add assertion error about config migration to prototype/autoround

test/prototype/test_autoround.py

@@ -86,7 +86,10 @@ def _check_params_and_buffers_type(module, check_fun):
 
 
 class TestAutoRound(TestCase):
-    @pytest.mark.skip(not TORCH_VERSION_AT_LEAST_2_5, "Requires torch 2.5 or later")
+    @pytest.mark.skip("these tests are broken on main branch")
+    @pytest.mark.skipif(
+        not TORCH_VERSION_AT_LEAST_2_5, reason="Requires torch 2.5 or later"
+    )
     @parametrize("device", _AVAILABLE_DEVICES)
     @torch.no_grad()
     def test_auto_round(self, device: str):
@@ -127,7 +130,10 @@ def test_auto_round(self, device: str):
         after_quant = m(*example_inputs)
         assert after_quant is not None, "Quantized model forward pass failed"
 
-    @pytest.mark.skip(not TORCH_VERSION_AT_LEAST_2_5, "Requires torch 2.5 or later")
+    @pytest.mark.skip("these tests are broken on main branch")
+    @pytest.mark.skipif(
+        not TORCH_VERSION_AT_LEAST_2_5, reason="Requires torch 2.5 or later"
+    )
     @parametrize("device", _AVAILABLE_DEVICES)
     @torch.no_grad()
     def test_wrap_model_with_multi_tensor(self, device: str):

torchao/prototype/autoround/core.py

@@ -165,6 +165,10 @@ def apply_auto_round():
     More details about the auto-round can be found at https://arxiv.org/abs/2309.05516.
     """
 
+    raise AssertionError(
+        "Please migrate this function to direct configuration, see https://github.com/pytorch/ao/issues/1690 for details"
+    )
+
     def _apply_auto_round(optimized_model: torch.nn.Module):
         """
         The `optimized_model` includes `Linear` layers optimized by auto-round, which includes `qdq_weight`, `scale`, `zp`.