Browse Source
Put most of the optimistic value iteration code into a new helper file
tempestpy_adaptions
Put most of the optimistic value iteration code into a new helper file
tempestpy_adaptions
Tim Quatmann
5 years ago
2 changed files with 301 additions and 204 deletions
-
226src/storm/solver/IterativeMinMaxLinearEquationSolver.cpp
-
279src/storm/solver/helper/OptimisticValueIterationHelper.h
@ -0,0 +1,279 @@ |
|||
#pragma once |
|||
|
|||
#include <vector> |
|||
#include <boost/optional.hpp> |
|||
|
|||
#include "storm/solver/OptimizationDirection.h" |
|||
#include "storm/solver/SolverStatus.h" |
|||
#include "storm/utility/vector.h" |
|||
#include "storm/utility/ProgressMeasurement.h" |
|||
#include "storm/storage/BitVector.h" |
|||
#include "storm/environment/solver/MinMaxSolverEnvironment.h" |
|||
#include "storm/environment/solver/OviSolverEnvironment.h" |
|||
|
|||
#include "storm/utility/macros.h" |
|||
|
|||
namespace storm { |
|||
|
|||
namespace solver { |
|||
namespace helper { |
|||
namespace oviinternal { |
|||
|
|||
template<typename ValueType> |
|||
ValueType computeMaxAbsDiff(std::vector<ValueType> const& allOldValues, std::vector<ValueType> const& allNewValues, storm::storage::BitVector const& relevantValues) { |
|||
ValueType result = storm::utility::zero<ValueType>(); |
|||
for (auto value : relevantValues) { |
|||
result = storm::utility::max<ValueType>(result, storm::utility::abs<ValueType>(allNewValues[value] - allOldValues[value])); |
|||
} |
|||
return result; |
|||
} |
|||
|
|||
template<typename ValueType> |
|||
ValueType computeMaxAbsDiff(std::vector<ValueType> const& allOldValues, std::vector<ValueType> const& allNewValues) { |
|||
ValueType result = storm::utility::zero<ValueType>(); |
|||
for (uint64_t i = 0; i < allOldValues.size(); ++i) { |
|||
result = storm::utility::max<ValueType>(result, storm::utility::abs<ValueType>(allNewValues[i] - allOldValues[i])); |
|||
} |
|||
return result; |
|||
} |
|||
|
|||
template<typename ValueType> |
|||
ValueType computeMaxRelDiff(std::vector<ValueType> const& allOldValues, std::vector<ValueType> const& allNewValues, storm::storage::BitVector const& relevantValues) { |
|||
ValueType result = storm::utility::zero<ValueType>(); |
|||
for (auto const& i : relevantValues) { |
|||
STORM_LOG_ASSERT(!storm::utility::isZero(allNewValues[i]) || storm::utility::isZero(allOldValues[i]), "Unexpected entry in iteration vector."); |
|||
if (!storm::utility::isZero(allNewValues[i])) { |
|||
result = storm::utility::max<ValueType>(result, storm::utility::abs<ValueType>(allNewValues[i] - allOldValues[i]) / allNewValues[i]); |
|||
} |
|||
} |
|||
return result; |
|||
} |
|||
|
|||
template<typename ValueType> |
|||
ValueType computeMaxRelDiff(std::vector<ValueType> const& allOldValues, std::vector<ValueType> const& allNewValues) { |
|||
ValueType result = storm::utility::zero<ValueType>(); |
|||
for (uint64_t i = 0; i < allOldValues.size(); ++i) { |
|||
STORM_LOG_ASSERT(!storm::utility::isZero(allNewValues[i]) || storm::utility::isZero(allOldValues[i]), "Unexpected entry in iteration vector."); |
|||
if (!storm::utility::isZero(allNewValues[i])) { |
|||
result = storm::utility::max<ValueType>(result, storm::utility::abs<ValueType>(allNewValues[i] - allOldValues[i]) / allNewValues[i]); |
|||
} |
|||
} |
|||
return result; |
|||
} |
|||
|
|||
template<typename ValueType> |
|||
ValueType updateIterationPrecision(storm::Environment const& env, std::vector<ValueType> const& currentX, std::vector<ValueType> const& newX, bool const& relative, boost::optional<storm::storage::BitVector> const& relevantValues) { |
