Upload model.py

model.py

@@ -0,0 +1,34 @@
+import torch.nn as nn
+
+class SimpleCNN(nn.Module):
+    def __init__(self):
+        super(SimpleCNN, self).__init__()
+        self.conv1 = nn.Conv2d(3, 16, kernel_size=3, padding=1)
+        self.relu1 = nn.ReLU()
+        self.pool1 = nn.MaxPool2d(2, 2)
+
+        self.conv2 = nn.Conv2d(16, 16, kernel_size=3, padding=1)
+        self.relu2 = nn.ReLU()
+        self.pool2 = nn.MaxPool2d(2, 2)
+
+        self.conv3 = nn.Conv2d(16, 16, kernel_size=3, padding=1)
+        self.relu3 = nn.ReLU()
+        self.pool3 = nn.MaxPool2d(2, 2)
+
+        self.conv4 = nn.Conv2d(16, 32, kernel_size=3, padding=1)
+        self.relu4 = nn.ReLU()
+        self.pool4 = nn.MaxPool2d(2, 2)
+
+        self.fc1 = nn.Linear(32 * 2 * 2, 256)
+        self.fc2 = nn.Linear(256, 10)
+
+    def forward(self, x):
+        x = self.pool1(self.relu1(self.conv1(x)))
+        x = self.pool2(self.relu2(self.conv2(x)))
+        x = self.pool3(self.relu3(self.conv3(x)))
+        x = self.pool4(self.relu4(self.conv4(x)))
+        x = x.view(-1, 32 * 2 * 2)
+        x = self.relu4(self.fc1(x))
+        x = self.fc2(x)
+
+        return x