diff --git a/tutorials/02-intermediate/deep_residual_network/main-gpu.py b/tutorials/02-intermediate/deep_residual_network/main-gpu.py
index de1d4ffd..dbca05ce 100644
--- a/tutorials/02-intermediate/deep_residual_network/main-gpu.py
+++ b/tutorials/02-intermediate/deep_residual_network/main-gpu.py
@@ -132,6 +132,7 @@ def forward(self, x):
         optimizer = torch.optim.Adam(resnet.parameters(), lr=lr) 
         
 # Test
+resnet.eval()
 correct = 0
 total = 0
 for images, labels in test_loader:
@@ -144,4 +145,4 @@ def forward(self, x):
 print('Accuracy of the model on the test images: %d %%' % (100 * correct / total))
 
 # Save the Model
-torch.save(resnet.state_dict(), 'resnet.pkl')
\ No newline at end of file
+torch.save(resnet.state_dict(), 'resnet.pkl')
diff --git a/tutorials/02-intermediate/deep_residual_network/main.py b/tutorials/02-intermediate/deep_residual_network/main.py
index cbab3d4c..6bbbe4ff 100644
--- a/tutorials/02-intermediate/deep_residual_network/main.py
+++ b/tutorials/02-intermediate/deep_residual_network/main.py
@@ -132,6 +132,7 @@ def forward(self, x):
         optimizer = torch.optim.Adam(resnet.parameters(), lr=lr) 
 
 # Test
+resnet.eval()
 correct = 0
 total = 0
 for images, labels in test_loader:
@@ -144,4 +145,4 @@ def forward(self, x):
 print('Accuracy of the model on the test images: %d %%' % (100 * correct / total))
 
 # Save the Model
-torch.save(resnet.state_dict(), 'resnet.pkl')
\ No newline at end of file
+torch.save(resnet.state_dict(), 'resnet.pkl')