minor refactoring for batch size in deep residual network

Author: arisliang

tutorials/02-intermediate/deep_residual_network/main.py

@@ -16,6 +16,7 @@
 
 # Hyper-parameters
 num_epochs = 80
+batch_size = 100
 learning_rate = 0.001
 
 # Image preprocessing modules
@@ -37,11 +38,11 @@
 
 # Data loader
 train_loader = torch.utils.data.DataLoader(dataset=train_dataset,
-                                           batch_size=100, 
+                                           batch_size=batch_size,
                                            shuffle=True)
 
 test_loader = torch.utils.data.DataLoader(dataset=test_dataset,
-                                          batch_size=100, 
+                                          batch_size=batch_size,
                                           shuffle=False)
 
 # 3x3 convolution