add multi level log

modelscope · Dec 27, 2024 · aad5561 · aad5561
1 parent fc5574d
commit aad5561
Showing 1 changed file with 14 additions and 12 deletions.
diff --git a/evalscope/collections/evaluator.py b/evalscope/collections/evaluator.py
@@ -1,7 +1,7 @@
 import json
 import os
 import pandas as pd
-from collections import OrderedDict, defaultdict
+from collections import defaultdict
 from tabulate import tabulate
 from tqdm import tqdm
 
@@ -92,34 +92,36 @@ def get_report(self, reviews):
                     })
 
         df = pd.DataFrame(data)
+        # Explode tags to multiple rows
+        df_exploded = df.explode('tags')
 
         # Helper function for aggregation and sorting
         def aggregate_and_sort(df, group_by_cols):
-            report_df = df.groupby(group_by_cols).agg(
-                average_score=('score', 'mean'), count=('score', 'size')).reset_index()
-            return report_df.sort_values(by='count', ascending=False)
+            report_df = df.groupby(group_by_cols) \
+                .agg(average_score=('score', 'mean'), count=('score', 'size')) \
+                .reset_index() \
+                .sort_values(by='count', ascending=False) \
+                .to_dict(orient='records')
+            return report_df
 
         # Multi-level aggregation
         subset_report_df = aggregate_and_sort(df, ['task_type', 'dataset_name', 'subset_name'])
         dataset_report_df = aggregate_and_sort(df, ['task_type', 'dataset_name'])
         task_report_df = aggregate_and_sort(df, ['task_type'])
-
-        # Explode tags and aggregate
-        df_exploded = df.explode('tags')
         tag_report_df = aggregate_and_sort(df_exploded, ['tags'])
 
         # Convert sorted DataFrames to Dict
         report = {
-            'subset_level': subset_report_df.to_dict(orient='records'),
-            'dataset_level': dataset_report_df.to_dict(orient='records'),
-            'task_level': task_report_df.to_dict(orient='records'),
-            'tag_level': tag_report_df.to_dict(orient='records')
+            'subset_level': subset_report_df,
+            'dataset_level': dataset_report_df,
+            'task_level': task_report_df,
+            'tag_level': tag_report_df
         }
 
         # Log the report
         for level, data in report.items():
             table = tabulate(data, headers='keys', tablefmt='pretty', showindex=False)
-            logger.info(f"{level} Report:\n{table}")
+            logger.info(f'{level} Report:\n{table}')
 
         # Save the report to a JSON file
         report_file_path = os.path.join(self.outputs.reports_dir, 'data_collection.json')