- refactored Rbm

git-svn-id: http://moon:8086/svn/software/trunk/projects/Rbm@750 b431acfa-c32f-4a4a-93f1-934dc6c82436
This commit is contained in:
2022-01-07 18:23:43 +00:00
parent ec2b11f7e3
commit 9472bb0a36
+38 -39
View File
@@ -71,54 +71,54 @@ Json::Value Rbm::toJson() const
return rbm; return rbm;
} }
void Rbm::weightUpdate(arma::mat const &v_state, arma::mat &dw, arma::mat &dbh, arma::mat &dbv) void Rbm::weightUpdate(arma::mat const &v_states, arma::mat &dw, arma::mat &dbh, arma::mat &dbv)
{ {
arma::mat hid_probs = toHiddenProbs(v_state); arma::mat h_probs = toHiddenProbs(v_states);
arma::mat vis_probs(dbv.n_rows, dbv.n_cols); arma::mat v_probs(dbv.n_rows, dbv.n_cols);
arma::mat h_state = hid_probs; arma::mat h_states = h_probs;
// Sample hidden // Sample hidden
if (!m_params.doRaoBlackwell) if (!m_params.doRaoBlackwell)
{ {
h_state = sample(hid_probs); h_states = sample(h_probs);
} }
// Update weights (positive phase) // Update weights (positive phase)
dw = v_state.t() * h_state; dw = v_states.t() * h_states;
dbv = sum(v_state, 0); dbv = sum(v_states, 0);
dbh = sum(h_state, 0); dbh = sum(h_states, 0);
for (int gibbs=0; gibbs < m_params.numGibbs; gibbs++) for (int gibbs=0; gibbs < m_params.numGibbs; gibbs++)
{ {
// Create visible reconstruction (a fantasy...) given hid // Create visible reconstruction (a fantasy...) given hid
if (m_params.gibbsDoSampleHidden) if (m_params.gibbsDoSampleHidden)
{ {
vis_probs = toVisibleProbs(sample(hid_probs)); v_probs = toVisibleProbs(sample(h_probs));
} }
else else
{ {
vis_probs = toVisibleProbs(hid_probs); v_probs = toVisibleProbs(h_probs);
} }
// Create hidden representation given v // Create hidden representation given v
if (m_params.gibbsDoSampleVisible) if (m_params.gibbsDoSampleVisible)
{ {
h_state = toHiddenState(sample(vis_probs)); h_states = toHiddenState(sample(v_probs));
} }
else else
{ {
h_state = toHiddenState(vis_probs); h_states = toHiddenState(v_probs);
} }
hid_probs = probsLogistic(h_state); h_probs = probsLogistic(h_states);
} }
// Update weights (negative phase) // Update weights (negative phase)
dw -= vis_probs.t() * hid_probs; dw -= v_probs.t() * h_probs;
dbv -= sum(vis_probs, 0); dbv -= sum(v_probs, 0);
dbh -= sum(hid_probs, 0); dbh -= sum(h_probs, 0);
} }
void Rbm::train(const arma::mat& batch, IListener* pListener) void Rbm::train(const arma::mat& batch, IListener* pListener)
@@ -154,74 +154,73 @@ void Rbm::train(const arma::mat& batch, IListener* pListener)
double weight_decay = m_params.weightDecay/scaler; double weight_decay = m_params.weightDecay/scaler;
#if RBM_TRAIN_FLAT #if RBM_TRAIN_FLAT
arma::mat hid_probs(miniBatchSizeActual, m_bh.n_cols); arma::mat h_probs(miniBatchSizeActual, m_bh.n_cols);
arma::mat vis_probs(miniBatchSizeActual, m_bv.n_cols); arma::mat v_probs(miniBatchSizeActual, m_bv.n_cols);
arma::mat hid_states(miniBatchSizeActual, m_bh.n_cols);
#endif #endif
arma::mat v_states(miniBatchSizeActual, m_bv.n_cols);
arma::mat hid_state(miniBatchSizeActual, m_bh.n_cols);
arma::mat vis_state(miniBatchSizeActual, m_bv.n_cols);
// Create hidden layer base on training data // Create hidden layer base on training data
