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- simplified initial v_states generation

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git-svn-id: http://moon:8086/svn/software/trunk/projects/Rbm@756 b431acfa-c32f-4a4a-93f1-934dc6c82436
This commit is contained in:
jens
2022-01-08 11:23:31 +00:00
parent 91bfa0e6ec
commit 1698ce0a1b
3 changed files with 809122 additions and 809109 deletions
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source/Rbm.cpp
+30 -17
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@@ -71,17 +71,6 @@ Json::Value Rbm::toJson() const
return rbm;
}
void Rbm::weightUpdate(arma::mat const &v_states, arma::mat const &c_states, arma::mat &dwhv, arma::mat &dwhc, arma::mat &dbh, arma::mat &dbv, arma::mat &dbc)
{
arma::mat hv_states = v_to_h(v_states);
arma::mat hc_states = c_to_h(c_states);
arma::mat h_states = hv_states + hc_states;
arma::mat h_probs = prob(h_states);
}
void Rbm::gibbs(arma::mat &h_probs, arma::mat &v_probs)
{
for (int gibbs=0; gibbs < m_params.numGibbs; gibbs++)
@@ -108,8 +97,36 @@ void Rbm::gibbs(arma::mat &h_probs, arma::mat &v_probs)
}
}
void weightUpdate(arma::mat const &v_states, arma::mat const &c_states, arma::mat &dwhv, arma::mat &dwhc, arma::mat &dbh, arma::mat &dbv, arma::mat &dbc)
void Rbm::weightUpdate(arma::mat const &v_states, arma::mat const &c_states, arma::mat &dwhv, arma::mat &dwhc, arma::mat &dbh, arma::mat &dbv, arma::mat &dbc)
{
arma::mat v_probs(v_states);
arma::mat hv_states = v_to_h(v_states);
arma::mat hc_states = c_to_h(c_states);
arma::mat h_states = hv_states + hc_states;
arma::mat h_probs = prob(h_states);
// Sample hidden
if (m_params.doRaoBlackwell)
{
h_states = h_probs;
}
else
{
h_states = sample(h_probs);
}
// Update weights (positive phase)
dwhv = v_states.t() * h_states;
dbv = sum(v_states, 0);
dbh = sum(h_states, 0);
gibbs(h_probs, v_probs);
// Update weights (negative phase)
dwhv -= v_probs.t() * h_probs;
dbv -= sum(v_probs, 0);
dbh -= sum(h_probs, 0);
}
@@ -179,7 +196,7 @@ void Rbm::train(const arma::mat& batch, IListener* pListener)
arma::mat v_probs(miniBatchSizeActual, m_bv.n_cols);
arma::mat hid_states(miniBatchSizeActual, m_bh.n_cols);
#endif
arma::mat v_states(miniBatchSizeActual, m_bv.n_cols);
arma::mat v_states(miniBatch);
// Create hidden layer base on training data
if (m_params.doSampleBatch)
@@ -187,10 +204,6 @@ void Rbm::train(const arma::mat& batch, IListener* pListener)
// When the hidden units are being driven by data, always use stochastic binary states
v_states = sample(miniBatch);
}
else
{
v_states = miniBatch;
}
for (int epoch=0; epoch < m_params.numEpochs; epoch++)
{