keras::LayerDense Class Reference

#include <keras_model.h>

Inheritance diagram for keras::LayerDense:

Public Member Functions
	LayerDense ()
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
Public Member Functions inherited from keras::Layer
	Layer (std::string name)
virtual	~Layer ()
std::string	get_name ()

Public Attributes
std::vector< std::vector< float > >	m_weights
std::vector< float >	m_bias
int	m_input_cnt
int	m_neurons
Public Attributes inherited from keras::Layer
std::string	m_name

Detailed Description

Definition at line 197 of file keras_model.h.

Constructor & Destructor Documentation

keras::LayerDense::LayerDense ( )

inline

Definition at line 199 of file keras_model.h.

: Layer("Dense") {}

Member Function Documentation

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

virtual

Implements keras::Layer.

Definition at line 363 of file keras_model.cc.

                                                                  {
  //cout << "weights: input size " << m_weights.size() << endl;
  //cout << "weights: neurons size " << m_weights[0].size() << endl;
  //cout << "bias " << m_bias.size() << endl;
  size_t size = m_weights[0].size();
  size_t size8 = size >> 3;

  keras::DataChunkFlat *out = new DataChunkFlat(size, 0);
  float * y_ret = out->get_1d_rw().data();

  auto const & im = dc->get_1d();

  for (size_t j = 0; j < m_weights.size(); ++j) { // iter over input
    const float * w = m_weights[j].data();
    float p = im[j];
    size_t k = 0;
    for (size_t i = 0; i < size8; ++i) { // iter over neurons
      y_ret[k]   += w[k]   * p;          // vectorize if you can
      y_ret[k+1] += w[k+1] * p;
      y_ret[k+2] += w[k+2] * p;
      y_ret[k+3] += w[k+3] * p;
      y_ret[k+4] += w[k+4] * p;
      y_ret[k+5] += w[k+5] * p;
      y_ret[k+6] += w[k+6] * p;
      y_ret[k+7] += w[k+7] * p;
      k += 8;
    }
    while (k < size) { y_ret[k] += w[k] * p; ++k; }
  }
  for (size_t i = 0; i < size; ++i) { // add biases
    y_ret[i] += m_bias[i];
  }

  return out;
}

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

inlinevirtual

Implements keras::Layer.

Definition at line 207 of file keras_model.h.

{ return m_input_cnt; }

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

inlinevirtual

Implements keras::Layer.

Definition at line 206 of file keras_model.h.

{ return 1; } // flat, just one row

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

inlinevirtual

Implements keras::Layer.

Definition at line 208 of file keras_model.h.

{ return m_neurons; }

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

virtual

Implements keras::Layer.

Definition at line 91 of file keras_model.cc.

                                                   {
  fin >> m_input_cnt >> m_neurons;
  float tmp_float;
  char tmp_char = ' ';
  for(int i = 0; i < m_input_cnt; ++i) {
    vector<float> tmp_n;
    fin >> tmp_char; // for '['
    for(int n = 0; n < m_neurons; ++n) {
      fin >> tmp_float;
      tmp_n.push_back(tmp_float);
    }
    fin >> tmp_char; // for ']'
    m_weights.push_back(tmp_n);
  }
  cout << "weights " << m_weights.size() << endl;
  fin >> tmp_char; // for '['
  for(int n = 0; n < m_neurons; ++n) {
    fin >> tmp_float;
    m_bias.push_back(tmp_float);
  }
  fin >> tmp_char; // for ']'
  cout << "bias " << m_bias.size() << endl;

}

Member Data Documentation

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

Definition at line 204 of file keras_model.h.

int keras::LayerDense::m_input_cnt

Definition at line 210 of file keras_model.h.

int keras::LayerDense::m_neurons

Definition at line 211 of file keras_model.h.

std::vector<std::vector<float> > keras::LayerDense::m_weights

Definition at line 203 of file keras_model.h.

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

• larrecodnn/larrecodnn/ImagePatternAlgs/Keras/keras_model.h
• larrecodnn/larrecodnn/ImagePatternAlgs/Keras/keras_model.cc