Fix VES problems (#34)

- Fix VES problems (263d6c7ee0fee8840c5b3bd9188eb42568b57a8a)


Co-authored-by: Francesco Giannuzzo <[email protected]>

app.py

@@ -734,6 +734,8 @@ with gr.Blocks(theme='shivi/calm_seafoam', css_paths='style.css', js=js_func) as
                 metrics_conc = target_df    
                 if 'valid_efficency_score' not in metrics_conc.columns:
                     metrics_conc['valid_efficency_score'] = metrics_conc['VES']
+                if 'VES' not in metrics_conc.columns:
+                    metrics_conc['VES'] = metrics_conc['valid_efficency_score']
                 eval_text = generate_eval_text("End evaluation")
                 yield gr.Markdown(eval_text, visible=True), gr.Image(), gr.Markdown(), gr.Markdown(), gr.Markdown(), metrics_conc, *[predictions_dict[model][columns_to_visulize] for model in model_list]
             
@@ -872,12 +874,16 @@ with gr.Blocks(theme='shivi/calm_seafoam', css_paths='style.css', js=js_func) as
                     metrics_df_model['model'] = model
                     metrics_conc = pd.concat([metrics_conc, metrics_df_model], ignore_index=True)
 
-                if 'valid_efficency_score' not in metrics_conc.columns and 'VES' in metrics_conc.columns:
+                if 'valid_efficency_score' not in metrics_conc.columns:
                     metrics_conc['valid_efficency_score'] = metrics_conc['VES']
 
-                if 'VES' not in metrics_conc.columns and 'valid_efficency_score' in metrics_conc.columns:
+                if 'VES' not in metrics_conc.columns:
                     metrics_conc['VES'] = metrics_conc['valid_efficency_score']
-                
+
+                if 'VES' not in metrics_conc.columns and 'valid_efficency_score' not in metrics_conc.columns:
+                    metrics_conc['VES'] = 0
+                    metrics_conc['valid_efficency_score'] = 0
+
                 eval_text = generate_eval_text("End evaluation")
                 yield gr.Markdown(eval_text, visible=True), gr.Image(), gr.Markdown(), gr.Markdown(), gr.Markdown(), metrics_conc, *[predictions_dict[model] for model in model_list]