#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; PetscInt low, high, low1, high1, low2, high2, i; PetscFunctionBegin; PetscCall(VecGetOwnershipRange(w, &low, &high)); PetscCall(VecGetOwnershipRange(x, &low1, &high1)); PetscCall(VecGetOwnershipRange(gv, &low2, &high2)); *gdx = 0.0; PetscCall(VecGetArray(w, &wptr)); PetscCall(VecGetArrayRead(x, &xptr)); PetscCall(VecGetArrayRead(gv, &gptr)); for (i = 0; i < high - low; i++) { if (xptr[i] * wptr[i] < 0.0) wptr[i] = 0.0; *gdx = *gdx + gptr[i] * (wptr[i] - xptr[i]); } PetscCall(VecRestoreArray(w, &wptr)); PetscCall(VecRestoreArrayRead(x, &xptr)); PetscCall(VecRestoreArrayRead(gv, &gptr)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode TaoLineSearchDestroy_OWArmijo(TaoLineSearch ls) { TaoLineSearch_OWARMIJO *armP = (TaoLineSearch_OWARMIJO *)ls->data; PetscFunctionBegin; PetscCall(PetscFree(armP->memory)); if (armP->x) PetscCall(PetscObjectDereference((PetscObject)armP->x)); PetscCall(VecDestroy(&armP->work)); PetscCall(PetscFree(ls->data)); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode TaoLineSearchSetFromOptions_OWArmijo(TaoLineSearch ls, PetscOptionItems PetscOptionsObject) { TaoLineSearch_OWARMIJO *armP = (TaoLineSearch_OWARMIJO *)ls->data; PetscFunctionBegin; PetscOptionsHeadBegin(PetscOptionsObject, "OWArmijo linesearch options"); PetscCall(PetscOptionsReal("-tao_ls_OWArmijo_alpha", "initial reference constant", "", armP->alpha, &armP->alpha, NULL)); PetscCall(PetscOptionsReal("-tao_ls_OWArmijo_beta_inf", "decrease constant one", "", armP->beta_inf, &armP->beta_inf, NULL)); PetscCall(PetscOptionsReal("-tao_ls_OWArmijo_beta", "decrease constant", "", armP->beta, &armP->beta, NULL)); PetscCall(PetscOptionsReal("-tao_ls_OWArmijo_sigma", "acceptance constant", "", armP->sigma, &armP->sigma, NULL)); PetscCall(PetscOptionsInt("-tao_ls_OWArmijo_memory_size", "number of historical elements", "", armP->memorySize, &armP->memorySize, NULL)); PetscCall(PetscOptionsInt("-tao_ls_OWArmijo_reference_policy", "policy for updating reference value", "", armP->referencePolicy, &armP->referencePolicy, NULL)); PetscCall(PetscOptionsInt("-tao_ls_OWArmijo_replacement_policy", "policy for updating memory", "", armP->replacementPolicy, &armP->replacementPolicy, NULL)); PetscCall(PetscOptionsBool("-tao_ls_OWArmijo_nondescending", "Use nondescending OWArmijo algorithm", "", armP->nondescending, &armP->nondescending, NULL)); PetscOptionsHeadEnd(); PetscFunctionReturn(PETSC_SUCCESS); } static PetscErrorCode TaoLineSearchView_OWArmijo(TaoLineSearch ls, PetscViewer pv) { TaoLineSearch_OWARMIJO *armP = (TaoLineSearch_OWARMIJO *)ls->data; PetscBool isascii; PetscFunctionBegin; PetscCall(PetscObjectTypeCompare((PetscObject)pv, PETSCVIEWERASCII, &isascii)); if (isascii) { PetscCall(PetscViewerASCIIPrintf(pv, " OWArmijo linesearch")); if (armP->nondescending) PetscCall(PetscViewerASCIIPrintf(pv, " (nondescending)")); PetscCall(PetscViewerASCIIPrintf(pv, ": alpha=%g beta=%g ", (double)armP->alpha, (double)armP->beta)); PetscCall(PetscViewerASCIIPrintf(pv, "sigma=%g ", (double)armP->sigma)); PetscCall(PetscViewerASCIIPrintf(pv, "memsize=%" PetscInt_FMT "\n", armP->memorySize)); } PetscFunctionReturn(PETSC_SUCCESS); } /* @ 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; PetscInt i, its = 0; 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; PetscCall(PetscObjectGetComm((PetscObject)ls, &comm)); fact = 0.0; ls->nfeval = 0; ls->reason = TAOLINESEARCH_CONTINUE_ITERATING; if (!armP->work) { PetscCall(VecDuplicate(x, &armP->work)); armP->x = x; PetscCall(PetscObjectReference((PetscObject)armP->x)); } else if (x != armP->x) { PetscCall(VecDestroy(&armP->work)); PetscCall(VecDuplicate(x, &armP->work)); PetscCall(PetscObjectDereference((PetscObject)armP->x)); armP->x = x; PetscCall(PetscObjectReference((PetscObject)armP->x)); } PetscCall(TaoLineSearchMonitor(ls, 0, *f, 0.0)); /* Check linesearch parameters */ if (armP->alpha < 1) { PetscCall(PetscInfo(ls, "OWArmijo line search error: alpha (%g) < 1\n", (double)armP->alpha)); ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER; } else if ((armP->beta <= 0) || (armP->beta >= 1)) { PetscCall(PetscInfo(ls, "OWArmijo line search error: beta (%g) invalid\n", (double)armP->beta)); ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER; } else if ((armP->beta_inf <= 0) || (armP->beta_inf >= 1)) { PetscCall(PetscInfo(ls, "OWArmijo line search error: beta_inf (%g) invalid\n", (double)armP->beta_inf)); ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER; } else if ((armP->sigma <= 0) || (armP->sigma >= 0.5)) { PetscCall(PetscInfo(ls, "OWArmijo line search error: sigma (%g) invalid\n", (double)armP->sigma)); ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER; } else if (armP->memorySize < 1) { PetscCall(PetscInfo(ls, "OWArmijo line search error: memory_size (%" PetscInt_FMT ") < 1\n", armP->memorySize)); ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER; } else if ((armP->referencePolicy != REFERENCE_MAX) && (armP->referencePolicy != REFERENCE_AVE) && (armP->referencePolicy != REFERENCE_MEAN)) { PetscCall(PetscInfo(ls, "OWArmijo line search error: reference_policy invalid\n")); ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER; } else if ((armP->replacementPolicy != REPLACE_FIFO) && (armP->replacementPolicy != REPLACE_MRU)) { PetscCall(PetscInfo(ls, "OWArmijo line search error: replacement_policy invalid\n")); ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER; } else if (PetscIsInfOrNanReal(*f)) { PetscCall(PetscInfo(ls, "OWArmijo line search error: initial function inf or nan\n")); ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER; } if (ls->reason != TAOLINESEARCH_CONTINUE_ITERATING) PetscFunctionReturn(PETSC_SUCCESS); /* 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) PetscCall(PetscMalloc1(armP->memorySize, &armP->memory)); 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; PetscCall(VecDuplicate(g, &g_old)); PetscCall(VecCopy(g, g_old)); ls->step = ls->initstep; while (ls->step >= owlqn_minstep && ls->nfeval < ls->max_funcs) { /* Calculate iterate */ ++its; PetscCall(VecWAXPY(armP->work, ls->step, s, x)); partgdx = 0.0; PetscCall(ProjWork_OWLQN(armP->work, x, g_old, &partgdx)); PetscCallMPI(MPIU_Allreduce(&partgdx, &gdx, 1, MPIU_REAL, MPIU_SUM, comm)); /* Check the condition of gdx */ if (PetscIsInfOrNanReal(gdx)) { PetscCall(PetscInfo(ls, "Initial Line Search step * g is infinity or NaN (%g)\n", (double)gdx)); ls->reason = TAOLINESEARCH_FAILED_INFORNAN; PetscFunctionReturn(PETSC_SUCCESS); } if (gdx >= 0.0) { PetscCall(PetscInfo(ls, "Initial Line Search step is not descent direction (g's=%g)\n", (double)gdx)); ls->reason = TAOLINESEARCH_FAILED_ASCENT; PetscFunctionReturn(PETSC_SUCCESS); } /* Calculate function at new iterate */ PetscCall(VecLockReadPush(x)); PetscCall(TaoLineSearchComputeObjectiveAndGradient(ls, armP->work, f, g)); PetscCall(VecLockReadPop(x)); g_computed = PETSC_TRUE; PetscCall(TaoLineSearchMonitor(ls, its, *f, ls->step)); 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; } } PetscCall(VecDestroy(&g_old)); /* Check termination */ if (PetscIsInfOrNanReal(*f)) { PetscCall(PetscInfo(ls, "Function is inf or nan.\n")); ls->reason = TAOLINESEARCH_FAILED_BADPARAMETER; } else if (ls->step < owlqn_minstep) { PetscCall(PetscInfo(ls, "Step length is below tolerance.\n")); ls->reason = TAOLINESEARCH_HALTED_RTOL; } else if (ls->nfeval >= ls->max_funcs) { PetscCall(PetscInfo(ls, "Number of line search function evals (%" PetscInt_FMT ") > maximum allowed (%" PetscInt_FMT ")\n", ls->nfeval, ls->max_funcs)); ls->reason = TAOLINESEARCH_HALTED_MAXFCN; } if (ls->reason) PetscFunctionReturn(PETSC_SUCCESS); /* Successful termination, update memory */ ls->reason = TAOLINESEARCH_SUCCESS; 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 */ PetscCall(VecCopy(armP->work, x)); if (!g_computed) PetscCall(TaoLineSearchComputeGradient(ls, x, g)); PetscCall(PetscInfo(ls, "%" PetscInt_FMT " function evals in line search, step = %10.4f\n", ls->nfeval, (double)ls->step)); PetscFunctionReturn(PETSC_SUCCESS); } /*MC TAOLINESEARCHOWARMIJO - Special line-search type for the Orthant-Wise Limited Quasi-Newton (`TAOOWLQN`) algorithm. Should not be used with any other algorithm. Level: developer .seealso: `TaoLineSearch`, `TAOOWLQN`, `Tao` M*/ PETSC_EXTERN PetscErrorCode TaoLineSearchCreate_OWArmijo(TaoLineSearch ls) { TaoLineSearch_OWARMIJO *armP; PetscFunctionBegin; PetscValidHeaderSpecific(ls, TAOLINESEARCH_CLASSID, 1); PetscCall(PetscNew(&armP)); 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->monitor = NULL; ls->ops->setup = NULL; ls->ops->reset = NULL; ls->ops->apply = TaoLineSearchApply_OWArmijo; ls->ops->view = TaoLineSearchView_OWArmijo; ls->ops->destroy = TaoLineSearchDestroy_OWArmijo; ls->ops->setfromoptions = TaoLineSearchSetFromOptions_OWArmijo; PetscFunctionReturn(PETSC_SUCCESS); }