utils.py 文件源码

def stats(criterion, a, y, mask):
   if mask is not None:
      _, preds = t.max(a.data, 2)
      batch, sLen, c = a.size()
      loss = criterion(a.view(-1, c), y.view(-1))

      m = t.sum(mask)
      mask = _sequence_mask(mask, sLen)
      acc = t.sum(mask.data.float() * (y.data == preds).float()) / float(m.data[0])
      #loss = criterion(a.view(-1, c), y.view(-1))
   else:
      _, preds = t.max(a.data, 1)
      loss = criterion(a, y)
      acc = t.mean((y.data == preds).float())

   return loss, acc