chainer_model.py 文件源码

def compute_loss(self, y, t):
        arc_logits, label_logits = y
        true_arcs, true_labels = t.T

        b, l1, l2 = arc_logits.shape
        true_arcs = F.pad_sequence(true_arcs, padding=-1)
        if not self.model._cpu:
            true_arcs.to_gpu()
        arc_loss = F.softmax_cross_entropy(
            F.reshape(arc_logits, (b * l1, l2)),
            F.reshape(true_arcs, (b * l1,)),
            ignore_label=-1)

        b, l1, d = label_logits.shape
        true_labels = F.pad_sequence(true_labels, padding=-1)
        if not self.model._cpu:
            true_labels.to_gpu()
        label_loss = F.softmax_cross_entropy(
            F.reshape(label_logits, (b * l1, d)),
            F.reshape(true_labels, (b * l1,)),
            ignore_label=-1)

        loss = arc_loss + label_loss
        return loss