meta_info_extractor.hpp

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#ifndef MLPACK_CORE_CV_META_INFO_EXTRACTOR_HPP
#define MLPACK_CORE_CV_META_INFO_EXTRACTOR_HPP
 
#include <type_traits>
 
#include <mlpack/core.hpp>
#include <mlpack/core/util/sfinae_utility.hpp>
 
namespace mlpack {
namespace cv {
 
template<typename MatType,
         typename PredictionsType,
         typename WeightsType,
         bool DatasetInfo,
         bool NumClasses>
struct TrainForm;
 
#if _MSC_VER <= 1916
// Visual Studio 2017 version 15.9 or older.
// Due to an internal MSVC compiler bug (MSVC ) we can't use two parameter
// packs. So we have to write multiple TrainFormBase forms.
template<typename PT, typename WT, typename T1, typename T2>
struct TrainFormBase4
{
  using PredictionsType = PT;
  using WeightsType = WT;
 
  /* A minimum number of parameters that should be inferred */
  static const size_t MinNumberOfAdditionalArgs = 1;
 
  template<typename Class, typename RT, typename... Ts>
  using Type = RT(Class::*)(T1, T2, Ts...);
};
 
template<typename PT, typename WT, typename T1, typename T2, typename T3>
struct TrainFormBase5
{
  using PredictionsType = PT;
  using WeightsType = WT;
 
  /* A minimum number of parameters that should be inferred */
  static const size_t MinNumberOfAdditionalArgs = 1;
 
  template<typename Class, typename RT, typename... Ts>
  using Type = RT(Class::*)(T1, T2, T3, Ts...);
};
 
template<typename PT, typename WT, typename T1, typename T2, typename T3,
    typename T4>
struct TrainFormBase6
{
  using PredictionsType = PT;
  using WeightsType = WT;
 
  /* A minimum number of parameters that should be inferred */
  static const size_t MinNumberOfAdditionalArgs = 1;
 
  template<typename Class, typename RT, typename... Ts>
  using Type = RT(Class::*)(T1, T2, T3, T4, Ts...);
};
 
template<typename PT, typename WT, typename T1, typename T2, typename T3,
    typename T4, typename T5>
struct TrainFormBase7
{
  using PredictionsType = PT;
  using WeightsType = WT;
 
  /* A minimum number of parameters that should be inferred */
  static const size_t MinNumberOfAdditionalArgs = 1;
 
  template<typename Class, typename RT, typename... Ts>
  using Type = RT(Class::*)(T1, T2, T3, T4, T5, Ts...);
};
 
template<typename MT, typename PT>
struct TrainForm<MT, PT, void, false, false> : public TrainFormBase4<PT, void,
    const MT&, const PT&> {};
 
template<typename MT, typename PT>
struct TrainForm<MT, PT, void, true, false> : public TrainFormBase5<PT, void,
    const MT&, const data::DatasetInfo&, const PT&> {};
 
template<typename MT, typename PT, typename WT>
struct TrainForm<MT, PT, WT, false, false> : public TrainFormBase5<PT, WT,
    const MT&, const PT&, const WT&> {};
 
template<typename MT, typename PT, typename WT>
struct TrainForm<MT, PT, WT, true, false> : public TrainFormBase6<PT, WT,
    const MT&, const data::DatasetInfo&, const PT&, const WT&> {};
 
template<typename MT, typename PT>
struct TrainForm<MT, PT, void, false, true> : public TrainFormBase5<PT, void,
    const MT&, const PT&, const size_t> {};
 
template<typename MT, typename PT>
struct TrainForm<MT, PT, void, true, true> : public TrainFormBase6<PT, void,
    const MT&, const data::DatasetInfo&, const PT&, const size_t> {};
 
template<typename MT, typename PT, typename WT>
struct TrainForm<MT, PT, WT, false, true> : public TrainFormBase6<PT, WT,
    const MT&, const PT&, const size_t, const WT&> {};
 
template<typename MT, typename PT, typename WT>
struct TrainForm<MT, PT, WT, true, true> : public TrainFormBase7<PT, WT,
    const MT&, const data::DatasetInfo&, const PT&,
    const size_t, const WT&> {};
#else
template<typename PT, typename WT, typename... SignatureParams>
struct TrainFormBase
{
  using PredictionsType = PT;
  using WeightsType = WT;
 
  /* A minimum number of parameters that should be inferred */
  static const size_t MinNumberOfAdditionalArgs = 1;
 
  template<typename Class, typename RT, typename... Ts>
  using Type = RT(Class::*)(SignatureParams..., Ts...);
};
 
template<typename MT, typename PT>
struct TrainForm<MT, PT, void, false, false> : public TrainFormBase<PT, void,
    const MT&, const PT&> {};
 
template<typename MT, typename PT>
struct TrainForm<MT, PT, void, true, false> : public TrainFormBase<PT, void,
    const MT&, const data::DatasetInfo&, const PT&> {};
 
template<typename MT, typename PT, typename WT>
struct TrainForm<MT, PT, WT, false, false> : public TrainFormBase<PT, WT,
    const MT&, const PT&, const WT&> {};
 
template<typename MT, typename PT, typename WT>
struct TrainForm<MT, PT, WT, true, false> : public TrainFormBase<PT, WT,
    const MT&, const data::DatasetInfo&, const PT&, const WT&> {};
 
