Update my_model/results/demo.py

my_model/results/demo.py

@@ -1,4 +1,5 @@
 import os
+from my_model.utilities.gen_utilities import log_function_call
 import altair as alt
 from my_model.config import evaluation_config as config 
 import streamlit as st
@@ -40,6 +41,7 @@ class ResultDemonstrator:
         """
         st.dataframe(data)
 
+    @log_function_call
     def calculate_and_append_data(self, data_list: list, score_column: str, model_config: str) -> None:
         """
         Calculates mean scores by category and appends them to the data list.
@@ -57,7 +59,8 @@ class ResultDemonstrator:
                     "Configuration": model_config,
                     "Mean Value": round(mean_value * 100, 2)
                 })
-
+                
+    @log_function_call
     def display_ablation_results_per_question_category(self) -> None:
         """Displays ablation results per question category for each model configuration."""
 
@@ -86,7 +89,8 @@ class ResultDemonstrator:
 
             with st.expander(f"{score_type.upper()} Scores per Question Category and Model Configuration"):
                 self.display_table(results_df)
-
+                
+    @log_function_call
     def display_main_results(self) -> None:
         """Displays the main model results from the Scores sheet, these are displayed from the file directly."""
         main_scores = pd.read_excel(config.EVALUATION_DATA_PATH, sheet_name="Scores", index_col=0)
@@ -94,6 +98,7 @@ class ResultDemonstrator:
         main_scores.reset_index()
         self.display_table(main_scores)
 
+    @log_function_call
     def plot_token_count_vs_scores(self, conf: str, model_name: str, score_name: str = 'VQA Score') -> None:
         """
         Plots an interactive scatter plot comparing token count to VQA or EM scores using Altair.
@@ -188,6 +193,8 @@ class ResultDemonstrator:
             return 'color: orange;'
         return 'color: black;'
 
+    
+    @log_function_call
     def show_samples(self, num_samples: int = 3) -> None:
         """
         Displays random sample images and their associated models answers and evaluations.