Update app_utils.py

app_utils.py

@@ -1,5 +1,24 @@
 import streamlit as st
 
+# Setting the states
+def initialize_states():
+    # Streamlit state variables
+    if "model_name" not in st.session_state:
+        st.session_state.model_name = None
+    
+    if "layer_name" not in st.session_state:
+        st.session_state.layer_name = None
+    
+    if "layer_list" not in st.session_state:
+        st.session_state.layer_list = None
+    
+    if "model" not in st.session_state:
+        st.session_state.model = None
+    
+    if "feat_extract" not in st.session_state:
+        st.session_state.feat_extract = None
+
+
 # Strings
 replicate = ":bulb: Choose **ResNet50V2** model and **conv3_block4_out** to get the results as in the example."
 credits = ":memo: [Keras example](https://keras.io/examples/vision/visualizing_what_convnets_learn/) by [@fchollet](https://twitter.com/fchollet)."
@@ -18,21 +37,4 @@ IMG_WIDTH = 180
 IMG_HEIGHT = 180
 VIS_OPTION = {"only the first filter": 0, "the first 64 filters": 64}
 ITERATIONS = 30
-LEARNING_RATE = 10.0
-
-
-# Streamlit state variables
-if "model_name" not in st.session_state:
-    st.session_state.model_name = None
-
-if "layer_name" not in st.session_state:
-    st.session_state.layer_name = None
-
-if "layer_list" not in st.session_state:
-    st.session_state.layer_list = None
-
-if "model" not in st.session_state:
-    st.session_state.model = None
-
-if "feat_extract" not in st.session_state:
-    st.session_state.feat_extract = None
+LEARNING_RATE = 10.0