update scripts

app.py

@@ -142,13 +142,13 @@ def update_table(
     hidden_df: pd.DataFrame,
     columns: list,
     #type_query: list,
-    #precision_query: str,
+    precision_query: str,
     size_query: list,
-    #show_deleted: bool,
+    show_deleted: bool,
     query: str,
 ):
     # filtered_df = filter_models(hidden_df, type_query, size_query, precision_query, show_deleted)
-    filtered_df = filter_models(hidden_df, size_query)
+    filtered_df = filter_models(hidden_df, size_query, precision_query, show_deleted)
     filtered_df = filter_queries(query, filtered_df)
     df = select_columns(filtered_df, columns)
     return df
@@ -191,7 +191,7 @@ def filter_queries(query: str, filtered_df: pd.DataFrame) -> pd.DataFrame:
 
 def filter_models(
     # df: pd.DataFrame, type_query: list, size_query: list, precision_query: list, show_deleted: bool
-    df: pd.DataFrame, size_query: list  # precision_query: list, show_deleted: bool
+    df: pd.DataFrame, size_query: list, precision_query: list, show_deleted: bool
 ) -> pd.DataFrame:
     # Show all models
     # if show_deleted:
@@ -203,12 +203,12 @@ def filter_models(
     
     # type_emoji = [t[0] for t in type_query]
     #filtered_df = filtered_df.loc[df[utils.AutoEvalColumn.model_type_symbol.name].isin(type_emoji)]
-    #filtered_df = filtered_df.loc[df[utils.AutoEvalColumn.precision.name].isin(precision_query + ["None"])]
-
-    numeric_interval = pd.IntervalIndex(sorted([utils.NUMERIC_INTERVALS[s] for s in size_query]))
-    params_column = pd.to_numeric(df[utils.AutoEvalColumn.params.name], errors="coerce")
-    mask = params_column.apply(lambda x: any(numeric_interval.contains(x)))
-    filtered_df = filtered_df.loc[mask]
+    # filtered_df = filtered_df.loc[df[utils.AutoEvalColumn.precision.name].isin(precision_query + ["None"])]
+    #
+    # numeric_interval = pd.IntervalIndex(sorted([utils.NUMERIC_INTERVALS[s] for s in size_query]))
+    # params_column = pd.to_numeric(df[utils.AutoEvalColumn.params.name], errors="coerce")
+    # mask = params_column.apply(lambda x: any(numeric_interval.contains(x)))
+    # filtered_df = filtered_df.loc[mask]
 
     return filtered_df
 
@@ -249,7 +249,7 @@ try:
                         #         value=False, label="Show gated/private/deleted models", interactive=True
                         #     )
                     # with gr.Column(min_width=320):
-                        # with gr.Box(elem_id="box-filter"):
+                        #with gr.Box(elem_id="box-filter"):
                         # filter_columns_type = gr.CheckboxGroup(
                         #     label="Model types",
                         #     choices=[t.to_str() for t in utils.ModelType],
@@ -299,8 +299,8 @@ try:
                         hidden_leaderboard_table_for_search,
                         shown_columns,
                         #filter_columns_type,
-                        # filter_columns_precision,
-                        # filter_columns_size,
+                        #filter_columns_precision,
+                        #filter_columns_size,
                         # deleted_models_visibility,
                         search_bar,
                     ],
@@ -314,9 +314,9 @@ try:
                             hidden_leaderboard_table_for_search,
                             shown_columns,
                             #filter_columns_type,
-                            #filter_columns_precision,
-                            #filter_columns_size,
-                            #deleted_models_visibility,
+                            # filter_columns_precision,
+                            # filter_columns_size,
+                            # deleted_models_visibility,
                             search_bar,
                         ],
                         leaderboard_table,