public void Init(string modelName)
{
try
{
using (var env = EnvHelper.NewTestEnvironment())
engine = new ValueMapperPredictionEngineFloat(env, modelName, "Probability");
}
catch (Exception e)
{
throw new Exception("erreur", e);
}
}
public void TestValueMapperPredictionEngineMultiThread()
{
var name = FileHelper.GetTestFile("bc-lr.zip");
/*using (*/
var env = EnvHelper.NewTestEnvironment();
using (var engine0 = new ValueMapperPredictionEngineFloat(env, name, conc: 1))
{
var feat = new float[] { 5, 1, 1, 1, 2, 1, 3, 1, 1 };
var exp = new float[100];
for (int i = 0; i < exp.Length; ++i)
{
feat[0] = i;
exp[i] = engine0.Predict(feat);
Assert.IsFalse(float.IsNaN(exp[i]));
Assert.IsFalse(float.IsInfinity(exp[i]));
}
var dico = new Dictionary <Tuple <int, bool, int>, double>();
foreach (var each in new[] { false, true })
{
foreach (int th in new int[] { 2, 0, 1, 3 })
{
var engine = new ValueMapperPredictionEngineFloat(env, name, conc: th);
var sw = new Stopwatch();
sw.Start();
for (int i = 0; i < exp.Length; ++i)
{
feat[0] = i;
var res = engine.Predict(feat);
Assert.AreEqual(exp[i], res);
}
sw.Stop();
dico[new Tuple <int, bool, int>(exp.Length, each, th)] = sw.Elapsed.TotalSeconds;
}
}
Assert.AreEqual(dico.Count, 8);
var df = DataFrameIO.Convert(dico, "N", "number of threads", "time(s)");
var methodName = System.Reflection.MethodBase.GetCurrentMethod().Name;
var filename = FileHelper.GetOutputFile("benchmark_ValueMapperPredictionEngineMultiThread.txt", methodName);
df.ToCsv(filename);
}
}
public void TestValueMapperPredictionEngine()
{
var name = FileHelper.GetTestFile("bc-lr.zip");
/*using (*/
var env = EnvHelper.NewTestEnvironment();
{
using (var engine = new ValueMapperPredictionEngineFloat(env, name))
{
var feat = new float[] { 5, 1, 1, 1, 2, 1, 3, 1, 1 };
for (int i = 0; i < 1000; ++i)
{
feat[0] = i;
var res = engine.Predict(feat);
Assert.IsFalse(float.IsNaN(res));
Assert.IsFalse(float.IsInfinity(res));
}
}
}
}
public void Dispose()
{
engine.Dispose();
engine = null;
}
