我正在使用pytorch训练一个字符级的GRU，并将文本分成一定长度的批次。这是训练循环：

for e in range(self.epochs):  self.model.train()  h = self.get_init_state(self.batch_size)    for batch_num in range(self.num_batch_runs):    batch = self.generate_batch(batch_num).to(device)        inp_batch = batch[:-1,:]    tar_batch = batch[1:,:]            self.model.zero_grad()    loss = 0    for i in range(inp_batch.shape[0]):      out, h = self.model(inp_batch[i:i+1,:],h)      loss += loss_fn(out[0],tar_batch[i].view(-1))              loss.backward()    nn.utils.clip_grad_norm_(self.model.parameters(), 5.0)    optimizer.step()        if not (batch_num % 5):      print("epoch: {}, loss: {}".format(e,loss.data.item()/inp_batch.shape[0]))

尽管如此，在第一个批次之后，我仍然遇到了这个错误：

Trying to backward through the graph a second time, but the buffers have already been freed. Specify retain_graph=True when calling backward the first time.

提前感谢..

回答：

我自己找到了答案，GRU的隐藏状态仍然附着在最后一次批次运行上，因此需要使用以下方法断开连接：

h.detach_()