Update app.py

app.py

@@ -22,8 +22,8 @@ def print_bn():
             bn_data.extend(m.running_var.data.numpy().tolist())
             bn_data.append(m.momentum)
     print(len(bn_data))
-    bn_data.extend(model.resnet.embedder.embedder.convolution.weight.data.numpy().tolist())
-    print(model.resnet.embedder.embedder.convolution.weight.data.numpy().tolist())
+    # bn_data.extend(model.resnet.embedder.embedder.convolution.weight.data.numpy().tolist())
+    # print(model.resnet.embedder.embedder.convolution.weight.data.numpy().tolist())
     return bn_data
 
 def update_bn(image):
@@ -50,8 +50,8 @@ def greet(image):
         bn_data = print_bn()
         return ','.join([f'{x:.2f}' for x in bn_data])
     else:  
-        conv_layer = model.resnet.embedder.embedder.convolution
-        conv_layer.weight.data = torch.ones_like(conv_layer.weight.data)
+        # conv_layer = model.resnet.embedder.embedder.convolution
+        # conv_layer.weight.data = torch.ones_like(conv_layer.weight.data)
         print(type(image))
         image = torch.tensor(image).float()
         print(image.min(), image.max())