Add check in Graph.eliminate_dead_code

test/dynamo/test_repros.py

@@ -6497,6 +6497,9 @@ def forward(self, s0 : torch.SymInt, s1 : torch.SymInt, L_x_ : torch.Tensor):
         torch.cuda.manual_seed_all(54321)
         expected = f(torch.randn((2, 12, 16, 32, 32))).sum()
 
+        # https://github.com/pytorch/pytorch/issues/147171
+        torch._inductor.config.fallback_random = True
+
         for backend in ["eager", "aot_eager"]:
             torch.manual_seed(54321)
             torch.cuda.manual_seed_all(54321)

torch/fx/graph.py

@@ -1854,10 +1854,14 @@ class Graph:
         # DCE below will not behave as expected.
         self.lint()
 
+        impure_random = True
+        if torch._guards.TracingContext.try_get():
+            impure_random = torch._inductor.config.fallback_random
+
         def has_side_effect(node):
             if is_impure_node is not None:
                 return is_impure_node(node)
-            return node.is_impure()
+            return node.is_impure(impure_random)
 
         # Reverse iterate so that when we remove a node, any nodes used as an
         # input to that node have an updated user count that no longer reflects

torch/fx/node.py

@@ -758,11 +758,14 @@ class Node(_NodeBase):
         return [n for n in to_process if n not in skipped]
 
     @compatibility(is_backward_compatible=False)
-    def is_impure(self) -> bool:
+    def is_impure(self, impure_random: bool = True) -> bool:
         """
         Returns whether this op is impure, i.e. if its op is a placeholder or
         output, or if a call_function or call_module which is impure.
 
+        Args:
+            impure_random (bool): Whether to treat rand op as impure.
+
         Returns:
 
             bool: If the op is impure or not.
@@ -778,7 +781,7 @@ class Node(_NodeBase):
 
             if getattr(self.target, "_nondeterministic_seeded", False):
                 # impure since it mutates RNG state
-                return True
+                return impure_random
 
             return self.target in _side_effectful_functions