Update app.py

app.py

@@ -102,8 +102,11 @@ st.sidebar.title("Options")
 # Create a radio button widget for training mode
 training_mode = st.sidebar.radio("Select training mode", ["None", "Dropout", "Batch Normalization"])
 
-# Create a select box widget for user choice
-user_choice = st.sidebar.selectbox("Select what you want to do", ["Predict", "Train"])
+if training_mode == 'None':
+    user_choice == 'Predict'
+elif training_mode == "Dropout" ot "Batch Normalization":
+    user_choice == 'Train'
+
 
 # Display the current training mode and user choice
 st.write(f"Training mode: {training_mode}")
@@ -123,9 +126,9 @@ try:
             # Generate some dummy target data for demonstration
             # You can replace this with your actual target data
             target = np.random.randint(0, 6, size=(1,))
-            # Call the model with the training mode argument
-            # Use a dictionary to map the training mode to the corresponding boolean value
-            loss = model.train_on_batch(image[np.newaxis, ...], target, training={"None": False, "Dropout": True, "Batch Normalization": True}[training_mode])
+            # Call the model without the training argument
+            loss = model.train_on_batch(image[np.newaxis, ...], target)
             st.success(f'Loss: {loss}')
+
 except Exception as e:
     st.error(f"An error occurred: {e}.  Please contact us EcoClim Solutions at EcoClimSolutions.wordpress.com.")