public void Fowardの式が正しい()
{
var testInput = new Variable(DenseMatrix.OfArray(new float[, ] {
{ -100, -1, 0.5f, 1, 100 }
}));
var testOutput = Sigmoid.ForwardStatic(testInput);
var expected = DenseMatrix.OfArray(new float[, ] {
{ 0f, 0.26f, 0.62f, 0.73f, 1f }
}); // by chainer
chainer.Helper.AssertMatrixAlmostEqual(testOutput.Value, expected);
}
public void Backardの式が正しい()
{
var testInput = new Variable(DenseMatrix.OfArray(new float[, ] {
{ 1, 2, 3 }
}));
var target = new Variable(DenseMatrix.OfArray(new float[, ] {
{ 0.5f, 0.5f, 0.5f }
}));
var loss = MeanSquaredError.ForwardStatic(
Sigmoid.ForwardStatic(testInput),
target
);
loss.Backward();
chainer.Helper.AssertMatrixAlmostEqual(
testInput.Grad,
DenseMatrix.OfArray(new float[, ] {
{ 0.03028592f, 0.02665417f, 0.01363052f }
}) // by chainer.py
);
}
