fixing regressions

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test/integration/test_integration.py

@@ -877,7 +877,8 @@ def _test_lin_weight_subclass_api_impl(
         api(mod)
 
         # test get_plain()
-        mod[0].weight.tensor_impl.get_plain()
+        if hasattr(mod[0].weight, "tensor_impl"):
+            mod[0].weight.tensor_impl.get_plain()
 
         test = mod(x)
         self.assertGreater(

torchao/dtypes/affine_quantized_tensor.py

@@ -235,12 +235,13 @@ def from_hp_to_intx(
                 compute_dtype=compute_dtype,
                 device=device,
                 verbose=False,
-                raw_output=not isinstance(_layout, TensorCoreTiledLayout),
+                raw_output=not isinstance(_layout, (TensorCoreTiledLayout, PlainLayout)),
                 # raw_output=False is basically the 'convert to TensorCoreTiledLayout zero_point version' option (add scale*midpoint)
                 # note in choose_qparams_affine, preserve_zero = False does this same thing while also controlling whether
                 # zero is preserved.
                 # TODO uncouple preserve_zero and conversion of zero_point to TensorCoreTiledLayout version
                 # TODO move the conversion of zero_point out of quant_primitives and into TensorCoreTiledLayout.from_plain
+                # TODO change PlainLayout to use raw_output.
             )
             data = data.to(target_dtype)
         else: