bug fix

src/display/utils.py

@@ -1,4 +1,4 @@
-from dataclasses import dataclass, make_dataclass
+from dataclasses import dataclass, field, make_dataclass
 from enum import Enum
 
 from src.about import Tasks
@@ -21,24 +21,43 @@ class ColumnContent:
 
 ## Leaderboard columns
 auto_eval_column_dict = []
+
+
+def column_field(name: str, type: str, displayed_by_default: bool, hidden: bool = False, never_hidden: bool = False):
+    return (
+        ColumnContent,
+        field(
+            default_factory=lambda: ColumnContent(
+                name,
+                type,
+                displayed_by_default,
+                hidden,
+                never_hidden,
+            )
+        ),
+    )
+
+
 # Init
-auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
-auto_eval_column_dict.append(["model", ColumnContent, ColumnContent("Model", "markdown", True, never_hidden=True)])
-auto_eval_column_dict.append(["average", ColumnContent, ColumnContent("Average ⬆️", "number", True)])
+auto_eval_column_dict.append(["model_type_symbol", *column_field("T", "str", True, never_hidden=True)])
+auto_eval_column_dict.append(["model", *column_field("Model", "markdown", True, never_hidden=True)])
+auto_eval_column_dict.append(["average", *column_field("Average ⬆️", "number", True)])
 for task in Tasks:
-    auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "number", True)])
-auto_eval_column_dict.append(["model_type", ColumnContent, ColumnContent("Type", "str", False)])
-auto_eval_column_dict.append(["architecture", ColumnContent, ColumnContent("Architecture", "str", False)])
-auto_eval_column_dict.append(["weight_type", ColumnContent, ColumnContent("Weight type", "str", False, True)])
-auto_eval_column_dict.append(["precision", ColumnContent, ColumnContent("Precision", "str", False)])
-auto_eval_column_dict.append(["license", ColumnContent, ColumnContent("Hub License", "str", False)])
-auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B)", "number", False)])
-auto_eval_column_dict.append(["likes", ColumnContent, ColumnContent("Hub ❤️", "number", False)])
-auto_eval_column_dict.append(["still_on_hub", ColumnContent, ColumnContent("Available on the hub", "bool", False)])
-auto_eval_column_dict.append(["revision", ColumnContent, ColumnContent("Model sha", "str", False, False)])
+    auto_eval_column_dict.append([task.name, *column_field(task.value.col_name, "number", True)])
+auto_eval_column_dict.append(["model_type", *column_field("Type", "str", False)])
+auto_eval_column_dict.append(["architecture", *column_field("Architecture", "str", False)])
+auto_eval_column_dict.append(["weight_type", *column_field("Weight type", "str", False, True)])
+auto_eval_column_dict.append(["precision", *column_field("Precision", "str", False)])
+auto_eval_column_dict.append(["license", *column_field("Hub License", "str", False)])
+auto_eval_column_dict.append(["params", *column_field("#Params (B)", "number", False)])
+auto_eval_column_dict.append(["likes", *column_field("Hub ❤️", "number", False)])
+auto_eval_column_dict.append(["still_on_hub", *column_field("Available on the hub", "bool", False)])
+auto_eval_column_dict.append(["revision", *column_field("Model sha", "str", False, False)])
 
 # We use make dataclass to dynamically fill the scores from Tasks
 AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)
+for field_name, _, field_def in auto_eval_column_dict:
+    setattr(AutoEvalColumn, field_name, field_def.default_factory())
 
 ## For the queue columns in the submission tab
 @dataclass(frozen=True)