nnet::ModelInterface Class Reference

#include <PointIdAlg.h>

Inheritance diagram for nnet::ModelInterface:

Public Member Functions
virtual	~ModelInterface ()
virtual std::vector< float >	Run (std::vector< std::vector< float >> const &inp2d)=0
virtual std::vector< std::vector< float > >	Run (std::vector< std::vector< std::vector< float >>> const &inps, int samples=-1)

Protected Member Functions
std::string	findFile (const char *fileName) const

Detailed Description

Interface class for various classifier models. Now MLP (NetMaker) and CNN (Keras with simple cpp interface) are supported. Will add interface to Protobuf as soon as Tensorflow may be used from UPS.

Definition at line 50 of file PointIdAlg.h.

Constructor & Destructor Documentation

virtual nnet::ModelInterface::~ModelInterface ( )

inlinevirtual

Definition at line 52 of file PointIdAlg.h.

{}

Member Function Documentation

std::string nnet::ModelInterface::findFile ( const char *  fileName ) const

protected

Definition at line 49 of file PointIdAlg.cxx.

{
  std::string fname_out;
  cet::search_path sp("FW_SEARCH_PATH");
  if (!sp.find_file(fileName, fname_out)) {
    struct stat buffer;
    if (stat(fileName, &buffer) == 0) { fname_out = fileName; }
    else {
      throw art::Exception(art::errors::NotFound) << "Could not find the model file " << fileName;
    }
  }
  return fname_out;
}

virtual std::vector<float> nnet::ModelInterface::Run ( std::vector< std::vector< float >> const &  inp2d )

pure virtual

Implemented in nnet::TfModelInterface, and nnet::KerasModelInterface.

std::vector< std::vector< float > > nnet::ModelInterface::Run ( std::vector< std::vector< std::vector< float >>> const &  inps, int  samples = -1  )

virtual

Reimplemented in nnet::TfModelInterface.

Definition at line 34 of file PointIdAlg.cxx.

{
  if ((samples == 0) || inps.empty() || inps.front().empty() || inps.front().front().empty())
    return std::vector<std::vector<float>>();

  if ((samples == -1) || (samples > (int)inps.size())) { samples = inps.size(); }

  std::vector<std::vector<float>> results;
  for (int i = 0; i < samples; ++i) {
    results.push_back(Run(inps[i]));
  }
  return results;
}

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The documentation for this class was generated from the following files:

• larrecodnn/larrecodnn/ImagePatternAlgs/Tensorflow/PointIdAlg/PointIdAlg.h
• larrecodnn/larrecodnn/ImagePatternAlgs/Tensorflow/PointIdAlg/PointIdAlg.cxx