fix bugs in generalization error calculation (pytorch#179)

ownway22 · Jul 7, 2017 · 1b26501 · 1b26501
1 parent cab5705
commit 1b26501
Showing 1 changed file with 2 additions and 3 deletions.
diff --git a/mnist_hogwild/train.py b/mnist_hogwild/train.py
@@ -51,12 +51,11 @@ def test_epoch(model, data_loader):
     for data, target in data_loader:
         data, target = Variable(data, volatile=True), Variable(target)
         output = model(data)
-        test_loss += F.nll_loss(output, target).data[0]
+        test_loss += F.nll_loss(output, target, size_average=False).data[0] # sum up batch loss
         pred = output.data.max(1)[1] # get the index of the max log-probability
         correct += pred.eq(target.data).cpu().sum()
 
-    test_loss = test_loss
-    test_loss /= len(data_loader) # loss function already averages over batch size
+    test_loss /= len(test_loader.dataset)
     print('\nTest set: Average loss: {:.4f}, Accuracy: {}/{} ({:.0f}%)\n'.format(
         test_loss, correct, len(data_loader.dataset),
         100. * correct / len(data_loader.dataset)))