Delete refactored function, move changes over (#126407)

Oops, in #125610 I moved this function to runtime_wrappers.py, but forgot to delete the old one. #126234 then modified it which would do nothing, so I'm applying the change correctly now and deleting the function as I intended.

Pull Request resolved: #126407
Approved by: https://github.com/eellison

torch/_functorch/_aot_autograd/jit_compile_runtime_wrappers.py

@@ -83,26 +83,6 @@ def _force_contiguous(x):
     return x
 
 
-def _compute_output_meta_with_inductor_strides(fw_module, fwd_output_strides):
-    out = [n.meta["val"] for n in (list(fw_module.graph.nodes)[-1].args[0])]
-    # will only be set for inductor
-    if not fwd_output_strides:
-        return out
-
-    from torch.fx.experimental.symbolic_shapes import statically_known_true
-
-    for i in range(len(out)):
-        if not isinstance(out[i], Tensor):
-            continue
-        if all(
-            statically_known_true(s1 == s2)
-            for s1, s2 in zip(out[i].stride(), fwd_output_strides[i])
-        ):
-            continue
-        out[i] = out[i].as_strided(out[i].shape, fwd_output_strides[i])
-    return out
-
-
 # See Note [Tangents must be contiguous, Part 2]
 def coerce_runtime_tangent(x, metadata_tensor):
     if not isinstance(x, torch.Tensor):

torch/_functorch/_aot_autograd/runtime_wrappers.py

@@ -486,15 +486,18 @@ def _compute_output_meta_with_inductor_strides(self):
         fwd_output_strides = self.fwd_output_strides
         if not fwd_output_strides:
             return out
-        with TracingContext.get().fake_mode.shape_env.suppress_guards():
-            for i in range(len(out)):
-                if not isinstance(out[i], Tensor):
-                    continue
-                if all(
-                    s1 == s2 for s1, s2 in zip(out[i].stride(), fwd_output_strides[i])
-                ):
-                    continue
-                out[i] = out[i].as_strided(out[i].shape, fwd_output_strides[i])
+
+        from torch.fx.experimental.symbolic_shapes import statically_known_true
+
+        for i in range(len(out)):
+            if not isinstance(out[i], Tensor):
+                continue
+            if all(
+                statically_known_true(s1 == s2)
+                for s1, s2 in zip(out[i].stride(), fwd_output_strides[i])
+            ):
+                continue
+            out[i] = out[i].as_strided(out[i].shape, fwd_output_strides[i])
         return out
 
     # To be called post compile