template<typename MT, typename PT>
struct TrainForm<MT, PT, void, false, true> : public TrainFormBase<PT, void,
    const MT&, const PT&, const size_t> {};
 
template<typename MT, typename PT>
struct TrainForm<MT, PT, void, true, true> : public TrainFormBase<PT, void,
    const MT&, const data::DatasetInfo&, const PT&, const size_t> {};
 
template<typename MT, typename PT, typename WT>
struct TrainForm<MT, PT, WT, false, true> : public TrainFormBase<PT, WT,
    const MT&, const PT&, const size_t, const WT&> {};
 
template<typename MT, typename PT, typename WT>
struct TrainForm<MT, PT, WT, true, true> : public TrainFormBase<PT, WT,
    const MT&, const data::DatasetInfo&, const PT&,
    const size_t, const WT&> {};
#endif
 
/* A struct for indication that a right method form can't be found */
struct NotFoundMethodForm
{
  using PredictionsType = void*;
  using WeightsType = void*;
};
 
template<typename MLAlgorithm,
         template<class, template<class...> class, size_t> class... HMFs>
struct SelectMethodForm;
 
template<typename MLAlgorithm,
         template<class, template<class...> class, size_t> class HasMethodForm,
         template<class, template<class...> class, size_t> class... HMFs>
struct SelectMethodForm<MLAlgorithm, HasMethodForm, HMFs...>
{
  template<typename... Forms>
  class From
  {
    /* Declaration and definition of Implementation for the case when
     * RemainingForms are empty */
    template<typename... RemainingForms>
    struct Implementation
    {
      using NextSMF = SelectMethodForm<MLAlgorithm, HMFs...>;
      using Type = typename NextSMF::template From<Forms...>::Type;
    };
 
    /* The case when there is at least one remaining form */
    template<typename Form, typename... RemainingForms>
    struct Implementation<Form, RemainingForms...>
    {
      using Type = typename std::conditional<
          HasMethodForm<MLAlgorithm, Form::template Type,
              Form::MinNumberOfAdditionalArgs>::value,
          Form,
          typename Implementation<RemainingForms...>::Type>::type;
    };
 
   public:
    using Type = typename Implementation<Forms...>::Type;
  };
};
 
template<typename MLAlgorithm>
struct SelectMethodForm<MLAlgorithm>
{
  template<typename... Forms>
  struct From
  {
    using Type = NotFoundMethodForm;
  };
};
 
template<typename MLAlgorithm,
         typename MT = arma::mat,
         typename PT = arma::Row<size_t>,
         typename WT = arma::rowvec>
class MetaInfoExtractor
{
  /* Defining type functions that check presence of Train methods of a given
   * form. Defining such functions for templated and non-templated Train
   * methods. */
  HAS_METHOD_FORM(Train, HasTrain);
  HAS_METHOD_FORM(template Train<>, HasTTrain);
  HAS_METHOD_FORM(template Train<const MT&>, HasMTrain);
  HAS_METHOD_FORM(SINGLE_ARG(template Train<const MT&, const PT&>), HasMPTrain);
  HAS_METHOD_FORM(SINGLE_ARG(template Train<const MT&, const PT&, const WT&>),
      HasMPWTrain);
 
  /* Forms of Train for regression algorithms */
  using TF1 = TrainForm<MT, arma::rowvec, void, false, false>;
  using TF2 = TrainForm<MT, arma::mat, void, false, false>;
  using TF3 = TrainForm<MT, PT, void, false, false>;
 
  /* Forms of Train for classification algorithms */
  using TF4 = TrainForm<MT, PT, void, false, true>;
  using TF5 = TrainForm<MT, PT, void, true, true>;
 
  /* Forms of Train with weights for regression algorithms */
  using WTF1 = TrainForm<MT, arma::rowvec, WT, false, false>;
  using WTF2 = TrainForm<MT, arma::mat, WT, false, false>;
  using WTF3 = TrainForm<MT, PT, WT, false, false>;
 
  /* Forms of Train with weights for classification algorithms */
  using WTF4 = TrainForm<MT, PT, WT, false, true>;
  using WTF5 = TrainForm<MT, PT, WT, true, true>;
 
  /* A short alias for a type function that selects a right method form */
  template<typename... MethodForms>
  using Select = typename SelectMethodForm<MLAlgorithm, HasTrain, HasTTrain,
      HasMTrain, HasMPTrain, HasMPWTrain>::template From<MethodForms...>;
 
  /* An indication whether a method form is selected */
  template<typename... MFs /* MethodForms */>
  using Selects = typename std::conditional<
      std::is_same<typename Select<MFs...>::Type, NotFoundMethodForm>::value,
      std::false_type, std::true_type>::type;
 
 public:
  using PredictionsType =
      typename Select<TF1, TF2, TF3, TF4, TF5>::Type::PredictionsType;
 
  using WeightsType =
      typename Select<WTF1, WTF2, WTF3, WTF4, WTF5>::Type::WeightsType;
 
  static const bool IsSupported = !std::is_same<PredictionsType, void*>::value;
 
  static const bool SupportsWeights = !std::is_same<WeightsType, void*>::value;
 
  static const bool TakesDatasetInfo = Selects<TF5>::value;
 
  static const bool TakesNumClasses = Selects<TF4, TF5>::value;
};
 
} // namespace cv
} // namespace mlpack
 
#endif