private void ComputeCrossEntropy(TensorOld y, TensorOld yHat)
{
var forwardoutData = ForwardOutput.GetRawValues();
var backwardoutData = BackwardOutput.GetRawValues();
for (int i = 0; i < sampleNumber; i++)
{
//取出一个样本及其对应的Label
y.GetByDim1(i, yBuff);
yHat.GetByDim1(i, yHatBuff);
//计算交叉熵
forwardoutData[i] = Functions.CrossEntropy(yBuff, yHatBuff);
//计算损失函数关于输入的导数
Derivatives.CrossEntropy(yBuff, yHatBuff, derBuff);
Array.Copy(derBuff, 0, backwardoutData, i * derBuff.Length, derBuff.Length);
}
}
/// <summary>
/// 计算Loss和Loss对yHat的导数（梯度）
/// </summary>
/// <param name="y"></param>
/// <param name="yHat"></param>
public override void Compute(TensorOld y, TensorOld yHat)
{
//只记录了平方误差，使用GetLoss可获取均方误差
Functions.SquareError(y, yHat, ForwardOutput);
Derivatives.MeanSquareError(y, yHat, BackwardOutput);
}
