calculating energy star before

app.py

@@ -75,13 +75,13 @@ def get_all_model_names():
         task_df= task_df.rename(columns={"Link": "model"})
         tasks_df = pd.merge(task_df, energy_df, on='model')
         tasks_df= tasks_df[['model', 'parameters', 'total_gpu_energy']]
+        tasks_df['Total GPU Energy (Wh)'] = tasks_df['total_gpu_energy']*1000
+        tasks_df['Total GPU Energy (Wh)'] = tasks_df['Total GPU Energy (Wh)'].round(2)
+        tasks_df['Rating'] = pd.cut(tasks_df['Total GPU Energy (Wh)'], 3, labels=["⭐⭐⭐", "⭐⭐", "⭐"])
         all_df = pd.concat([all_df, tasks_df])
     all_df=all_df.drop_duplicates(subset=['model'])
     all_df['Parameters'] = all_df['parameters'].apply(format_params)
     all_df['Model'] = all_df['model'].apply(make_link)
-    all_df['Total GPU Energy (Wh)'] = all_df['total_gpu_energy']*1000
-    all_df['Total GPU Energy (Wh)'] = all_df['Total GPU Energy (Wh)'].round(2)
-    all_df['Rating'] = pd.cut(all_df['Total GPU Energy (Wh)'], 3, labels=["⭐⭐⭐", "⭐⭐", "⭐"])
     all_df= all_df.sort_values('Total GPU Energy (Wh)')
     model_names = all_df[['Model','Rating','Total GPU Energy (Wh)', 'Parameters']]
     return model_names