debug

Signed-off-by: n1ck-guo <heng.guo@intel.com>

app.py

@@ -386,6 +386,8 @@ def filter_models(
 
     filtered_df = filtered_df.loc[df[AutoEvalColumn.group_size.name].isin(group_dtype)]
 
+    print(filtered_df['model_name_for_query'])
+
     numeric_interval = pd.IntervalIndex(sorted([NUMERIC_INTERVALS[s] for s in size_query]))
     params_column = pd.to_numeric(df[AutoEvalColumn.params.name], errors="coerce")
     mask = params_column.apply(lambda x: any(numeric_interval.contains(x)))

src/populate.py

@@ -15,7 +15,6 @@ def get_leaderboard_df(results_path: str, requests_path: str, dynamic_path: str,
     print(all_data_json)
     all_data_json.append(baseline_row)
     filter_models_flags(all_data_json)
-    print([all_data_json[i]['model_name_for_query'] for i in range(len(all_data_json))])
     print("Keys in the first record of all_data_json:", all_data_json[0].keys())
 
 
@@ -27,7 +26,6 @@ def get_leaderboard_df(results_path: str, requests_path: str, dynamic_path: str,
 
     # filter out if any of the benchmarks have not been produced
     df = df[has_no_nan_values(df, benchmark_cols)]
-    print("get_leaderboard_df:", df)
     return raw_data, df