public static DataFrame TestScikitAPI_EngineSimpleTrainAndPredict(string engine, int th, int N, int ncall, bool cacheScikit)
{
var dico = new Dictionary <Tuple <int, string, int, int>, double>();
var scorer = _TrainSentiment();
var trscorer = _TrainSentiment2();
foreach (var res in _MeasureTime(th, engine, scorer, trscorer, N, ncall, cacheScikit))
{
dico[new Tuple <int, string, int, int>(res.Item1, engine, th, res.Item3)] = res.Item2.TotalSeconds;
}
var df = DataFrameIO.Convert(dico, "N", "engine", "number of threads", "call", "time(s)");
return(df);
}
public void TestScikitAPI_EngineSimpleTrainAndPredict()
{
var dico = new Dictionary <Tuple <int, string, string, int, int>, double>();
var scorer = _TrainSentiment();
var trscorer = _TrainSentiment2Transformer();
foreach (var cache in new[] { false, true })
{
for (int th = 1; th <= 3; ++th)
{
var memo = new Dictionary <string, float[]>();
foreach (var engine in new[] { "mlnet", "scikit" })
{
foreach (var kind in new[] { "array", "stream" })
{
var strat_ = new[] {
cache ? "extcache" : "viewcache",
kind,
};
var strat = string.Join("+", strat_);
foreach (var res in _MeasureTime(th, strat, engine, scorer, trscorer, 2))
{
dico[new Tuple <int, string, string, int, int>(res.Item1, engine, strat, th, res.Item3)] = res.Item2.TotalSeconds;
if (res.Item3 == 1)
{
memo[engine] = res.Item4;
}
}
}
}
var p1 = memo["mlnet"];
var p2 = memo["scikit"];
Assert.AreEqual(p1.Length, p2.Length);
var abs = 0.0;
for (int ii = 0; ii < p1.Length; ++ii)
{
abs += Math.Abs(p1[ii] - p2[ii]);
}
abs /= p1.Length;
// Assert.IsTrue(abs <= 2);
}
}
var df = DataFrameIO.Convert(dico, "N", "engine", "strategy", "number of threads", "call", "time(s)");
var methodName = System.Reflection.MethodBase.GetCurrentMethod().Name;
var filename = FileHelper.GetOutputFile("benchmark_ValueMapperPredictionEngineMultiThread.txt", methodName);
df.ToCsv(filename);
Assert.AreEqual(dico.Count, 48);
}
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);
}
}