public static void TestMemoryLeak()
{
string outModelFile = "cb_adf_mem_leak.model";
using (var vw = new VowpalWabbit <DataString, DataStringADF>("--cb_adf --rank_all"))
{
DataString[] sampleData = CreateStringCbAdfData(1000);
foreach (DataString example in sampleData)
{
vw.Learn(example, example.ActionDependentFeatures, example.SelectedActionIndex, example.Label);
}
vw.Native.SaveModel(outModelFile);
}
var vwModel = new VowpalWabbitModel(new VowpalWabbitSettings(string.Format("--quiet -t -i {0}", outModelFile))
{
MaxExampleCacheSize = 1024
});
var pool = new VowpalWabbitThreadedPrediction <DataString, DataStringADF>(vwModel);
while (true)
{
vwModel = new VowpalWabbitModel(new VowpalWabbitSettings(string.Format("--quiet -t -i {0}", outModelFile))
{
MaxExampleCacheSize = 1024
});
pool.UpdateModel(vwModel);
}
}
public void ThreadPoolNull()
{
using (var pool = new VowpalWabbitThreadedPrediction())
{
using (var vw = pool.GetOrCreate())
{
Assert.IsNull(vw.Value);
}
pool.UpdateModel(new VowpalWabbitModel(string.Empty));
using (var vw = pool.GetOrCreate())
{
Assert.IsNotNull(vw.Value);
}
}
}
public static void MultiThreadedPrediction()
{
var example = new MyExample { Income = 40, Age = 25 };
var vwModel = new VowpalWabbitModel("-t -i m1.model");
using (var pool = new VowpalWabbitThreadedPrediction<MyExample>(vwModel))
{
// thread-safe
using (var vw = pool.GetOrCreate())
{
// vw.Value is not thread-safe
vw.Value.Predict(example);
}
// thread-safe
pool.UpdateModel(new VowpalWabbitModel("-t -i m2.model"));
}
}
public void TestSaveLoadSkip()
{
using (var vw = new VowpalWabbit <SimpleData>("--binary -f saveload.model"))
{
for (int i = 0; i < 100; i++)
{
vw.Learn(new SimpleData {
Value = 1
}, new SimpleLabel {
Label = 1
});
vw.Learn(new SimpleData {
Value = -1
}, new SimpleLabel {
Label = -1
});
}
Assert.AreEqual(1, vw.Predict(new SimpleData {
Value = 1
}, VowpalWabbitPredictionType.Scalar));
Assert.AreEqual(-1, vw.Predict(new SimpleData {
Value = -1
}, VowpalWabbitPredictionType.Scalar));
}
using (var model = new VowpalWabbitModel(new VowpalWabbitSettings {
Arguments = "--binary", ModelStream = File.Open("saveload.model", FileMode.Open)
}))
using (var pool = new VowpalWabbitThreadedPrediction <SimpleData>(new VowpalWabbitSettings {
Model = model
}))
{
using (var vw = pool.GetOrCreate())
{
Assert.AreEqual(-1, vw.Value.Predict(new SimpleData {
Value = -1
}, VowpalWabbitPredictionType.Scalar));
}
}
}
public static void MultiThreadedPrediction()
{
var example = new MyExample {
Income = 40, Age = 25
};
var vwModel = new VowpalWabbitModel("-t -i m1.model");
using (var pool = new VowpalWabbitThreadedPrediction <MyExample>(vwModel))
{
// thread-safe
using (var vw = pool.GetOrCreate())
{
// vw.Value is not thread-safe
vw.Value.Predict(example);
}
// thread-safe
pool.UpdateModel(new VowpalWabbitModel("-t -i m2.model"));
}
}
public static void TestMemoryLeak()
{
string outModelFile = "cb_adf_mem_leak.model";
using (var vw = new VowpalWabbit<DataString, DataStringADF>("--cb_adf --rank_all"))
{
DataString[] sampleData = CreateStringCbAdfData(1000);
foreach (DataString example in sampleData)
{
vw.Learn(example, example.ActionDependentFeatures, example.SelectedActionIndex, example.Label);
}
vw.Native.SaveModel(outModelFile);
}
