Fix LoRALinear throwing errors (meta-pytorch#2909)

Signed-off-by: Emmanuel Ferdman <emmanuelferdman@gmail.com>

Author: emmanuel-ferdman

tests/torchtune/modules/peft/test_lora.py

@@ -237,9 +237,16 @@ def test_quantized_state_dict(self, dtype):
         )
 
     def test_qat_lora_forward(self, inputs, lora_linear, out_dim) -> None:
-        lora_linear = lora_linear(use_bias=True, dtype=torch.float32)
+        lora_linear = lora_linear(use_bias=False, dtype=torch.float32)
         qat_lora_linear = QATLoRALinear.from_lora_linear(lora_linear)
         expected = torch.tensor(QAT_EXPECTED_VAL)
         actual = qat_lora_linear(inputs)
         assert actual.shape == (BSZ, SEQ_LEN, out_dim)
         torch.testing.assert_close(actual.mean(), expected, atol=1e-4, rtol=1e-6)
+
+    def test_qat_lora_with_bias_raises_error(self, lora_linear) -> None:
+        lora_linear_with_bias = lora_linear(use_bias=True, dtype=torch.float32)
+        with pytest.raises(
+            ValueError, match="Bias is not supported in QAT \\+ LoRA yet"
+        ):
+            QATLoRALinear.from_lora_linear(lora_linear_with_bias)

torchtune/modules/peft/lora.py

@@ -277,9 +277,9 @@ def from_lora_linear(
         preserving the weights and adapters.
         """
         if lora_linear.bias is not None:
-            ValueError("Bias is not supported in QAT + LoRA yet")
+            raise ValueError("Bias is not supported in QAT + LoRA yet")
         if lora_linear._quantize_base:
-            ValueError("quantize_base is not compatible with QAT + LoRA")
+            raise ValueError("quantize_base is not compatible with QAT + LoRA")
         if isinstance(lora_linear.dropout, nn.Dropout):
             dropout = lora_linear.dropout.p
         else: