keras::LayerConv2D Class Reference

#include "/cvmfs/nova-development.opensciencegrid.org/novasoft/releases/N21-01-21/ExoticsTriggers/KerasModel.h"

Inheritance diagram for keras::LayerConv2D:

Public Member Functions
	LayerConv2D ()
void	load_weights (std::ifstream &fin)
keras::DataChunk *	compute_output (keras::DataChunk *)
virtual unsigned int	get_input_rows () const
virtual unsigned int	get_input_cols () const
virtual unsigned int	get_output_units () const
	LayerConv2D ()
void	load_weights (std::ifstream &fin)
keras::DataChunk *	compute_output (keras::DataChunk *)
virtual unsigned int	get_input_rows () const
virtual unsigned int	get_input_cols () const
virtual unsigned int	get_output_units () const
std::string	get_name ()
std::string	get_name ()

Public Attributes
std::vector< std::vector< std::vector< std::vector< float > > > >	m_kernels
std::vector< float >	m_bias
std::string	m_border_mode
int	m_kernels_cnt
int	m_depth
int	m_rows
int	m_cols
std::string	m_name

Detailed Description

Definition at line 164 of file KerasModel.h.

Constructor & Destructor Documentation

keras::LayerConv2D::LayerConv2D ( )

inline

Definition at line 166 of file KerasModel.h.

References fin.

: Layer("Conv2D") {}

keras::LayerConv2D::LayerConv2D ( )

inline

Definition at line 164 of file KerasModel.h.

References fin.

: Layer("Conv2D") {}

Member Function Documentation

keras::DataChunk* keras::LayerConv2D::compute_output ( keras::DataChunk *  )

virtual

Implements keras::Layer.

keras::DataChunk * keras::LayerConv2D::compute_output ( keras::DataChunk *  dc )

virtual

Implements keras::Layer.

Definition at line 278 of file KerasModel.cxx.

References keras::conv_single_depth_same(), keras::conv_single_depth_valid(), keras::DataChunk::get_3d(), MECModelEnuComparisons::i, calib::j, m, confusionMatrixTree::out, keras::DataChunk::set_data(), gen_hdf5record::size, tmp, submit_syst::x, and submit_syst::y.

Referenced by keras::missing_activation_impl().

                                                                   {

  unsigned int st_x = (m_kernels[0][0].size()-1)/2;
  unsigned int st_y = (m_kernels[0][0][0].size()-1)/2;
  vector< vector< vector<float> > > y_ret;
  auto const & im = dc->get_3d();

  size_t size_x = (m_border_mode == "valid")? im[0].size() - 2 * st_x : im[0].size();
  size_t size_y = (m_border_mode == "valid")? im[0][0].size() - 2 * st_y: im[0][0].size();
  for(unsigned int i = 0; i < m_kernels.size(); ++i) { // depth
    vector<vector<float> > tmp;
    tmp.reserve(size_x);
    for(unsigned int j = 0; j < size_x; ++j) { // rows
      tmp.emplace_back(vector<float>(size_y, 0.0));
    }
    y_ret.push_back(tmp);
  }

  for(unsigned int j = 0; j < m_kernels.size(); ++j) { // loop over kernels
    for(unsigned int m = 0; m < im.size(); ++m) { // loope over image depth

      vector<vector<float> > tmp_w = (m_border_mode == "valid")?
        keras::conv_single_depth_valid(im[m], m_kernels[j][m]) :
        keras::conv_single_depth_same(im[m], m_kernels[j][m]);

      for(unsigned int x = 0; x < tmp_w.size(); ++x) {
        for(unsigned int y = 0; y < tmp_w[0].size(); ++y) {
          y_ret[j][x][y] += tmp_w[x][y];
        }
      }
    }

    for(unsigned int x = 0; x < y_ret[0].size(); ++x) {
      for(unsigned int y = 0; y < y_ret[0][0].size(); ++y) {
        y_ret[j][x][y] += m_bias[j];
      }
    }
  }

  keras::DataChunk *out = new keras::DataChunk2D();
  out->set_data(y_ret);
  return out;
}

virtual unsigned int keras::LayerConv2D::get_input_cols ( ) const

inlinevirtual

Implements keras::Layer.

