moses-smt/mosesdecoder
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add parameter --delay-updates

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This commit is contained in:
Eva Hasler 2012-01-14 15:56:16 +00:00
parent 1551f44879
commit a050992abd
4 changed files with 50 additions and 19 deletions
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37
mira/Main.cpp
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@ -121,6 +121,7 @@ int main(int argc, char** argv) {
float max_length_dev_reference;
float relax_BP;
bool stabiliseLength;
bool delayUpdates;
po::options_description desc("Allowed options");
desc.add_options()
("accumulate-weights", po::value<bool>(&accumulateWeights)->default_value(false), "Accumulate and average weights over all epochs")
@ -135,6 +136,7 @@ int main(int argc, char** argv) {
("core-weights", po::value<string>(&coreWeightFile), "Weight file containing the core weights (already tuned, have to be non-zero)")
("decoder-settings", po::value<string>(&decoder_settings)->default_value(""), "Decoder settings for tuning runs")
("decr-learning-rate", po::value<float>(&decrease_learning_rate)->default_value(0),"Decrease learning rate by the given value after every epoch")
("delay-updates", po::value<bool>(&delayUpdates)->default_value(false), "Delay all updates until the end of an epoch")
("distinct-nbest", po::value<bool>(&distinctNbest)->default_value(true), "Use n-best list with distinct translations in inference step")
("epochs,e", po::value<size_t>(&epochs)->default_value(10), "Number of epochs")
("fear-n", po::value<int>(&fear_n)->default_value(-1), "Number of fear translations used")
@ -413,6 +415,9 @@ int main(int argc, char** argv) {
// when length ratio >= 1, set this to true
bool fixLength = false;
// for accumulating delayed updates
ScoreComponentCollection delayedWeightUpdates;
bool stop = false;
// int sumStillViolatedConstraints;
float *sendbuf, *recvbuf;
@ -432,8 +437,10 @@ int main(int argc, char** argv) {
size_t weightEpochDump = 0;
// sum lengths of dev hypothesis/references to calculate translation length ratio for this epoch
size_t dev_hypothesis_length;
size_t dev_reference_length;
size_t dev_hypothesis_length = 0;
size_t dev_reference_length = 0;
delayedWeightUpdates.ZeroAll();
size_t shardPosition = 0;
vector<size_t>::const_iterator sid = shard.begin();
@ -682,24 +689,28 @@ int main(int argc, char** argv) {
// Run optimiser on batch:
VERBOSE(1, "\nRank " << rank << ", epoch " << epoch << ", run optimiser:" << endl);
size_t update_status;
ScoreComponentCollection weightUpdate;
if (perceptron_update) {
vector<vector<float> > dummy1;
update_status = optimiser->updateWeightsHopeFear(mosesWeights,
update_status = optimiser->updateWeightsHopeFear(mosesWeights, weightUpdate,
featureValuesHope, featureValuesFear, dummy1, dummy1, learning_rate, rank, epoch);
}
else if (hope_fear) {
update_status = optimiser->updateWeightsHopeFear(mosesWeights,
update_status = optimiser->updateWeightsHopeFear(mosesWeights, weightUpdate,
featureValuesHope, featureValuesFear, bleuScoresHope, bleuScoresFear, learning_rate, rank, epoch);
}
else {
// model_hope_fear
update_status = ((MiraOptimiser*) optimiser)->updateWeights(mosesWeights,
update_status = ((MiraOptimiser*) optimiser)->updateWeights(mosesWeights, weightUpdate,
featureValues, losses, bleuScores, oracleFeatureValues, oracleBleuScores, learning_rate, rank, epoch);
}
// sumStillViolatedConstraints += update_status;
if (update_status == 0) { // if weights were updated
// apply weight update
mosesWeights.PlusEquals(weightUpdate);
if (normaliseWeights) {
mosesWeights.L1Normalise();
}
@ -718,8 +729,11 @@ int main(int argc, char** argv) {
mosesWeights = averageWeights;
}
// set new Moses weights
decoder->setWeights(mosesWeights);
if (delayUpdates)
delayedWeightUpdates.PlusEquals(weightUpdate);
else
// set new Moses weights
decoder->setWeights(mosesWeights);
}
// update history (for approximate document Bleu)
@ -830,8 +844,17 @@ int main(int argc, char** argv) {
}
}
}// end dumping
} // end of shard loop, end of this epoch
if (delayUpdates) {
// apply all updates from this epoch to the weight vector
ScoreComponentCollection mosesWeights = decoder->getWeights();
mosesWeights.PlusEquals(delayedWeightUpdates);
decoder->setWeights(mosesWeights);
cerr << "Rank " << rank << ", epoch " << epoch << ", delayed update, new moses weights: " << mosesWeights << endl;
}
if (stabiliseLength && !fixLength) {
float lengthRatio = (float)(dev_hypothesis_length+1) / dev_reference_length;
if (lengthRatio >= 1) {

