private void testZeroTrainingError(
GradientOracle<DynamicFactorGraph, Example<DynamicAssignment, DynamicAssignment>> oracle,
boolean useLbfgs) {
MapReduceConfiguration.setMapReduceExecutor(new LocalMapReduceExecutor(1, 1));
SufficientStatistics parameters = null;
if (useLbfgs) {
RetryingLbfgs trainer = new RetryingLbfgs(50, 10, 0.1, new DefaultLogFunction(1, false));
parameters = trainer.train(oracle, sequenceModel.getNewSufficientStatistics(), trainingData);
} else {
StochasticGradientTrainer trainer =
StochasticGradientTrainer.createWithL2Regularization(
100, 1, 1.0, true, false, 0.1, new DefaultLogFunction());
parameters = trainer.train(oracle, sequenceModel.getNewSufficientStatistics(), trainingData);
}
DynamicFactorGraph trainedModel = sequenceModel.getModelFromParameters(parameters);
// Should be able to get 0 training error.
FactorGraphPredictor predictor =
new FactorGraphPredictor(
trainedModel,
VariableNamePattern.fromTemplateVariables(y, VariableNumMap.EMPTY),
new JunctionTree());
for (Example<DynamicAssignment, DynamicAssignment> trainingDatum : trainingData) {
DynamicAssignment prediction =
predictor.getBestPrediction(trainingDatum.getInput()).getBestPrediction();
assertEquals(trainingDatum.getOutput(), prediction);
}
}
private Example<DynamicAssignment, DynamicAssignment> getListVarAssignment(
List<Assignment> xs, List<Assignment> ys) {
Preconditions.checkArgument(xs.size() == ys.size());
DynamicAssignment input = DynamicAssignment.createPlateAssignment("plateVar", xs);
DynamicAssignment output = DynamicAssignment.createPlateAssignment("plateVar", ys);
return Example.create(input, output);
}