3#include <boost/none.hpp>
4#include <boost/optional.hpp>
92 const static std::string extremumSearch;
93 const static std::string feasibleInstantiationSearch;
94 const static std::string derivativeAtInstantiation;
95 const static std::string learningRate;
96 const static std::string miniBatchSize;
97 const static std::string adamParams;
98 const static std::string averageDecay;
99 const static std::string squaredAverageDecay;
100 const static std::string printJson;
101 const static std::string terminationEpsilon;
102 const static std::string gradientDescentMethod;
103 const static std::string omitInconsequentialParams;
104 const static std::string constraintMethod;
105 boost::optional<derivative::GradientDescentMethod> methodFromString(
const std::string &
str)
const;
106 boost::optional<derivative::GradientDescentConstraintMethod> constraintMethodFromString(
const std::string &
str)
const;
This class represents the settings for Gradient Descent.
boost::optional< std::string > getDerivativeAtInstantiation() const
Retrieves whether an extremum should be found by Gradient Descent.
double getSquaredAverageDecay() const
Retrieves the decay of the squared decaying step average of the ADAM algorithm.
std::string getGradientDescentMethodAsString() const
Retrieves the gradient descent method as a string.
static const std::string moduleName
uint_fast64_t getMiniBatchSize() const
Retrieves the mini batch size of the gradient descent.
boost::optional< derivative::GradientDescentMethod > getGradientDescentMethod() const
Retrieves the gradient descent method.
DerivativeSettings()
Creates a new set of monotonicity checking settings.
double getAverageDecay() const
Retrieves the decay of the decaying step average of the ADAM algorithm.
bool areInconsequentialParametersOmitted() const
Are inconsequential parameters omitted?
boost::optional< derivative::GradientDescentConstraintMethod > getConstraintMethod() const
Retrieves the gradient descent method constraint method.
bool isFeasibleInstantiationSearchSet() const
Retrieves whether a feasible instance should be found by Gradient Descent.
double getTerminationEpsilon() const
Retrieves the termination epsilon.
double getLearningRate() const
Retrieves the learning rate for the gradient descent.
bool isPrintJsonSet() const
Retrieves whether the GradientDescentInstantiationSearcher should print the run as json after finishi...
std::string getConstraintMethodAsString() const
Retrieves the gradient descent method constraint method as a string.
This is the base class of the settings for a particular module.
SettingsType const & getModule()
Get module.