16
mira/MiraOptimiser.cpp
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@ -7,7 +7,9 @@ using namespace std;
namespace Mira {
size_t MiraOptimiser::updateWeights(ScoreComponentCollection& currWeights,
size_t MiraOptimiser::updateWeights(
ScoreComponentCollection& currWeights,
ScoreComponentCollection& weightUpdate,
const vector<vector<ScoreComponentCollection> >& featureValues,
const vector<vector<float> >& losses,
const vector<vector<float> >& bleuScores,
@ -142,9 +144,7 @@ size_t MiraOptimiser::updateWeights(ScoreComponentCollection& currWeights,
}
cerr << "Rank " << rank << ", epoch " << epoch << ", update: " << summedUpdate << endl;
// apply update to weight vector
currWeights.PlusEquals(summedUpdate);
weightUpdate.PlusEquals(summedUpdate);
// Sanity check: are there still violated constraints after optimisation?
/* int violatedConstraintsAfter = 0;
@ -164,7 +164,9 @@ size_t MiraOptimiser::updateWeights(ScoreComponentCollection& currWeights,
return 0;
}
size_t MiraOptimiser::updateWeightsHopeFear(Moses::ScoreComponentCollection& currWeights,
size_t MiraOptimiser::updateWeightsHopeFear(
Moses::ScoreComponentCollection& currWeights,
Moses::ScoreComponentCollection& weightUpdate,
const std::vector< std::vector<Moses::ScoreComponentCollection> >& featureValuesHope,
const std::vector< std::vector<Moses::ScoreComponentCollection> >& featureValuesFear,
const std::vector<std::vector<float> >& bleuScoresHope,
@ -299,9 +301,7 @@ size_t MiraOptimiser::updateWeightsHopeFear(Moses::ScoreComponentCollection& cur
}
cerr << "Rank " << rank << ", epoch " << epoch << ", update: " << summedUpdate << endl;
// apply update to weight vector
currWeights.PlusEquals(summedUpdate);
weightUpdate.PlusEquals(summedUpdate);
// Sanity check: are there still violated constraints after optimisation?
/* int violatedConstraintsAfter = 0;

10
mira/Optimiser.h
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@ -30,7 +30,9 @@ namespace Mira {
public:
Optimiser() {}
virtual size_t updateWeightsHopeFear(Moses::ScoreComponentCollection& currWeights,
virtual size_t updateWeightsHopeFear(
Moses::ScoreComponentCollection& currWeights,
Moses::ScoreComponentCollection& weightUpdate,
const std::vector<std::vector<Moses::ScoreComponentCollection> >& featureValuesHope,
const std::vector<std::vector<Moses::ScoreComponentCollection> >& featureValuesFear,
const std::vector<std::vector<float> >& bleuScoresHope,
@ -42,7 +44,9 @@ namespace Mira {
class Perceptron : public Optimiser {
public:
virtual size_t updateWeightsHopeFear(Moses::ScoreComponentCollection& currWeights,
virtual size_t updateWeightsHopeFear(
Moses::ScoreComponentCollection& currWeights,
Moses::ScoreComponentCollection& weightUpdate,
const std::vector<std::vector<Moses::ScoreComponentCollection> >& featureValuesHope,
const std::vector<std::vector<Moses::ScoreComponentCollection> >& featureValuesFear,
const std::vector<std::vector<float> >& bleuScoresHope,
@ -66,6 +70,7 @@ namespace Mira {
m_margin_slack(margin_slack) { }
size_t updateWeights(Moses::ScoreComponentCollection& currWeights,
Moses::ScoreComponentCollection& weightUpdate,
const std::vector<std::vector<Moses::ScoreComponentCollection> >& featureValues,
const std::vector<std::vector<float> >& losses,
const std::vector<std::vector<float> >& bleuScores,
@ -75,6 +80,7 @@ namespace Mira {
size_t rank,
size_t epoch);
virtual size_t updateWeightsHopeFear(Moses::ScoreComponentCollection& currWeights,
Moses::ScoreComponentCollection& weightUpdate,
const std::vector<std::vector<Moses::ScoreComponentCollection> >& featureValuesHope,
const std::vector<std::vector<Moses::ScoreComponentCollection> >& featureValuesFear,
const std::vector<std::vector<float> >& bleuScoresHope,

6
mira/Perceptron.cpp
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@ -24,7 +24,9 @@ using namespace std;
namespace Mira {
size_t Perceptron::updateWeightsHopeFear(ScoreComponentCollection& currWeights,
size_t Perceptron::updateWeightsHopeFear(
ScoreComponentCollection& currWeights,
ScoreComponentCollection& weightUpdate,
const vector< vector<ScoreComponentCollection> >& featureValuesHope,
const vector< vector<ScoreComponentCollection> >& featureValuesFear,
const vector< vector<float> >& dummy1,
@ -39,7 +41,7 @@ size_t Perceptron::updateWeightsHopeFear(ScoreComponentCollection& currWeights,
featureValueDiff.MinusEquals(featureValuesFear[0][0]);
cerr << "Rank " << rank << ", epoch " << epoch << ", hope - fear: " << featureValueDiff << endl;
featureValueDiff.MultiplyEquals(perceptron_learning_rate);
currWeights.PlusEquals(featureValueDiff);
weightUpdate.PlusEquals(featureValueDiff);
cerr << "Rank " << rank << ", epoch " << epoch << ", update: " << featureValueDiff << endl;
return 0;
}