|||
auto factor = storm::utility::convertNumber<ValueType>(env.solver().ovi().getPrecisionUpdateFactor()); |
|||
bool useRelevant = relevantValues.is_initialized() && env.solver().ovi().useRelevantValuesForPrecisionUpdate(); |
|||
if (relative) { |
|||
return (useRelevant ? computeMaxRelDiff(newX, currentX, relevantValues.get()) : computeMaxRelDiff(newX, currentX)) * factor; |
|||
} else { |
|||
return (useRelevant ? computeMaxAbsDiff(newX, currentX, relevantValues.get()) : computeMaxAbsDiff(newX, currentX)) * factor; |
|||
} |
|||
} |
|||
|
|||
template<typename ValueType> |
|||
void guessUpperBoundRelative(std::vector<ValueType> const& x, std::vector<ValueType> &target, ValueType const& relativeBoundGuessingScaler) { |
|||
storm::utility::vector::applyPointwise<ValueType, ValueType>(x, target, [&relativeBoundGuessingScaler] (ValueType const& argument) -> ValueType { return argument * relativeBoundGuessingScaler; }); |
|||
} |
|||
|
|||
template<typename ValueType> |
|||
void guessUpperBoundAbsolute(std::vector<ValueType> const& x, std::vector<ValueType> &target, ValueType const& precision) { |
|||
storm::utility::vector::applyPointwise<ValueType, ValueType>(x, target, [&precision] (ValueType const& argument) -> ValueType { return argument + precision; }); |
|||
} |
|||
|
|||
} |
|||
|
|||
|
|||
/*! |
|||
* Performs Optimistic value iteration. |
|||
* See https://arxiv.org/abs/1910.01100 for more information on this algorithm |
|||
* |
|||
* @tparam ValueType |
|||
* @tparam ValueType |
|||
* @param env |
|||
* @param lowerX Needs to be some arbitrary lower bound on the actual values initially |
|||
* @param upperX Does not need to be an upper bound initially |
|||
* @param auxVector auxiliary storage |
|||
* @param valueIterationCallback Function that should perform standard value iteration on the input vector |
|||
* @param singleIterationCallback Function that should perform a single value iteration step on the input vector e.g. ( x' = min/max(A*x + b)) |
|||
* @param relevantValues If given, we only check the precision at the states with the given indices. |
|||
* @return The status upon termination as well as the number of iterations Also, the maximum (relative/absolute) difference between lowerX and upperX will be 2*epsilon |
|||
* with precision parameters as given by the environment env. |
|||
*/ |
|||
template<typename ValueType, typename ValueIterationCallback, typename SingleIterationCallback> |
|||
std::pair<SolverStatus, uint64_t> solveEquationsOptimisticValueIteration(Environment const& env, std::vector<ValueType>* lowerX, std::vector<ValueType>* upperX, std::vector<ValueType>* auxVector, ValueIterationCallback const& valueIterationCallback, SingleIterationCallback const& singleIterationCallback, boost::optional<storm::storage::BitVector> relevantValues = boost::none) { |
|||
STORM_LOG_ASSERT(lowerX->size() == upperX->size(), "Dimension missmatch."); |
|||
STORM_LOG_ASSERT(lowerX->size() == auxVector->size(), "Dimension missmatch."); |
|||
|
|||
// As we will shuffle pointers around, let's store the original positions here. |
|||
std::vector<ValueType>* initLowerX = lowerX; |
|||
std::vector<ValueType>* initUpperX = upperX; |
|||
std::vector<ValueType>* initAux = auxVector; |
|||
|
|||
uint64_t overallIterations = 0; |
|||
uint64_t lastValueIterationIterations = 0; |
|||
uint64_t currentVerificationIterations = 0; |
|||
uint64_t valueIterationInvocations = 0; |
|||
|
|||
// Get some parameters for the algorithm |
|||
// 2 |
|||
ValueType two = storm::utility::convertNumber<ValueType>(2.0); |
|||
// Relative errors |
|||
bool relative = env.solver().minMax().getRelativeTerminationCriterion(); |
|||
// Goal precision |
|||
ValueType precision = storm::utility::convertNumber<ValueType>(env.solver().minMax().getPrecision()); |
|||
// Desired max difference between upperX and lowerX |
|||
ValueType doublePrecision = precision * two; |
|||
// Upper bound only iterations |
|||
uint64_t upperBoundOnlyIterations = env.solver().ovi().getUpperBoundOnlyIterations(); |
|||
// Maximum number of iterations done overall |
|||
uint64_t maxOverallIterations = env.solver().minMax().getMaximalNumberOfIterations(); |
|||
ValueType relativeBoundGuessingScaler = (storm::utility::one<ValueType>() + storm::utility::convertNumber<ValueType>(env.solver().ovi().getUpperBoundGuessingFactor()) * precision); |
|||
// Initial precision for the value iteration calls |
|||
ValueType iterationPrecision = precision; |
|||
|
|||
SolverStatus status = SolverStatus::InProgress; |
|||
|
|||
while (status == SolverStatus::InProgress && overallIterations < maxOverallIterations) { |
|||
|
|||
// Perform value iteration until convergence |
|||
++valueIterationInvocations; |
|||
auto result = valueIterationCallback(lowerX, auxVector, iterationPrecision, relative, overallIterations, maxOverallIterations); |
|||
lastValueIterationIterations = result.iterations; |
|||
overallIterations += result.iterations; |
|||
|
|||
if (result.status != SolverStatus::Converged) { |
|||
status = result.status; |
|||
} else { |
|||
bool intervalIterationNeeded = false; |
|||
currentVerificationIterations = 0; |
|||
|
|||
if (relative) { |
|||
oviinternal::guessUpperBoundRelative(*lowerX, *upperX, relativeBoundGuessingScaler); |
|||
} else { |
|||
oviinternal::guessUpperBoundAbsolute(*lowerX, *upperX, precision); |
|||
} |
|||
|
|||
bool cancelGuess = false; |
|||
while (status == SolverStatus::InProgress && overallIterations < maxOverallIterations) { |
|||
++overallIterations; |
|||
++currentVerificationIterations; |
|||
// Perform value iteration stepwise for lower bound and guessed upper bound |
|||
|
|||
// Upper bound iteration |
|||
singleIterationCallback(upperX, auxVector, overallIterations); |
|||
// At this point, auxVector contains the old values for the upper bound whereas upperX contains the new ones. |
|||
|
|||
// Compare the new upper bound candidate with the old one |
|||
bool newUpperBoundAlwaysHigherEqual = true; |
|||
bool newUpperBoundAlwaysLowerEqual = true; |
|||
for (uint64_t i = 0; i < upperX->size(); ++i) { |
|||
if ((*auxVector)[i] > (*upperX)[i]) { |
|||
newUpperBoundAlwaysHigherEqual = false; |
|||
} else if ((*auxVector)[i] != (*upperX)[i]) { |
|||
newUpperBoundAlwaysLowerEqual = false; |
|||
} |
|||
} |
|||
if (newUpperBoundAlwaysHigherEqual & !newUpperBoundAlwaysLowerEqual) { |
|||
// All values moved up or stayed the same (but are not the same) |
|||
// That means the guess for an upper bound is actually a lower bound |
|||
iterationPrecision = oviinternal::updateIterationPrecision(env, *auxVector, *upperX, relative, relevantValues); |
|||
// We assume to have a single fixed point. We can thus safely set the new lower bound, to the wrongly guessed upper bound |
|||
// Set lowerX to the upper bound candidate |
|||
std::swap(lowerX, upperX); |
|||
break; |
|||
} else if (newUpperBoundAlwaysLowerEqual) { |
|||
// All values moved down or stayed the same and we have a maximum difference of twice the requested precision |
|||
// We can safely use twice the requested precision, as we calculate the center of both vectors |
|||
bool reachedPrecision; |
|||
if (relevantValues) { |
|||
reachedPrecision = storm::utility::vector::equalModuloPrecision(*lowerX, *upperX, relevantValues.get(), doublePrecision, relative); |
|||
} else { |
|||
reachedPrecision = storm::utility::vector::equalModuloPrecision(*lowerX, *upperX, doublePrecision, relative); |
|||
} |
|||
if (reachedPrecision) { |
|||
status = SolverStatus::Converged; |
|||
break; |
|||
} else { |
|||
// From now on, we keep updating both bounds |
|||
intervalIterationNeeded = true; |
|||
} |
|||
} |
|||
// At this point, the old upper bounds (auxVector) are not needed anymore. |
|||
|
|||
// Check whether we tried this guess for too long |
|||
ValueType scaledIterationCount = storm::utility::convertNumber<ValueType>(currentVerificationIterations) * storm::utility::convertNumber<ValueType>(env.solver().ovi().getMaxVerificationIterationFactor()); |
|||
if (!intervalIterationNeeded && scaledIterationCount >= storm::utility::convertNumber<ValueType>(lastValueIterationIterations)) { |
|||
cancelGuess = true; |
|||
// In this case we will make one more iteration on the lower bound (mainly to obtain a new iterationPrecision) |
|||
} |
|||
|
|||
// Lower bound iteration (only if needed) |
|||
if (cancelGuess || intervalIterationNeeded || currentVerificationIterations > upperBoundOnlyIterations) { |
|||
singleIterationCallback(lowerX, auxVector, overallIterations); |
|||
// At this point, auxVector contains the old values for the lower bound whereas lowerX contains the new ones. |
|||
|
|||
// Check whether the upper and lower bounds have crossed, i.e., the upper bound is smaller than the lower bound. |
|||
bool valuesCrossed = false; |
|||
for (uint64_t i = 0; i < lowerX->size(); ++i) { |
|||
if ((*upperX)[i] < (*lowerX)[i]) { |
|||
valuesCrossed = true; |
|||
break; |
|||
} |
|||
} |
|||
|
|||
if (cancelGuess || valuesCrossed) { |
|||
// A new guess is needed. |
|||
iterationPrecision = oviinternal::updateIterationPrecision(env, *auxVector, *lowerX, relative, relevantValues); |
|||
break; |
|||
} |
|||
} |
|||
} |
|||
} |
|||
} |
|||
|
|||
// Swap the results into the output vectors. |
|||
if (initLowerX == lowerX) { |
|||
// lowerX is already at the correct position. We still have to care for upperX |
|||
if (initUpperX != upperX) { |
|||
// UpperX is not at the correct position. It has to be at the auxVector |
|||
assert(initAux == upperX); |
|||
std::swap(*initUpperX, *initAux); |
|||
} |
|||
} else if (initUpperX == upperX) { |
|||
// UpperX is already at the correct position. |
|||
// We already know that lowerX is at the wrong position. It has to be at the auxVector |
|||
assert(initAux == lowerX); |
|||
std::swap(*initLowerX, *initAux); |
|||
} else if (initAux == auxVector) { |
|||
// We know that upperX and lowerX are swapped. |
|||
assert(initLowerX == upperX); |
|||
assert(initUpperX == lowerX); |
|||
std::swap(*initUpperX, *initLowerX); |
|||
} else { |
|||
// Now we know that all vectors are at the wrong position. There are only two possibilities left |
|||
if (initLowerX == upperX) { |
|||
assert(initUpperX == auxVector); |
|||
assert(initAux == lowerX); |
|||
std::swap(*initLowerX, *initAux); |
|||
std::swap(*initUpperX, *initAux); |
|||
} else { |
|||
assert(initLowerX == auxVector); |
|||
assert(initUpperX == lowerX); |
|||
assert (initAux == upperX); |
|||
std::swap(*initUpperX, *initAux); |
|||
std::swap(*initLowerX, *initAux); |
|||
} |
|||
} |
|||
|
|||
if (overallIterations > maxOverallIterations) { |
|||
status = SolverStatus::MaximalIterationsExceeded; |
|||
} |
|||
|
|||
return {status, overallIterations}; |
|||
} |
|||
} |
|||
} |
|||
} |
|||
|
|||
Write
Preview
Loading…
Cancel
Save
Reference in new issue