diff --git a/src/operators/kernel/arm/lrn_kernel.cpp b/src/operators/kernel/arm/lrn_kernel.cpp
index b7dc0a2646c9594d7ef3e74d2d667f9d616cb332..5ac4c67559ebe1603230e0d50895d0702c38cb77 100644
--- a/src/operators/kernel/arm/lrn_kernel.cpp
+++ b/src/operators/kernel/arm/lrn_kernel.cpp
@@ -23,27 +23,22 @@ namespace operators {
 
 template <>
 void LrnKernel<CPU, float>::Compute(const LrnParam &param) const {
-  const float alpha = param.Alpha();
   const Tensor *input_x = param.InputX();
   auto x_dims = input_x->dims();
   Tensor *out = param.Out();
   out->mutable_data<float>();
-  if (alpha < 0.001) {
-    // coarse precision
-    out->ShareDataWith(*input_x);
-  } else {
-    /// data_format = NCHW
-    const int N = x_dims[0];
-    const int C = x_dims[1];
-    const int H = x_dims[2];
-    const int W = x_dims[3];
-
-    const int n = param.N();
-    const float beta = param.Beta();
-    const float k = param.K();
-    LRNFunctor<float> lrnFunctor;
-    lrnFunctor(*input_x, out, N, C, H, W, n, k, alpha, beta);
-  }
+  /// data_format = NCHW
+  const int N = x_dims[0];
+  const int C = x_dims[1];
+  const int H = x_dims[2];
+  const int W = x_dims[3];
+
+  const int n = param.N();
+  const float alpha = param.Alpha();
+  const float beta = param.Beta();
+  const float k = param.K();
+  LRNFunctor<float> lrnFunctor;
+  lrnFunctor(*input_x, out, N, C, H, W, n, k, alpha, beta);
 }
 
 template class LrnKernel<CPU, float>;