Port metadata from the linear node onto the reference custom op for int4

Summary:
Allow for numerical debugger in ExecuTorch use the from_node info for
correlation

Test Plan:
CI

Reviewers:

Subscribers:

Tasks:

Tags:

ghstack-source-id: 858a6f4
Pull Request resolved: #2860

Author: kimishpatel

torchao/quantization/pt2e/reference_representation_rewrite.py

@@ -15,7 +15,7 @@
 from torch.ao.quantization.fx._decomposed import quantized_decomposed_lib  # noqa: F401
 from torch.fx import GraphModule
 from torch.fx.passes.utils.matcher_with_name_node_map_utils import InternalMatch
-from torch.fx.subgraph_rewriter import replace_pattern_with_filters
+from torch.fx.subgraph_rewriter import ReplacedPatterns, replace_pattern_with_filters
 
 from torchao.quantization.pt2e.export_utils import WrapperModule
 from torchao.quantization.pt2e.utils import (
@@ -455,6 +455,34 @@ def _filter_fn_for_dynamic_quantized_linear_4bit_groupwise(
     return weight_is_int4 and act_quant_is_int8
 
 
+def _port_metadata_for_dynamic_quantized_linear_4bit_groupwise(
+    replacement_pattern: ReplacedPatterns,
+):
+    """
+    Port metadata for dynamically quantized linear 4-bit groupwise operation.
+    It custom_op node's metadata with corresponding linear node's metadata.
+    """
+    from torch.fx.traceback import NodeSource, NodeSourceAction
+
+    linear_node = None
+    int4_custom_op_node = None
+    for _, g_n in replacement_pattern.nodes_map.items():
+        if g_n.target == torch.ops.aten.linear.default:
+            linear_node = g_n
+            break
+    if len(replacement_pattern.replacements) > 0:
+        int4_custom_op_node = replacement_pattern.replacements[-1]
+    if linear_node is not None and int4_custom_op_node is not None:
+        int4_custom_op_node.meta = linear_node.meta.copy()
+        int4_custom_op_node.meta["from_node"] = [
+            NodeSource(
+                linear_node,
+                "ReplaceInt4DynamicQuantWithCustomOp",
+                NodeSourceAction.REPLACE,
+            )
+        ]
+
+
 def _qdq_quantized_conv2d(
     x_i8,
     x_scale,
@@ -883,6 +911,7 @@ class _RewriteInfo:
         list[Callable[["InternalMatch", torch.fx.Graph, torch.fx.Graph], bool]]
     ] = None
     ignore_literals: bool = False
+    port_metadata_fn: Optional[Callable[["ReplacedPatterns"], None]] = None
 
 
 def reference_representation_rewrite(model: GraphModule) -> GraphModule:
@@ -1053,6 +1082,7 @@ def reference_representation_rewrite(model: GraphModule) -> GraphModule:
             ),
             filter_fn=[_filter_fn_for_dynamic_quantized_linear_4bit_groupwise],
             ignore_literals=True,
+            port_metadata_fn=_port_metadata_for_dynamic_quantized_linear_4bit_groupwise,
         ),
         _RewriteInfo(
             _DYNAMIC_QUANTIZED_LINEAR_4BIT_GROUPWISE_EXAMPLE_INPUTS_2,
@@ -1074,6 +1104,7 @@ def reference_representation_rewrite(model: GraphModule) -> GraphModule:
             ),
             filter_fn=[_filter_fn_for_dynamic_quantized_linear_4bit_groupwise],
             ignore_literals=True,
+            port_metadata_fn=_port_metadata_for_dynamic_quantized_linear_4bit_groupwise,
         ),
         _RewriteInfo(
             _QUANTIZED_LINEAR_EXAMPLE_INPUTS,
@@ -1153,12 +1184,15 @@ def reference_representation_rewrite(model: GraphModule) -> GraphModule:
                 replacement = replacement_post_trans(replacement)
             pattern.recompile()  # type: ignore[attr-defined]
             replacement.recompile()  # type: ignore[attr-defined]
-            replace_pattern_with_filters(
+            matches = replace_pattern_with_filters(
                 model,
                 pattern,
                 replacement,
                 match_filters=rewrite_info.filter_fn,
                 ignore_literals=rewrite_info.ignore_literals,
             )  # type: ignore[arg-type]
+            if rewrite_info.port_metadata_fn:
+                for m in matches:
+                    rewrite_info.port_metadata_fn(m)  # type: ignore[arg-type]
 
     return model