Expose bias attribute on tuner layers (#1530)

Expose bias attribute on tuner layers

See #1524

This is similar to how we already expose the weight attribute.

src/peft/tuners/tuners_utils.py

@@ -415,6 +415,11 @@ def weight(self) -> torch.Tensor:
             weight = base_layer.weight
         return weight
 
+    @property
+    def bias(self) -> torch.Tensor:
+        base_layer = self.get_base_layer()
+        return base_layer.bias
+
     def merge(self, safe_merge: bool = False, adapter_names: Optional[list[str]] = None) -> None:
         raise NotImplementedError
 

tests/test_custom_models.py

@@ -805,6 +805,13 @@ def test_delete_inactive_adapter(self, test_name, model_id, config_cls, config_k
     def test_adding_multiple_adapters_with_bias_raises(self, test_name, model_id, config_cls, config_kwargs):
         self._test_adding_multiple_adapters_with_bias_raises(model_id, config_cls, config_kwargs)
 
+    def test_weight_bias_attributes(self):
+        model = MLP()
+        config = LoraConfig(target_modules=["lin0"])
+        model = get_peft_model(model, config)
+        assert hasattr(model.base_model.model.lin0, "weight")
+        assert hasattr(model.base_model.model.lin0, "bias")
+
     def test_existing_model_card(self):
         # ensure that if there is already a model card, it is not overwritten
         model = MLP()