util.py 文件源码

def log_sum_exp(vecs):
    n = len(vecs.size())
    if n == 1:
        vecs = vecs.view(1, -1)
    _, idx = torch.max(vecs, 1)
    max_score = torch.index_select(vecs, 1, idx.view(-1))
    ret = max_score + torch.log(torch.sum(torch.exp(vecs - max_score.expand_as(vecs))))
    if n == 1:
        return ret.view(-1)
    return ret