added some clean error handling prior to model inferencing

tab_manager.py

@@ -84,9 +84,17 @@ def general_bias_eval_setup(tab, modelID, imagesTab):
                 hide_index=True,
                 num_rows="fixed",
             )
-        if st.button('Evaluate!', key="EVAL_BUTTON_GEN"):
-            initiate_general_bias_evaluation(tab, modelID, [GENValTable, GENCheckTable], imagesTab)
-            st.rerun()
+            
+        if not all([GENValTable["GEN Values"][0].isnumeric(), GENValTable["GEN Values"][1].isnumeric(), GENValTable["GEN Values"][2].isnumeric()]):
+            st.error('Looks like you have entered non-numeric values! '
+                     'Please enter numeric values in the table above', icon="🚨")
+        elif not all([check_for_power_of_two(int(GENValTable["GEN Values"][2])), int(GENValTable["GEN Values"][2]) >= 8]):
+            st.error('Please ensure that your image resolution is 1 number that is to the power of 2 (greater than 8) '
+                     'e.g. 8,16,32,64, 128 etc.', icon="🚨")
+        else:
+            if st.button('Evaluate!', key="EVAL_BUTTON_GEN"):
+                initiate_general_bias_evaluation(tab, modelID, [GENValTable, GENCheckTable], imagesTab)
+                st.rerun()
 
         if user_evaluation_variables.RUN_TIME and user_evaluation_variables.CURRENT_EVAL_TYPE == 'general':
             GBM.output_eval_results(user_evaluation_variables.EVAL_METRICS, 21, 'general')
@@ -141,13 +149,19 @@ def task_oriented_bias_eval_setup(tab, modelID, imagesTab):
         target = st.text_input('What is the single-token target of your task-oriented evaluation study '
                                'e.g.: "burger", "coffee", "men",  "women"')
 
-        if st.button('Evaluate!', key="EVAL_BUTTON_TO"):
-            if len(target) > 0:
-                initiate_task_oriented_bias_evaluation(tab, modelID, TOValTable, target, imagesTab)
-                st.rerun()
-            else:
-                st.error('Please input a target for your task-oriented analysis', icon="🚨")
-            # update_images_tab(imagesTab)
+        if not all([TOValTable["TO Values"][0].isnumeric(), TOValTable["TO Values"][1].isnumeric(), TOValTable["TO Values"][2].isnumeric()]):
+            st.error('Looks like you have entered non-numeric values! '
+                     'Please enter numeric values in the table above', icon="🚨")
+        elif not all([check_for_power_of_two(int(TOValTable["TO Values"][2])), int(TOValTable["TO Values"][2]) >= 8]):
+            st.error('Please ensure that your image resolution is 1 number that is to the power of 2 (greater than 8) '
+                     'e.g. 8,16,32,64, 128 etc.', icon="🚨")
+        else:
+            if st.button('Evaluate!', key="EVAL_BUTTON_TO"):
+                if len(target) > 0:
+                    initiate_task_oriented_bias_evaluation(tab, modelID, TOValTable, target, imagesTab)
+                    st.rerun()
+                else:
+                    st.error('Please input a target for your task-oriented analysis', icon="🚨")
         if user_evaluation_variables.RUN_TIME and user_evaluation_variables.CURRENT_EVAL_TYPE == 'task-oriented':
             GBM.output_eval_results(user_evaluation_variables.EVAL_METRICS, 21, 'task-oriented')
             taskCSVData = create_word_distribution_csv(user_evaluation_variables.EVAL_METRICS,