pytorch_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.size()
        true_arcs = _model_var(
            self.model,
            pad_sequence(true_arcs, padding=-1, dtype=np.int64))
        arc_loss = F.cross_entropy(
            arc_logits.view(b * l1, l2), true_arcs.view(b * l1),
            ignore_index=-1)

        b, l1, d = label_logits.size()
        true_labels = _model_var(
            self.model,
            pad_sequence(true_labels, padding=-1, dtype=np.int64))
        label_loss = F.cross_entropy(
            label_logits.view(b * l1, d), true_labels.view(b * l1),
            ignore_index=-1)

        loss = arc_loss + label_loss
        return loss