE;
198: } else if (ls->usegts) {
199: TaoLineSearchComputeObjectiveAndGTS(ls, armP->work, f, &gdx);
200: g_computed = PETSC_FALSE;
201: } else {
202: TaoLineSearchComputeObjectiveAndGradient(ls, armP->work, f, g);
203: g_computed = PETSC_TRUE;
204: }
205: if (ls->step == ls->initstep) ls->f_fullstep = *f;
207: TaoLineSearchMonitor(ls, its, *f, ls->step);
209: if (PetscIsInfOrNanReal(*f)) {
210: ls->step *= armP->beta_inf;
211: } else {
212: /* Check descent condition */
213: if (armP->nondescending && *f <= ref - ls->step * fact * ref) break;
214: if (!armP->nondescending && *f <= ref + ls->step * fact) break;
216: ls->step *= armP->beta;
217: }
218: }
220: /* Check termination */
221: if (PetscIsInfOrNanReal(*f)) {
222: PetscInfo(ls, "Function is inf or nan.\n");
223: ls->reason = TAOLINESEARCH_FAILED_INFORNAN;
224: } else if (ls->step < ls->stepmin) {
225: PetscInfo(ls, "Step length is below tolerance.\n");
226: ls->reason = TAOLINESEARCH_HALTED_RTOL;
227: } else if ((ls->nfeval + ls->nfgeval) >= ls->max_funcs) {
228: PetscInfo(ls, "Number of line search function evals (%" PetscInt_FMT ") > maximum allowed (%" PetscInt_FMT ")\n", ls->nfeval + ls->nfgeval, ls->max_funcs);
229: ls->reason = TAOLINESEARCH_HALTED_MAXFCN;
230: }
231: if (ls->reason) return 0;
233: /* Successful termination, update memory */
234: ls->reason = TAOLINESEARCH_SUCCESS;
235: armP->lastReference = ref;
236: if (armP->replacementPolicy == REPLACE_FIFO) {
237: armP->memory[armP->current++] = *f;
238: if (armP->current >= armP->memorySize) armP->current = 0;
239: } else {
240: armP->current = idx;
241: armP->memory[idx] = *f;
242: }
244: /* Update iterate and compute gradient */
245: VecCopy(armP->work, x);
246: if (!g_computed) TaoLineSearchComputeGradient(ls, x, g);
247: PetscInfo(ls, "%" PetscInt_FMT " function evals in line search, step = %g\n", ls->nfeval, (double)ls->step);
248: return 0;
249: }
251: /*MC
252: TAOLINESEARCHARMIJO - Backtracking line-search that satisfies only the (nonmonotone) Armijo condition
253: (i.e., sufficient decrease).
255: Armijo line-search type can be selected with "-tao_ls_type armijo".
257: Level: developer
259: .seealso: `TaoLineSearchCreate()`, `TaoLineSearchSetType()`, `TaoLineSearchApply()`
261: .keywords: Tao, linesearch
262: M*/
263: PETSC_EXTERN PetscErrorCode TaoLineSearchCreate_Armijo(TaoLineSearch ls)
264: {
265: TaoLineSearch_ARMIJO *armP;
268: PetscNew(&armP);
270: armP->memory = NULL;
271: armP->alpha = 1.0;
272: armP->beta = 0.5;
273: armP->beta_inf = 0.5;
274: armP->sigma = 1e-4;
275: armP->memorySize = 1;
276: armP->referencePolicy = REFERENCE_MAX;
277: armP->replacementPolicy = REPLACE_MRU;
278: armP->nondescending = PETSC_FALSE;
279: ls->data = (void *)armP;
280: ls->initstep = 1.0;
281: ls->ops->setup = NULL;
282: ls->ops->monitor = NULL;
283: ls->ops->apply = TaoLineSearchApply_Armijo;
284: ls->ops->view = TaoLineSearchView_Armijo;
285: ls->ops->destroy = TaoLineSearchDestroy_Armijo;
286: ls->ops->reset = TaoLineSearchReset_Armijo;
287: ls->ops->setfromoptions = TaoLineSearchSetFromOptions_Armijo;
288: return 0;
289: }