Update app.py

app.py

@@ -25,16 +25,17 @@ DEVICE = torch.device("cpu")
 class PretrainedEfficientNet(nn.Module):
     def __init__(self, num_classes=10):
         super().__init__()
-        self.net = models.efficientnet_b0(weights=None)   
-        old = self.net.features[0][0]
-        self.net.features[0][0] = nn.Conv2d(
+        self.efficientnet = models.efficientnet_b0(weights=None)   
+        old = self.efficientnet.features[0][0]
+        self.efficientnet.features[0][0] = nn.Conv2d(
             1, old.out_channels, kernel_size=old.kernel_size,
             stride=old.stride, padding=old.padding, bias=False)
-        self.net.classifier[1] = nn.Linear(
-            self.net.classifier[1].in_features, num_classes)
+        self.efficientnet.classifier[1] = nn.Linear(
+            self.efficientnet.classifier[1].in_features, num_classes)
 
     def forward(self, x):
-        return self.net(x)
+        return self.efficientnet(x)
+ 
  
 model = PretrainedEfficientNet(num_classes=10)
 weights_path = os.path.join(os.path.dirname(__file__), "best_effnet.pth")