public static double Accuracy(FunctionStack functionStack, NdArray x, NdArray y)
{
double matchCount = 0;
NdArray forwardResult = functionStack.Predict(x)[0];
for (int b = 0; b < x.BatchCount; b++)
{
Real maxval = forwardResult.Data[b * forwardResult.Length];
int maxindex = 0;
for (int i = 1; i < forwardResult.Length; i++)
{
if (maxval < forwardResult.Data[b * forwardResult.Length + i])
{
maxval = forwardResult.Data[b * forwardResult.Length + i];
maxindex = i;
}
}
if (maxindex == (int)y.Data[b * y.Length])
{
matchCount++;
}
}
return(matchCount / x.BatchCount);
}
public static T Accuracy <T>(FunctionStack <T> functionStack, NdArray <T> x, NdArray <int> y, LossFunction <T, int> lossFunction, out T loss) where T : unmanaged, IComparable <T>
{
NdArray <T> forwardResult = functionStack.Predict(x)[0];
loss = lossFunction.Evaluate(forwardResult, y);
return(Accuracy(x, y, forwardResult));
}
public static T Accuracy <T>(FunctionStack <T> functionStack, NdArray <T> x, NdArray <int> y, LossFunction <T, int> lossFunction, out T loss) where T : unmanaged, IComparable <T>
{
int matchCount = 0;
NdArray <T> forwardResult = functionStack.Predict(x)[0];
loss = lossFunction.Evaluate(forwardResult, y);
for (int b = 0; b < x.BatchCount; b++)
{
T maxval = forwardResult.Data[b * forwardResult.Length];
int maxindex = 0;
for (int i = 1; i < forwardResult.Length; i++)
{
if (maxval.CompareTo(forwardResult.Data[b * forwardResult.Length + i]) < 0)
{
maxval = forwardResult.Data[b * forwardResult.Length + i];
maxindex = i;
}
}
if (maxindex == y.Data[b * y.Length])
{
matchCount++;
}
}
return((TVal <T>)matchCount / (TVal <T>)x.BatchCount);
}
public static T Accuracy <T>(FunctionStack <T> functionStack, NdArray <T> x, NdArray <int> y) where T : unmanaged, IComparable <T>
{
return(Accuracy(x, y, functionStack.Predict(x)[0]));
}
