fix bug about batch_count (#60)

code/d2lzh_pytorch/utils.py

@@ -230,9 +230,8 @@ def train_ch5(net, train_iter, test_iter, batch_size, optimizer, device, num_epo
     net = net.to(device)
     print("training on ", device)
     loss = torch.nn.CrossEntropyLoss()
-    batch_count = 0
     for epoch in range(num_epochs):
-        train_l_sum, train_acc_sum, n, start = 0.0, 0.0, 0, time.time()
+        train_l_sum, train_acc_sum, n, batch_count, start = 0.0, 0.0, 0, 0, time.time()
         for X, y in train_iter:
             X = X.to(device)
             y = y.to(device)

docs/chapter05_CNN/5.5_lenet.md

@@ -131,9 +131,8 @@ def train_ch5(net, train_iter, test_iter, batch_size, optimizer, device, num_epo
     net = net.to(device)
     print("training on ", device)
     loss = torch.nn.CrossEntropyLoss()
-    batch_count = 0
     for epoch in range(num_epochs):
-        train_l_sum, train_acc_sum, n, start = 0.0, 0.0, 0, time.time()
+        train_l_sum, train_acc_sum, n, batch_count, start = 0.0, 0.0, 0, 0, time.time()
         for X, y in train_iter:
             X = X.to(device)
             y = y.to(device)