s

src/leaderboard/read_evals.py

@@ -108,22 +108,93 @@ class EvalResult:
     def to_dict(self):
         """Converts the Eval Result to a dict compatible with our dataframe display"""
         average = sum([v for v in self.results.values() if v is not None]) / len(Tasks)
-        data_dict = {
-            "eval_name": self.eval_name,  # not a column, just a save name,
-            AutoEvalColumn.precision.name: self.precision.value.name,
-            AutoEvalColumn.model_type.name: self.model_type.value.name,
-            AutoEvalColumn.model_type_symbol.name: self.model_type.value.symbol,
-            AutoEvalColumn.weight_type.name: self.weight_type.value.name,
-            AutoEvalColumn.architecture.name: self.architecture,
-            AutoEvalColumn.model.name: make_clickable_model(self.full_model),
-            AutoEvalColumn.dummy.name: self.full_model,
-            AutoEvalColumn.revision.name: self.revision,
-            AutoEvalColumn.average.name: average,
-            AutoEvalColumn.license.name: self.license,
-            AutoEvalColumn.likes.name: self.likes,
-            AutoEvalColumn.params.name: self.num_params,
-            AutoEvalColumn.still_on_hub.name: self.still_on_hub,
-        }
+        # data_dict = {
+        #     "eval_name": self.eval_name,  # not a column, just a save name,
+        #     AutoEvalColumn.precision.name: self.precision.value.name,
+        #     AutoEvalColumn.model_type.name: self.model_type.value.name,
+        #     AutoEvalColumn.model_type_symbol.name: self.model_type.value.symbol,
+        #     AutoEvalColumn.weight_type.name: self.weight_type.value.name,
+        #     AutoEvalColumn.architecture.name: self.architecture,
+        #     AutoEvalColumn.model.name: make_clickable_model(self.full_model),
+        #     AutoEvalColumn.dummy.name: self.full_model,
+        #     AutoEvalColumn.revision.name: self.revision,
+        #     AutoEvalColumn.average.name: average,
+        #     AutoEvalColumn.license.name: self.license,
+        #     AutoEvalColumn.likes.name: self.likes,
+        #     AutoEvalColumn.params.name: self.num_params,
+        #     AutoEvalColumn.still_on_hub.name: self.still_on_hub,
+        # }
+        try:
+            data_dict["eval_name"] = self.eval_name
+        except KeyError:
+            print(f"Could not find eval name")
+
+        try:
+            data_dict[AutoEvalColumn.precision.name] = self.precision.value.name
+        except KeyError:
+            print(f"Could not find precision")
+
+        try:
+            data_dict[AutoEvalColumn.model_type.name] = self.model_type.value.name
+        except KeyError:
+            print(f"Could not find model type")
+
+        try:
+            data_dict[AutoEvalColumn.model_type_symbol.name] = self.model_type.value.symbol
+        except KeyError:
+            print(f"Could not find model type symbol")
+
+        try:
+            data_dict[AutoEvalColumn.weight_type.name] = self.weight_type.value.name
+        except KeyError:
+            print(f"Could not find weight type")
+
+        try:
+            data_dict[AutoEvalColumn.architecture.name] = self.architecture
+        except KeyError:
+            print(f"Could not find architecture")
+
+        try:
+            data_dict[AutoEvalColumn.model.name] = make_clickable_model(self.full_model)
+        except KeyError:
+            print(f"Could not find model")
+
+        try:
+            data_dict[AutoEvalColumn.dummy.name] = self.full_model
+        except KeyError:
+            print(f"Could not find dummy")
+
+        try:
+            data_dict[AutoEvalColumn.revision.name] = self.revision
+        except KeyError:
+            print(f"Could not find revision")
+
+        try:
+            data_dict[AutoEvalColumn.average.name] = average
+        except KeyError:
+            print(f"Could not find average")
+
+        try:
+            data_dict[AutoEvalColumn.license.name] = self.license
+        except KeyError:
+            print(f"Could not find license")
+
+        try:
+            data_dict[AutoEvalColumn.likes.name] = self.likes
+        except KeyError:
+            print(f"Could not find likes")
+
+        try:
+            data_dict[AutoEvalColumn.params.name] = self.num_params
+        except KeyError:
+            print(f"Could not find params")
+
+        try:
+            data_dict[AutoEvalColumn.still_on_hub.name] = self.still_on_hub
+        except KeyError:
+            print(f"Could not find still on hub")
+
+
 
         for task in Tasks:
             data_dict[task.value.col_name] = self.results[task.value.benchmark]