var vwModel = new VowpalWabbitModel(new VowpalWabbitSettings(string.Format("--quiet -t -i {0}", outModelFile), maxExampleCacheSize: 1024));
var pool = new VowpalWabbitThreadedPrediction<DataString, DataStringADF>(vwModel);
while (true)
{
vwModel = new VowpalWabbitModel(new VowpalWabbitSettings(string.Format("--quiet -t -i {0}", outModelFile), maxExampleCacheSize: 1024));
pool.UpdateModel(vwModel);
}
}
public void ThreadPoolNull()
{
using (var pool = new VowpalWabbitThreadedPrediction())
{
using (var vw = pool.GetOrCreate())
{
Assert.IsNull(vw.Value);
}
pool.UpdateModel(new VowpalWabbitModel(string.Empty));
using (var vw = pool.GetOrCreate())
{
Assert.IsNotNull(vw.Value);
}
}
}
public void TestSharedModel()
{
string cbadfModelFile = "models/cb_adf.model";
var sampleData = CreateSampleCbAdfData();
using (var vw = new VowpalWabbit<DataString, DataStringADF>("--cb_adf --rank_all"))
{
foreach (DataString example in sampleData)
{
vw.Learn(example, example.ActionDependentFeatures, example.SelectedActionIndex, example.Label);
}
vw.Native.SaveModel(cbadfModelFile);
}
// Get ground truth predictions
var expectedPredictions = new List<DataStringADF[]>();
using (var vw = new VowpalWabbit<DataString, DataStringADF>(string.Format("-t -i {0}", cbadfModelFile)))
{
foreach (DataString example in sampleData)
{
expectedPredictions.Add(vw.Predict(example, example.ActionDependentFeatures));
}
}
// Test synchronous VW instances using shared model
using (var vwModel = new VowpalWabbitModel(new VowpalWabbitSettings("-t", modelStream: File.OpenRead(cbadfModelFile))))
using (var vwShared1 = new VowpalWabbit<DataString, DataStringADF>(new VowpalWabbitSettings(model: vwModel)))
using (var vwShared2 = new VowpalWabbit<DataString, DataStringADF>(new VowpalWabbitSettings(model: vwModel)))
{
for (int i = 0; i < sampleData.Length; i++)
{
DataStringADF[] actualPrediction = vwShared1.Predict(sampleData[i], sampleData[i].ActionDependentFeatures);
ReferenceEquals(expectedPredictions[i], actualPrediction);
}
}
// Test concurrent VW instances using shared model and model pool
using (var vwModel = new VowpalWabbitModel(new VowpalWabbitSettings("-t", modelStream: File.OpenRead(cbadfModelFile))))
using (var vwPool = new VowpalWabbitThreadedPrediction<DataString, DataStringADF>(vwModel))
{
Parallel.For
(
fromInclusive: 0,
toExclusive: 20,
parallelOptions: new ParallelOptions { MaxDegreeOfParallelism = Environment.ProcessorCount * 2 },
body: i =>
{
using (var vwObject = vwPool.GetOrCreate())
{
var actualPredictions = new List<DataStringADF[]>();
foreach (DataString example in sampleData)
{
actualPredictions.Add(vwObject.Value.Predict(example, example.ActionDependentFeatures));
}
Assert.AreEqual(expectedPredictions.Count, actualPredictions.Count);
for (int j = 0; j < expectedPredictions.Count; j++)
{
ReferenceEquals(expectedPredictions[j], actualPredictions[j]);
}
}
}
);
}
}
public void TestSharedModel()
{
string cbadfModelFile = "models/cb_adf.model";
var sampleData = CreateSampleCbAdfData();
using (var vw = new VowpalWabbit <DataString, DataStringADF>("--cb_adf --rank_all"))
using (var vwSharedValidation = new VowpalWabbitExampleValidator <DataString>("--cb_adf --rank_all"))
using (var vwADFValidation = new VowpalWabbitExampleValidator <DataStringADF>("--cb_adf --rank_all"))
{
foreach (DataString example in sampleData)
{
Validate(vwSharedValidation, vwADFValidation, example);
vw.Learn(example, example.ActionDependentFeatures, example.SelectedActionIndex, example.Label);
}
vw.Native.SaveModel(cbadfModelFile);
}
// Get ground truth predictions
var expectedPredictions = new List <DataStringADF[]>();
using (var vw = new VowpalWabbit <DataString, DataStringADF>(string.Format("-t -i {0}", cbadfModelFile)))
{
foreach (DataString example in sampleData)
{
var pred = vw.Predict(example, example.ActionDependentFeatures);
if (pred == null)
{
expectedPredictions.Add(null);
}
else
{
expectedPredictions.Add(pred.Select(p => p.Feature).ToArray());
}
}
}
// Test synchronous VW instances using shared model
using (var vwModel = new VowpalWabbitModel(new VowpalWabbitSettings("-t")
{
ModelStream = File.OpenRead(cbadfModelFile)
}))
using (var vwShared1 = new VowpalWabbit <DataString, DataStringADF>(new VowpalWabbitSettings {
Model = vwModel
}))
using (var vwShared2 = new VowpalWabbit <DataString, DataStringADF>(new VowpalWabbitSettings {
Model = vwModel
}))
{
for (int i = 0; i < sampleData.Length; i++)
{
var actualPrediction = vwShared1.Predict(sampleData[i], sampleData[i].ActionDependentFeatures);
if (actualPrediction == null)
{
ReferenceEquals(expectedPredictions[i], actualPrediction);
}
else
{
ReferenceEquals(expectedPredictions[i], actualPrediction.Select(p => p.Feature).ToArray());
}
}
}
// Test concurrent VW instances using shared model and model pool
using (var vwModel = new VowpalWabbitModel(new VowpalWabbitSettings("-t")
{
ModelStream = File.OpenRead(cbadfModelFile)
}))
using (var vwPool = new VowpalWabbitThreadedPrediction <DataString, DataStringADF>(vwModel))
{
Parallel.For
(
fromInclusive: 0,
toExclusive: 20,
parallelOptions: new ParallelOptions {
MaxDegreeOfParallelism = Environment.ProcessorCount * 2
},
body: i =>
{
using (var vwObject = vwPool.GetOrCreate())
{
var actualPredictions = new List <DataStringADF[]>();
foreach (DataString example in sampleData)
{
actualPredictions.Add(vwObject.Value.Predict(example, example.ActionDependentFeatures).Select(p => p.Feature).ToArray());
}
Assert.AreEqual(expectedPredictions.Count, actualPredictions.Count);
for (int j = 0; j < expectedPredictions.Count; j++)
{
ReferenceEquals(expectedPredictions[j], actualPredictions[j]);
}
}
}
);
}
}
public void TestSaveLoadSkip()
{
using (var vw = new VowpalWabbit<SimpleData>("--binary -f saveload.model"))
{
for (int i = 0; i < 100; i++)
{
vw.Learn(new SimpleData { Value = 1 }, new SimpleLabel { Label = 1 });
vw.Learn(new SimpleData { Value = -1 }, new SimpleLabel { Label = -1 });
}
Assert.AreEqual(1, vw.Predict(new SimpleData { Value = 1 }, VowpalWabbitPredictionType.Scalar));
Assert.AreEqual(-1, vw.Predict(new SimpleData { Value = -1 }, VowpalWabbitPredictionType.Scalar));
}
using (var model = new VowpalWabbitModel(new VowpalWabbitSettings { Arguments = "--binary", ModelStream = File.Open("saveload.model", FileMode.Open) }))
using (var pool = new VowpalWabbitThreadedPrediction<SimpleData>(new VowpalWabbitSettings { Model = model }))
{
using (var vw = pool.GetOrCreate())
{
Assert.AreEqual(-1, vw.Value.Predict(new SimpleData { Value = -1 }, VowpalWabbitPredictionType.Scalar));
}
}
}
