Additional fixes for autoquant serialization (#1486)

Summary:
Can't overwrite `.layout` attribute of a Tensor since `tensor.layout` should be `torch.layout`

discovered when loading the autoquantized model https://huggingface.co/jerryzh168/llama3-8b-autoquant

Test Plan:
tested locally with huggingface transformers
Reviewers:

Subscribers:

Tasks:

Tags:

torchao/quantization/autoquant.py

@@ -411,7 +411,7 @@ class AQInt8DynamicallyQuantizedLinearWeight(AQMixin, LinearActivationQuantizedT
     AutoQuantizable version of Int8DynamicallyQuantizedLinearWeight
     """
 
-    layout: Layout = PlainLayout()
+    aq_layout: Layout = PlainLayout()
 
     @classmethod
     def from_float(cls, weight):
@@ -442,7 +442,7 @@ def get_weight_block_size(x):
         target_dtype = torch.int8
         eps = torch.finfo(torch.float32).eps
         zero_point_dtype = torch.int64
-        _layout = cls.layout
+        _layout = cls.aq_layout
         block_size = get_weight_block_size(weight)
 
         weight = to_affine_quantized_intx(
@@ -616,12 +616,13 @@ class AQInt4G32WeightOnlyQuantizedLinearWeight(AffineQuantizedTensor, AQMixin):
     """
 
     group_size: int = 32
-    layout: Layout = TensorCoreTiledLayout(inner_k_tiles=8)
+    # can't override the `layout` attribute
+    aq_layout: Layout = TensorCoreTiledLayout(inner_k_tiles=8)
 
     @classmethod
     def from_float(cls, weight):
         group_size = cls.group_size
-        _layout = cls.layout
+        _layout = cls.aq_layout
 
         if weight.shape[-1] % group_size != 0:
             return weight
@@ -681,7 +682,7 @@ class AQInt4G128WeightOnlyQuantizedMarlinSparseLinearWeight(
     AQInt4G32WeightOnlyQuantizedLinearWeight
 ):
     group_size: int = 128
-    layout: Layout = MarlinSparseLayout()
+    aq_layout: Layout = MarlinSparseLayout()
 
 
 class AQGemliteInt4G32WeightOnlyQuantizedLinearWeight(AffineQuantizedTensor, AQMixin):