change kernel size to 5x5 in Pruning example (#2639)

Author: ChanBong

intermediate_source/pruning_tutorial.py

@@ -44,9 +44,9 @@
 class LeNet(nn.Module):
     def __init__(self):
         super(LeNet, self).__init__()
-        # 1 input image channel, 6 output channels, 3x3 square conv kernel
-        self.conv1 = nn.Conv2d(1, 6, 3)
-        self.conv2 = nn.Conv2d(6, 16, 3)
+        # 1 input image channel, 6 output channels, 5x5 square conv kernel
+        self.conv1 = nn.Conv2d(1, 6, 5)
+        self.conv2 = nn.Conv2d(6, 16, 5)
         self.fc1 = nn.Linear(16 * 5 * 5, 120)  # 5x5 image dimension
         self.fc2 = nn.Linear(120, 84)
         self.fc3 = nn.Linear(84, 10)