chore: revert layer_norm test

Author: peri044

tests/py/dynamo/conversion/test_layer_norm_aten.py

@@ -24,6 +24,31 @@ def forward(self, x):
             inputs,
         )
 
+    def test_layernorm_with_dynamic_shape(self):
+        class LayerNorm(torch.nn.Module):
+            def forward(self, x):
+                return torch.ops.aten.layer_norm.default(
+                    x,
+                    torch.tensor([3, 224, 224]),
+                    torch.ones((3, 224, 224)),
+                    torch.zeros((3, 224, 224)),
+                    1e-05,
+                    True,
+                )
+
+        input_specs = [
+            Input(
+                shape=(-1, 3, 224, 224),
+                dtype=torch.float32,
+                shape_ranges=[((1, 3, 224, 224), (1, 3, 224, 224), (2, 3, 224, 224))],
+            ),
+        ]
+
+        self.run_test_with_dynamic_shape(
+            LayerNorm(),
+            input_specs,
+        )
+
 
 class TestNativeLayerNormConverter(DispatchTestCase):
     def test_layer_norm(self):
@@ -43,6 +68,30 @@ def forward(self, x):
             inputs,
         )
 
+    def test_layernorm_with_dynamic_shape(self):
+        class LayerNorm(torch.nn.Module):
+            def forward(self, x):
+                return torch.ops.aten.native_layer_norm.default(
+                    x,
+                    torch.tensor([3, 224, 224]),
+                    torch.ones((3, 224, 224)),
+                    torch.zeros((3, 224, 224)),
+                    1e-05,
+                )[0]
+
+        input_specs = [
+            Input(
+                shape=(-1, 3, 224, 224),
+                dtype=torch.float32,
+                shape_ranges=[((1, 3, 224, 224), (1, 3, 224, 224), (2, 3, 224, 224))],
+            ),
+        ]
+
+        self.run_test_with_dynamic_shape(
+            LayerNorm(),
+            input_specs,
+        )
+
 
 if __name__ == "__main__":
     run_tests()