Configs: saner num_labels in configs. (#3967)

src/transformers/configuration_utils.py

@@ -86,11 +86,13 @@ class PretrainedConfig(object):
         # Fine-tuning task arguments
         self.architectures = kwargs.pop("architectures", None)
         self.finetuning_task = kwargs.pop("finetuning_task", None)
-        self.num_labels = kwargs.pop("num_labels", 2)
-        self.id2label = kwargs.pop("id2label", {i: f"LABEL_{i}" for i in range(self.num_labels)})
-        self.id2label = dict((int(key), value) for key, value in self.id2label.items())
-        self.label2id = kwargs.pop("label2id", dict(zip(self.id2label.values(), self.id2label.keys())))
-        self.label2id = dict((key, int(value)) for key, value in self.label2id.items())
+        self.id2label = kwargs.pop("id2label", None)
+        self.label2id = kwargs.pop("label2id", None)
+        if self.id2label is not None:
+            self.id2label = dict((int(key), value) for key, value in self.id2label.items())
+            # Keys are always strings in JSON so convert ids to int here.
+        else:
+            self.num_labels = kwargs.pop("num_labels", 2)
 
         # Tokenizer arguments TODO: eventually tokenizer and models should share the same config
         self.prefix = kwargs.pop("prefix", None)
@@ -115,15 +117,12 @@ class PretrainedConfig(object):
 
     @property
     def num_labels(self):
-        return self._num_labels
+        return len(self.id2label)
 
     @num_labels.setter
     def num_labels(self, num_labels):
-        self._num_labels = num_labels
-        self.id2label = {i: "LABEL_{}".format(i) for i in range(self.num_labels)}
-        self.id2label = dict((int(key), value) for key, value in self.id2label.items())
+        self.id2label = {i: "LABEL_{}".format(i) for i in range(num_labels)}
         self.label2id = dict(zip(self.id2label.values(), self.id2label.keys()))
-        self.label2id = dict((key, int(value)) for key, value in self.label2id.items())
 
     def save_pretrained(self, save_directory):
         """