CovarianceFunctionBase.h

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//* This file is part of the MOOSE framework
//* https://mooseframework.inl.gov
//*
//* All rights reserved, see COPYRIGHT for full restrictions
//* https://github.com/idaholab/moose/blob/master/COPYRIGHT
//*
//* Licensed under LGPL 2.1, please see LICENSE for details
//* https://www.gnu.org/licenses/lgpl-2.1.html
#ifdef MOOSE_LIBTORCH_ENABLED

#pragma once

#include "StochasticToolsApp.h"
#include "MooseObject.h"
#include "CovarianceInterface.h"

class CovarianceFunctionBase : public MooseObject, public CovarianceInterface
{
public:
  using HyperParameterMap = std::unordered_map<std::string, torch::Tensor>;

  static bool isScalarHyperParameter(const torch::Tensor & tensor);

  static bool isVectorHyperParameter(const torch::Tensor & tensor);

  static InputParameters validParams();
  CovarianceFunctionBase(const InputParameters & parameters);

  virtual void computeCovarianceMatrix(torch::Tensor & K,
                                       const torch::Tensor & x,
                                       const torch::Tensor & xp,
                                       const bool is_self_covariance) const = 0;

  void loadHyperParamMap(const HyperParameterMap & map);

  void buildHyperParamMap(HyperParameterMap & map) const;

  virtual bool
  getTuningData(const std::string & name, unsigned int & size, Real & min, Real & max) const;

  void dependentCovarianceTypes(std::map<UserObjectName, std::string> & name_type_map) const;

  const std::vector<UserObjectName> & dependentCovarianceNames() const
  {
    return _dependent_covariance_names;
  }

  virtual bool computedKdhyper(torch::Tensor & dKdhp,
                               const torch::Tensor & x,
                               const std::string & hyper_param_name,
                               unsigned int ind) const;

  virtual bool isTunable(const std::string & name) const;

  unsigned int numOutputs() const { return _num_outputs; }

protected:
  torch::Tensor &
  addRealHyperParameter(const std::string & name, const Real value, const bool is_tunable);

  torch::Tensor & addVectorRealHyperParameter(const std::string & name,
                                              const std::vector<Real> & value,
                                              const bool is_tunable);

  HyperParameterMap _hyperparameters;

  std::unordered_set<std::string> _tunable_hp;

  const unsigned int _num_outputs;

  const std::vector<UserObjectName> _dependent_covariance_names;

  std::vector<std::string> _dependent_covariance_types;

  std::vector<CovarianceFunctionBase *> _covariance_functions;
};

#endif