Upload app.py

app.py

@@ -7,18 +7,18 @@ class CNN(nn.Module):
     """
     A custom CNN class.  The network has: (1) a convolution layer with 1 input channel and 16 output channels with ReLU activation and 2x2 max-pooling, (2) a second convolution layer with 16 input channels and 32 output channels with ReLU activation and 2x2 max-pooling, and (3) a linear output layer with 10 outputs.
     """
-	def __init__(self):
-		super(CNN,self).__init__()
-		self.conv1 = nn.Sequential(
-			nn.Conv2d(1,16,5,stride=1,padding=2),
-            	nn.ReLU(),
-           	 	nn.MaxPool2d(kernel_size=2),
-        		)
-        		self.conv2 = nn.Sequential(
-            		nn.Conv2d(16,32,5,1,2),
-            		nn.ReLU(),
-            		nn.MaxPool2d(2),
-        		)
+    def __init__(self):
+        super(CNN,self).__init__()
+        self.conv1 = nn.Sequential(
+            nn.Conv2d(1,16,5,stride=1,padding=2),
+            nn.ReLU(),
+           	nn.MaxPool2d(kernel_size=2),
+        )
+        self.conv2 = nn.Sequential(
+            nn.Conv2d(16,32,5,1,2),
+            nn.ReLU(),
+            nn.MaxPool2d(2),
+        )
         self.out = nn.Linear(32*7*7,10)
         
     # Forward propogation method