Ensure rms_norm decomp generates add.Scalar for pattern match BC (pytorch#165437)

Summary: Apparently if I just do `tensor + eps` this turns into add.Tensor, which is bad because the constant Tensor ends up getting hoisted into an input, which is a bozo thing to do. Just make sure it's exactly compatible.

Test Plan:
```
buck run 'fbcode//mode/opt' fbcode//bolt/nn/executorch/backends/tests:qnn_test_ar1g1 bolt.nn.executorch.backends.tests.qnn_test_ar1g1.QnnTestAR1G1.test_RMSNorm
```

Reviewed By: tugsbayasgalan

Differential Revision: D84613184

Pull Request resolved: pytorch#165437
Approved by: https://github.com/tugsbayasgalan

Author: ezyang

torch/_decomp/decompositions.py

@@ -1783,7 +1783,10 @@ def _fused_rms_norm(
 
     rqrst_input = torch.rsqrt(
         # NB: don't inplace here, will violate functional IR invariant
-        torch.pow(upcasted_input, 2).mean(dim=dims_to_reduce, keepdim=True).add(eps_val)
+        # NB: carefully use the Scalar overload of add to ensure compatibility with the C++ decomp
+        torch.ops.aten.add.Scalar(
+            torch.pow(upcasted_input, 2).mean(dim=dims_to_reduce, keepdim=True), eps_val
+        )
     )
 
     upcasted_result = upcasted_input.mul(rqrst_input)