diff --git a/aten/src/ATen/native/layer_norm.cpp b/aten/src/ATen/native/layer_norm.cpp
index 480ea9706e2..ec129a93e0d 100644
--- a/aten/src/ATen/native/layer_norm.cpp
+++ b/aten/src/ATen/native/layer_norm.cpp
@@ -278,27 +278,18 @@ Tensor rms_norm_symint(
         input.scalar_type(),
         "rms_norm",
         [&] {
+    scalar_t eps_val;
+    if (!eps.has_value()) {
+      eps_val = std::numeric_limits<at::scalar_value_type<scalar_t>::type>::epsilon();
+    } else {
+      eps_val = eps.value();
+    }
+
     // upcast is needed for fp16 and bf16
     c10::ScalarType opmath_t = toOpMathType(input.scalar_type());
     Tensor upcasted_input = input.to(opmath_t);
 
-    Tensor rqrst_input;
-
-    // opmath_t would be one of [Double, Float, ComplexFloat, ComplexDouble]
-    if (opmath_t == at::ScalarType::Float || opmath_t == at::ScalarType::ComplexFloat) {
-      float eps_val = std::numeric_limits<float>::epsilon();
-      if (eps.has_value()) {
-        eps_val = eps.value();
-      }
-      rqrst_input = rsqrt(at::pow(upcasted_input, 2).mean(dims_to_reduce_ref, /*keepdim=*/true).add_(eps_val));
-    } else {
-      double eps_val = std::numeric_limits<double>::epsilon();
-      if (eps.has_value()) {
-        eps_val = eps.value();
-      }
-      rqrst_input = rsqrt(at::pow(upcasted_input, 2).mean(dims_to_reduce_ref, /*keepdim=*/true).add_(eps_val));
-    }
-
+    auto rqrst_input = rsqrt(at::pow(upcasted_input, 2).mean(dims_to_reduce_ref, /*keepdim=*/true).add_(eps_val));
     Tensor result = upcasted_input.mul(rqrst_input).type_as(input);
 
     if (weight_opt.has_value()) {