Definition at line 172 of file KerasModel.h.

{ return m_cols; }

virtual unsigned int keras::LayerConv2D::get_input_cols ( ) const

inlinevirtual

Implements keras::Layer.

Definition at line 174 of file KerasModel.h.

{ return m_cols; }

virtual unsigned int keras::LayerConv2D::get_input_rows ( ) const

inlinevirtual

Implements keras::Layer.

Definition at line 171 of file KerasModel.h.

{ return m_rows; }

virtual unsigned int keras::LayerConv2D::get_input_rows ( ) const

inlinevirtual

Implements keras::Layer.

Definition at line 173 of file KerasModel.h.

{ return m_rows; }

std::string keras::Layer::get_name ( )

inlineinherited

Definition at line 116 of file KerasModel.h.

References string.

{ return m_name; }

std::string keras::Layer::get_name ( )

inlineinherited

Definition at line 118 of file KerasModel.h.

{ return m_name; }

virtual unsigned int keras::LayerConv2D::get_output_units ( ) const

inlinevirtual

Implements keras::Layer.

Definition at line 173 of file KerasModel.h.

References string.

{ return m_kernels_cnt; }

virtual unsigned int keras::LayerConv2D::get_output_units ( ) const

inlinevirtual

Implements keras::Layer.

Definition at line 175 of file KerasModel.h.

{ return m_kernels_cnt; }

void keras::LayerConv2D::load_weights ( std::ifstream &  fin )

virtual

Implements keras::Layer.

void keras::LayerConv2D::load_weights ( std::ifstream &  fin )

virtual

Implements keras::Layer.

Definition at line 40 of file KerasModel.cxx.

References plot_validation_datamc::c, d, r(), and compare_h5_caf::skip.

                                                    {
  char tmp_char = ' ';
  string tmp_str = "";
  float tmp_float;
  bool skip = false;
  fin >> m_kernels_cnt >> m_depth >> m_rows >> m_cols >> m_border_mode;
  if (m_border_mode == "[") { m_border_mode = "valid"; skip = true; }

  // reading kernel weights
  for(int k = 0; k < m_kernels_cnt; ++k) {
    vector<vector<vector<float> > > tmp_depths;
    for(int d = 0; d < m_depth; ++d) {
      vector<vector<float> > tmp_single_depth;
      for(int r = 0; r < m_rows; ++r) {
        if (!skip) { fin >> tmp_char; } // for '['
        else { skip = false; }
        vector<float> tmp_row;
        for(int c = 0; c < m_cols; ++c) {
          fin >> tmp_float;
          tmp_row.push_back(tmp_float);
        }
        fin >> tmp_char; // for ']'
        tmp_single_depth.push_back(tmp_row);
      }
      tmp_depths.push_back(tmp_single_depth);
    }
    m_kernels.push_back(tmp_depths);
  }
  // reading kernel biases
  fin >> tmp_char; // for '['
  for(int k = 0; k < m_kernels_cnt; ++k) {
    fin >> tmp_float;
    m_bias.push_back(tmp_float);
  }
  fin >> tmp_char; // for ']'

}

Member Data Documentation

std::vector< float > keras::LayerConv2D::m_bias

Definition at line 171 of file KerasModel.h.

std::string keras::LayerConv2D::m_border_mode

Definition at line 177 of file KerasModel.h.

int keras::LayerConv2D::m_cols

Definition at line 181 of file KerasModel.h.

int keras::LayerConv2D::m_depth

Definition at line 179 of file KerasModel.h.

std::vector< std::vector< std::vector< std::vector< float > > > > keras::LayerConv2D::m_kernels

Definition at line 170 of file KerasModel.h.

int keras::LayerConv2D::m_kernels_cnt

Definition at line 178 of file KerasModel.h.

std::string keras::Layer::m_name

inherited

Definition at line 119 of file KerasModel.h.

int keras::LayerConv2D::m_rows

Definition at line 180 of file KerasModel.h.

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

• /cvmfs/nova-development.opensciencegrid.org/novasoft/releases/N21-01-21/ExoticsTriggers/KerasModel.h
• /cvmfs/nova-development.opensciencegrid.org/novasoft/releases/N21-01-21/ExoticsTriggers/KerasModel.cxx