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 = ReLU.ForwardStatic(testInput);
var expected = DenseMatrix.OfArray(new float[, ] {
{ 0, 0, 0.5f, 1f, 100f }
}); // 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(
ReLU.ForwardStatic(testInput),
target
);
loss.Backward();
chainer.Helper.AssertMatrixAlmostEqual(
DenseMatrix.OfArray(new float[, ] {
{ 0.33333334f, 1f, 1.66666675f }
}), // by chainer.py
testInput.Grad
);
}
