Update app.py

app.py

@@ -76,7 +76,7 @@ nn_model = NN(128, 64, 32)
 cnn_model = CNN(1, 32)
 phi_model = PhiModel(128)
 
-dummy_input = torch.rand(1, 128)  # Updated to match GA model's expected input shape
+dummy_input = torch.rand(1, 128)  # This is the input tensor for processing
 
 def iit_consciousness_processing(dummy_input):
     flat_input = dummy_input.view(1, -1)
@@ -85,8 +85,11 @@ def iit_consciousness_processing(dummy_input):
     snn_output = snn_model(flat_input)
     rnn_output = rnn_model(flat_input.unsqueeze(1))  # Reshape to match RNN input
     nn_output = nn_model(flat_input)
-    cnn_input = dummy_input.view(1, 1, 16, 16)  # Match CNN input shape
+    
+    # Update CNN input shape to ensure it's correct
+    cnn_input = dummy_input.view(1, 1, 8, 16)  # Change this to match CNN input size
     cnn_output = cnn_model(cnn_input)
+    
     phi_output = phi_model(flat_input)
 
     consciousness_score = (