Separated IVector machine initialization from IVector trainer initialization

bob/learn/em/cpp/IVectorTrainer.cpp

@@ -49,7 +49,17 @@ bob::learn::em::IVectorTrainer::~IVectorTrainer()
 void bob::learn::em::IVectorTrainer::initialize(
   bob::learn::em::IVectorMachine& machine)
 {
+  // Initializes \f$T\f$ and \f$\Sigma\f$ of the machine
+  blitz::Array<double,2>& T = machine.updateT();
+  bob::core::array::randn(*m_rng, T);
+  blitz::Array<double,1>& sigma = machine.updateSigma();
+  sigma = machine.getUbm()->getVarianceSupervector();
+  machine.precompute();
+}
 
+void bob::learn::em::IVectorTrainer::resetAccumulators(const bob::learn::em::IVectorMachine& machine)
+{
+   // Resize the accumulator
   const int C = machine.getNGaussians();
   const int D = machine.getNInputs();
   const int Rt = machine.getDimRt();
@@ -75,14 +85,17 @@ void bob::learn::em::IVectorTrainer::initialize(
   if (m_update_sigma)
     m_tmp_dd1.resize(D,D);
 
-  // Initializes \f$T\f$ and \f$\Sigma\f$ of the machine
-  blitz::Array<double,2>& T = machine.updateT();
-  bob::core::array::randn(*m_rng, T);
-  blitz::Array<double,1>& sigma = machine.updateSigma();
-  sigma = machine.getUbm()->getVarianceSupervector();
-  machine.precompute();
+  // initialize with 0
+  m_acc_Nij_wij2 = 0.;
+  m_acc_Fnormij_wij = 0.;
+  if (m_update_sigma)
+  {
+    m_acc_Nij = 0.;
+    m_acc_Snormij = 0.;
+  }
 }
 
+
 void bob::learn::em::IVectorTrainer::eStep(
   bob::learn::em::IVectorMachine& machine,
   const std::vector<bob::learn::em::GMMStats>& data)
@@ -91,13 +104,8 @@ void bob::learn::em::IVectorTrainer::eStep(
   const int C = machine.getNGaussians();
 
   // Reinitializes accumulators to 0
-  m_acc_Nij_wij2 = 0.;
-  m_acc_Fnormij_wij = 0.;
-  if (m_update_sigma)
-  {
-    m_acc_Nij = 0.;
-    m_acc_Snormij = 0.;
-  }
+  resetAccumulators(machine);
+
   for (std::vector<bob::learn::em::GMMStats>::const_iterator it = data.begin();
        it != data.end(); ++it)
   {
@@ -179,7 +187,7 @@ bob::learn::em::IVectorTrainer& bob::learn::em::IVectorTrainer::operator=
   (const bob::learn::em::IVectorTrainer &other)
 {
   if (this != &other)
-  {    
+  {
     m_update_sigma = other.m_update_sigma;
 
     m_acc_Nij_wij2.reference(bob::core::array::ccopy(other.m_acc_Nij_wij2));
@@ -225,4 +233,3 @@ bool bob::learn::em::IVectorTrainer::is_similar_to
          bob::core::array::isClose(m_acc_Nij, other.m_acc_Nij, r_epsilon, a_epsilon) &&
          bob::core::array::isClose(m_acc_Snormij, other.m_acc_Snormij, r_epsilon, a_epsilon);
 }
-

bob/learn/em/include/bob.learn.em/IVectorTrainer.h

@@ -51,6 +51,12 @@ class IVectorTrainer
      */
     virtual void initialize(bob::learn::em::IVectorMachine& ivector);
 
+    /**
+     * @brief Reset the statistics accumulators
+     * to the correct size and a value of zero.
+     */
+    void resetAccumulators(const bob::learn::em::IVectorMachine& ivector);
+
     /**
      * @brief Calculates statistics across the dataset,
      * and saves these as: