step method
Performs a single optimization step using the basic gradient descent rule.
Implementation
@override
void step() {
for (Tensor param in parameters) {
if (param.value is Vector) {
Vector valVec = param.value as Vector;
Vector gradVec = param.grad as Vector;
for (int i = 0; i < valVec.length; i++) {
valVec[i] -= learningRate * gradVec[i];
}
} else if (param.value is Matrix) {
Matrix valMat = param.value as Matrix;
Matrix gradMat = param.grad as Matrix;
for (int r = 0; r < valMat.length; r++) {
for (int c = 0; c < valMat[0].length; c++) {
valMat[r][c] -= learningRate * gradMat[r][c];
}
}
}
}
}