public void AutomatonNormalizationPerformance1()
{
Assert.Timeout(() =>
{
StringAutomaton automaton = StringAutomaton.Zero();
var nextState = automaton.Start.AddTransitionsForSequence("abc");
nextState.AddSelfTransition('d', Weight.FromValue(0.1));
nextState.AddTransitionsForSequence("efg").EndWeight = Weight.One;
nextState.AddTransitionsForSequence("hejfhoenmf").EndWeight = Weight.One;
ProfileAction(() => automaton.GetLogNormalizer(), 100000);
}, 10000);
}
public void RegexpBuildingPerformanceTest3()
{
Assert.Timeout(() =>
{
StringDistribution dist = StringFormatOp_RequireEveryPlaceholder_NoArgumentNames.FormatAverageConditional(
StringDistribution.String("aaaaaaaaaaa"),
new[] { StringDistribution.PointMass("a"), StringDistribution.PointMass("aa") });
Console.WriteLine(dist.ToString());
ProfileAction(() => RegexpTreeBuilder.BuildRegexp(dist.GetWorkspaceOrPoint()), 1000);
}, 20000);
}
public void RegexpBuildingPerformanceTest1()
{
Assert.Timeout(() =>
{
StringDistribution dist =
StringDistribution.OneOf(
StringDistribution.Lower() + StringDistribution.Upper() + StringDistribution.Optional(StringDistribution.Upper(2)),
StringDistribution.Digits(3) + StringDistribution.String("XXX") + StringDistribution.Letters(3, 5));
Console.WriteLine(dist.ToString());
ProfileAction(() => RegexpTreeBuilder.BuildRegexp(dist.GetWorkspaceOrPoint()), 6000);
}, 10000);
}
public void RegexpBuildingPerformanceTest2()
{
Assert.Timeout(() =>
{
StringDistribution dist = StringDistribution.OneOf(StringDistribution.Lower(), StringDistribution.Upper());
for (int i = 0; i < 3; ++i)
{
dist = StringDistribution.OneOf(dist, dist);
}
Console.WriteLine(dist.ToString());
ProfileAction(() => RegexpTreeBuilder.BuildRegexp(dist.GetWorkspaceOrPoint()), 6000);
}, 20000);
}
public void AutomatonNormalizationPerformance1()
{
Assert.Timeout(() =>
{
var builder = new StringAutomaton.Builder();
var nextState = builder.Start.AddTransitionsForSequence("abc");
nextState.AddSelfTransition('d', Weight.FromValue(0.1));
nextState.AddTransitionsForSequence("efg").SetEndWeight(Weight.One);
nextState.AddTransitionsForSequence("hejfhoenmf").SetEndWeight(Weight.One);
var automaton = builder.GetAutomaton();
ProfileAction(() => automaton.GetLogNormalizer(), 100000);
}, 10000);
}
public void AutomatonNormalizationPerformance2()
{
Assert.Timeout(() =>
{
StringAutomaton automaton = StringAutomaton.Zero();
var nextState = automaton.Start.AddTransitionsForSequence("abc");
nextState.SetEndWeight(Weight.One);
nextState.AddSelfTransition('d', Weight.FromValue(0.1));
nextState = nextState.AddTransitionsForSequence("efg");
nextState.SetEndWeight(Weight.One);
nextState.AddSelfTransition('h', Weight.FromValue(0.2));
nextState = nextState.AddTransitionsForSequence("grlkhgn;lk3rng");
nextState.SetEndWeight(Weight.One);
nextState.AddSelfTransition('h', Weight.FromValue(0.3));
ProfileAction(() => automaton.GetLogNormalizer(), 100000);
}, 20000);
}
public void AutomatonNormalizationPerformance3()
{
Assert.Timeout(() =>
{
StringAutomaton automaton = StringAutomaton.Zero();
automaton.Start.AddSelfTransition('a', Weight.FromValue(0.5));
automaton.Start.EndWeight = Weight.One;
var nextState = automaton.Start.AddTransitionsForSequence("aa");
nextState.AddSelfTransition('a', Weight.FromValue(0.5));
nextState.EndWeight = Weight.One;
for (int i = 0; i < 3; ++i)
{
automaton = automaton.Product(automaton);
}
ProfileAction(() => automaton.GetLogNormalizer(), 100);
}, 120000);
}
public void StringFormatPerformanceTest2()
{
Assert.Timeout(() =>
{
Rand.Restart(777);
Variable <string> template = Variable.Constant("{0} {1}").Named("template");
Variable <string> arg1 = Variable.Random(StringDistribution.Any(minLength: 1, maxLength: 15)).Named("arg1");
Variable <string> arg2 = Variable.Random(StringDistribution.Any(minLength: 1)).Named("arg2");
Variable <string> text = Variable.StringFormat(template, arg1, arg2).Named("text");
Variable <string> fullTextFormat = Variable.Random(StringDistribution.Any()).Named("fullTextFormat");
Variable <string> fullText = Variable.StringFormat(fullTextFormat, text).Named("fullText");
var engine = new InferenceEngine();
engine.Compiler.RecommendedQuality = QualityBand.Experimental;
engine.ShowProgress = false;
Action action = () =>
{
// Generate random observed string
string observedPattern = string.Empty;
for (int j = 0; j < 5; ++j)
{
for (int k = 0; k < 5; ++k)
{
observedPattern += (char)Rand.Int('a', 'z' + 1);
}
observedPattern += ' ';
}
// Run inference
fullText.ObservedValue = observedPattern;
engine.Infer <StringDistribution>(arg1);
engine.Infer <StringDistribution>(arg2);
engine.Infer <StringDistribution>(text);
engine.Infer <StringDistribution>(fullTextFormat);
};
action(); // To exclude the compilation time from the profile
ProfileAction(action, 100);
}, 10000);
}
public void AutomatonNormalizationPerformance3()
{
Assert.Timeout(() =>
{
var builder = new StringAutomaton.Builder();
builder.Start.AddSelfTransition('a', Weight.FromValue(0.5));
builder.Start.SetEndWeight(Weight.One);
var nextState = builder.Start.AddTransitionsForSequence("aa");
nextState.AddSelfTransition('a', Weight.FromValue(0.5));
nextState.SetEndWeight(Weight.One);
var automaton = builder.GetAutomaton();
for (int i = 0; i < 3; ++i)
{
automaton = automaton.Product(automaton);
}
ProfileAction(() => automaton.GetLogNormalizer(), 100);
}, 120000);
}
