PatternMatcher supports matching list-typed args (#88656)

SherlockNoMad · pytorchmergebot · commit 1d82eba98b22 · 2022-11-08T21:05:18.000Z
Pull Request resolved: #88656 Approved by: https://github.com/jerryzh168
diff --git a/test/fx/test_subgraph_rewriter.py b/test/fx/test_subgraph_rewriter.py
@@ -840,3 +840,24 @@ def num_repalcement_node_found(traced):
             [second_input_is_scalar])
         self.assertEqual(len(matches), 1)
         self.assertEqual(num_repalcement_node_found(traced), 1)
+
+    def test_matching_pattern_with_list_type_arg(self):
+        class M(torch.nn.Module):
+            def forward(self, x):
+                return torch.ops.aten._reshape_alias_copy.default(x, [1, 2], [3, 4])
+
+        def pattern(x, arg0, arg1):
+            return torch.ops.aten._reshape_alias_copy.default(x, arg0, arg1)
+
+        def replacement(x, arg0, arg1):
+            return torch.ops.aten._reshape_alias_copy.default(x, arg1, arg0)
+
+        traced = symbolic_trace(M())
+        matches = subgraph_rewriter.replace_pattern(traced, pattern, replacement)
+
+        self.assertEqual(len(matches), 1)
+
+        self.assertExpectedInline(traced.code.strip(), """\
+def forward(self, x):
+    _reshape_alias_copy_default_1 = torch.ops.aten._reshape_alias_copy.default(x, [3, 4], [1, 2]);  x = None
+    return _reshape_alias_copy_default_1""")  # noqa: B950
diff --git a/torch/fx/passes/utils/matcher_utils.py b/torch/fx/passes/utils/matcher_utils.py
@@ -4,7 +4,6 @@
 from torch.fx.graph import Graph
 from torch.fx.node import Node
 from torch.fx._compatibility import compatibility
-import torch.utils._pytree as pytree
 from typing import Dict, List, Set, Any
 import logging
 import os
@@ -106,12 +105,11 @@ def _nodes_are_equal(self, pn: Node, gn: Node) -> bool:
     def _is_contained(self, nodes_map: Dict[Node, Node]) -> bool:
         # `lookup` represents all the nodes in `original_graph`
         # that are part of `pattern`
-        lookup: Dict[Node, Node] = {gn : pn for pn, gn in nodes_map.items()}
-        for gn, pn in lookup.items():
-            # Placeholders can be used by other nodes in the graphs
-            if pn.op == "placeholder":
-                continue
 
+        # Placeholders can be used by other nodes in the graphs
+        lookup: Dict[Node, Node] = {gn : pn for pn, gn in nodes_map.items() if pn.op != "placeholder"}
+
+        for gn, pn in lookup.items():
             # nodes returned by output are allowed to be used in other areas of the graph
             if pn in self.pattern_returning_nodes:
                 continue
@@ -188,8 +186,20 @@ def _match_nodes(self, pn: Node, gn: Node, match: InternalMatch) -> bool:
         # match for `gn`
         match_found = True
 
-        pn_flatten_args, _ = pytree.tree_flatten(pn.args)
-        gn_flatten_args, _ = pytree.tree_flatten(gn.args)
+        def flatten_args(args) -> List[Any]:
+            # Recursively flatten args
+            result : List[Any] = []
+            for arg in args:
+                # flatten the list, if only it's a list/tuple of nodes
+                if isinstance(arg, (list, tuple)) and len(arg) > 0 and isinstance(arg[0], Node):
+                    result.extend(flatten_args(arg))
+                else:
+                    result.append(arg)
+
+            return result
+
+        pn_flatten_args = flatten_args(pn.args)
+        gn_flatten_args = flatten_args(gn.args)
 
         if pn.kwargs.keys() == gn.kwargs.keys():
             for key in pn.kwargs.keys():
diff --git a/torch/fx/subgraph_rewriter.py b/torch/fx/subgraph_rewriter.py
@@ -257,7 +257,10 @@ def _replace_pattern(
         assert len(match.placeholder_nodes) == len(replacement_placeholders)
         val_map: Dict[Node, Node] = {}
         for rn, gn in zip(replacement_placeholders, match.placeholder_nodes):
-            val_map[rn] = match_changed_node.get(gn, gn)
+            if isinstance(gn, Node):
+                val_map[rn] = match_changed_node.get(gn, gn)
+            else:
+                val_map[rn] = gn
 
         # Copy the replacement graph over
         user_nodes: Set[Node] = set()
