fix bug

ls

code/d2lzh_pytorch/utils.py

@@ -497,7 +497,7 @@ def train_and_predict_rnn_pytorch(model, num_hiddens, vocab_size, device,
     state = None
     for epoch in range(num_epochs):
         l_sum, n, start = 0.0, 0, time.time()
-        data_iter = d2l.data_iter_consecutive(corpus_indices, batch_size, num_steps, device) # 相邻采样
+        data_iter = data_iter_consecutive(corpus_indices, batch_size, num_steps, device) # 相邻采样
         for X, Y in data_iter:
             if state is not None:
                 # 使用detach函数从计算图分离隐藏状态, 这是为了
@@ -517,7 +517,7 @@ def train_and_predict_rnn_pytorch(model, num_hiddens, vocab_size, device,
             optimizer.zero_grad()
             l.backward()
             # 梯度裁剪
-            d2l.grad_clipping(model.parameters(), clipping_theta, device)
+            grad_clipping(model.parameters(), clipping_theta, device)
             optimizer.step()
             l_sum += l.item() * y.shape[0]
             n += y.shape[0]