if (m_params.doSampleBatch) if (m_params.doSampleBatch)
{ {
// When the hidden units are being driven by data, always use stochastic binary states // When the hidden units are being driven by data, always use stochastic binary states
vis_state = sample(miniBatch); v_states = sample(miniBatch);
} }
else else
{ {
vis_state = miniBatch; v_states = miniBatch;
} }
for (int epoch=0; epoch < m_params.numEpochs; epoch++) for (int epoch=0; epoch < m_params.numEpochs; epoch++)
{ {
#if RBM_TRAIN_FLAT #if RBM_TRAIN_FLAT
// Sample hidden // Sample hidden
hid_probs = probsLogistic(toHiddenState(vis_state)); h_probs = probsLogistic(toHiddenState(v_states));
if (m_params.doRaoBlackwell) if (m_params.doRaoBlackwell)
{ {
hid_state = hid_probs; hid_states = h_probs;
} }
else else
{ {
hid_state = sample(hid_probs); hid_states = sample(h_probs);
} }
// Update weights (positive phase) // Update weights (positive phase)
grad_weight = vis_state.t() * hid_state; grad_weight = v_states.t() * hid_states;
grad_bias_v = sum(vis_state, 0); grad_bias_v = sum(v_states, 0);
grad_bias_h = sum(hid_state, 0); grad_bias_h = sum(hid_states, 0);
for (int gibbs=0; gibbs < m_params.numGibbs; gibbs++) for (int gibbs=0; gibbs < m_params.numGibbs; gibbs++)
{ {
// Create visible reconstruction (a fantasy...) given hid // Create visible reconstruction (a fantasy...) given hid
if (m_params.gibbsDoSampleHidden) if (m_params.gibbsDoSampleHidden)
{ {
vis_probs = toVisibleProbs(sample(hid_probs)); v_probs = toVisibleProbs(sample(h_probs));
} }
else else
{ {
vis_probs = toVisibleProbs(hid_probs); v_probs = toVisibleProbs(h_probs);
} }
// Create hidden representation given v // Create hidden representation given v
if (m_params.gibbsDoSampleVisible) if (m_params.gibbsDoSampleVisible)
{ {
hid_state = toHiddenState(sample(vis_probs)); hid_states = toHiddenState(sample(v_probs));
} }
else else
{ {
hid_state = toHiddenState(vis_probs); hid_states = toHiddenState(v_probs);
} }
hid_probs = probsLogistic(hid_state); h_probs = probsLogistic(hid_states);
} }
// Update weights (negative phase) // Update weights (negative phase)
grad_weight -= vis_probs.t() * hid_probs; grad_weight -= v_probs.t() * h_probs;
grad_bias_v -= sum(vis_probs, 0); grad_bias_v -= sum(v_probs, 0);
grad_bias_h -= sum(hid_probs, 0); grad_bias_h -= sum(h_probs, 0);
#else #else
weightUpdate(vis_state, grad_weight, grad_bias_h, grad_bias_v); weightUpdate(v_states, grad_weight, grad_bias_h, grad_bias_v);
#endif #endif
penalty_weights = weight_decay*arma::sign(m_whv); penalty_weights = weight_decay*arma::sign(m_whv);
@@ -244,7 +243,7 @@ void Rbm::train(const arma::mat& batch, IListener* pListener)
lastProgress = status.progress; lastProgress = status.progress;
// Calculate error // Calculate error
arma::mat diffErr = miniBatch - toVisibleProbs(toHiddenProbs(vis_state)); arma::mat diffErr = miniBatch - toVisibleProbs(toHiddenProbs(v_states));
arma::mat diffErr_squared = diffErr % diffErr; arma::mat diffErr_squared = diffErr % diffErr;
status.err = accu(diffErr_squared)/diffErr_squared.n_elem; status.err = accu(diffErr_squared)/diffErr_squared.n_elem;
if (pListener) if (pListener)