055c61d73514d471158ee36b83762802c8d4e3d4,lib/loss/clipped_weighted_huber_loss.py,ClippedWeightedHuberLoss,forward,#ClippedWeightedHuberLoss#Any#,22

Before Change

        mask = y > (self.delta ** 2)
        y -= mask * xp.square(abs(self.diff) - self.delta)
        y *= 0.5
        return xp.array(y.sum() / y.dtype.type(y.size), dtype=y.dtype),

    def backward(self, inputs, gy):
        xp = cuda.get_array_module(*inputs)

After Change

        xp.square(diff, out=diff)
        y = (y - diff) * 0.5

        return y.mean(),

    def backward(self, inputs, grad_outputs):
        xp = cuda.get_array_module(*inputs)

Instances