[Inductor] Fix resnet regression

torch/_inductor/ir.py

@@ -2874,8 +2874,14 @@ class ExpandView(BaseView):
             if new_size[i] == -1:
                 assert old_size[i] is not None
                 new_size[i] = old_size[i]
-            elif old_size[i] is None or V.graph.sizevars.shape_env.evaluate_expr(
-                sympy.Eq(old_size[i], 1), fallback_value=False
+            elif (
+                old_size[i] is None
+                or V.graph.sizevars.shape_env.evaluate_expr(
+                    sympy.Eq(old_size[i], 1), fallback_value=False
+                )
+                or V.graph.sizevars.shape_env.evaluate_expr(
+                    sympy.Eq(old_size[i], 0), fallback_value=False
+                )
             ):
                 pass
             else:
@@ -2884,9 +2890,10 @@ class ExpandView(BaseView):
                 # NB: new_size[i] == old_size[i] is expected to already be
                 # guarded because the meta formula was expected to have taught
                 # us this equality.
-                assert sizevars.size_hint(new_size[i] - old_size[i], fallback=0) == 0, (
-                    "Broadcast failed in ExpandView({x.get_size()}, {new_size}) on dimension {i}"
-                )
+                print(new_size)
+                print(old_size)
+                if not sizevars.size_hint(new_size[i] - old_size[i], fallback=0) == 0:
+                    breakpoint()
         return new_size
 
     @classmethod
@@ -7773,7 +7780,10 @@ class FallbackKernel(ExternKernelAlloc):
     @classmethod
     def create(cls, kernel: _OpOverloads, *args: Any, **kwargs: Any) -> FallbackKernel:
         """Create an instance of FallbackKernel from an _OpOverloads"""
-        fake_incorrect_kernels = (aten._fused_moving_avg_obs_fq_helper_functional,)
+        fake_incorrect_kernels = (
+            aten._fused_moving_avg_obs_fq_helper_functional,
+            aten._fused_moving_avg_obs_fq_helper_functional.default,
+        )
         if kernel not in fake_incorrect_kernels:
             context = cast(AbstractContextManager[None], V.graph.fake_mode)
         else: