static void ScoreMelModel(Set sourceFiles, Matrix Model)
{
if (Model == null)
{
Console.WriteLine("Model not loaded.");
return;
}
string[] Shuffle = ((IEnumerable <string>)sourceFiles).ToArray();
foreach (string file in Shuffle)
{
Matrix Data = System.Ai.Model.LoadFromFile(file, SIZE, out string fmt, out CBOW.DIMS);
Debug.Assert(fmt == "MIDI");
var wo = Model["a"];
if (wo == null)
{
continue;
}
foreach (var it in Data)
{
double dot = 0.0,
score;
for (int j = 0; j < it.Axis.Length; j++)
{
dot += it.Axis[j].Re * wo.Axis[j].Im;
}
score = Sigmoid.f(dot);
it.Score.Im = score;
it.Axis = null;
}
SaveMidi(Data.GetBuffer(), fmt, Path.ChangeExtension(file, ".score"));
}
}
public static Word[] Predict(IEnumerable <Word> Model, float[] Re, int max)
{
Word[] best = new Word[max];
foreach (Word c in Model)
{
int b = 0;
for (int j = 0; j < best.Length; j++)
{
if (best[j] == null)
{
b = j;
break;
}
if (best[j].Re < best[b].Re)
{
b = j;
}
}
float dot = 0,
score;
for (int j = 0; j < Re.Length; j++)
{
dot += c.Elements[j].Im * Re[j];
}
score = (float)Sigmoid.f(dot);
if (best[b] == null || best[b].Re < score)
{
best[b] = new Word(c.Id, c.HashCode)
{
Re = score
};
}
}
return(best);
}
public static double binaryLogistic(double[] X, double[] W)
{
Debug.Assert(X.Length == W.Length);
int len = X.Length;
double Dot = 0.0;
for (int j = 0; j < len; j++)
{
Dot += X[j] * W[j];
}
var y = Sigmoid.f(Dot);
return(y);
}
public static double binaryLogistic(double[] wi,
double[] grads, Complex[] wo, double label, double lr)
{
if (wo == null)
{
return(0);
}
Debug.Assert(label >= -1 && label <= 1);
Debug.Assert(lr >= 0 && lr <= 1);
int len = wi.Length;
double dot = 0.0;
for (int j = 0; j < len; j++)
{
dot += wo[j].Im * wi[j];
}
var y = Sigmoid.f(dot);
double diff = lr * (label - y);
if (double.IsNaN(diff) || double.IsInfinity(diff))
{
Console.WriteLine("NaN or Infinity detected...");
return(diff);
}
if (grads != null)
{
Debug.Assert(grads.Length == len);
for (int j = 0; j < len; j++)
{
grads[j] += wo[j].Im * diff;
}
}
for (int j = 0; j < len; j++)
{
wo[j].Im += (float)(wi[j] * diff);
}
return(y);
}