diff --git a/src/mlpack/methods/ann/layer/log_softmax_impl.hpp b/src/mlpack/methods/ann/layer/log_softmax_impl.hpp
index 63f0b59e5f..bf432513de 100644
--- a/src/mlpack/methods/ann/layer/log_softmax_impl.hpp
+++ b/src/mlpack/methods/ann/layer/log_softmax_impl.hpp
@@ -68,32 +68,31 @@ void LogSoftMaxType<MatType>::Forward(const MatType& input, MatType& output)
   MatType maxInput = repmat(max(input), input.n_rows, 1);
   output = (maxInput - input);
 
-  //// Approximation of the base-e exponential function. The acuracy however is
-  //// about 0.00001 lower as using exp. Credits go to Leon Bottou.
-  //output.transform([](double x)
-  //{
-    ////! Fast approximation of exp(-x) for x positive.
-    //static constexpr double A0 = 1.0;
-    //static constexpr double A1 = 0.125;
-    //static constexpr double A2 = 0.0078125;
-    //static constexpr double A3 = 0.00032552083;
-    //static constexpr double A4 = 1.0172526e-5;
+  // Approximation of the base-e exponential function. The acuracy however is
+  // about 0.00001 lower as using exp. Credits go to Leon Bottou.
+  output.transform([](double x)
+  {
+    //! Fast approximation of exp(-x) for x positive.
+    static constexpr double A0 = 1.0;
+    static constexpr double A1 = 0.125;
+    static constexpr double A2 = 0.0078125;
+    static constexpr double A3 = 0.00032552083;
+    static constexpr double A4 = 1.0172526e-5;
 
-    //if (x < 13.0)
-    //{
-      //double y = A0 + x * (A1 + x * (A2 + x * (A3 + x * A4)));
-      //y *= y;
-      //y *= y;
-      //y *= y;
-      //y = 1 / y;
+    if (x < 13.0)
+    {
+      double y = A0 + x * (A1 + x * (A2 + x * (A3 + x * A4)));
+      y *= y;
+      y *= y;
+      y *= y;
+      y = 1 / y;
 
-      //return y;
-    //}
+      return y;
+    }
 
-    //return 0.0;
- // });
- // 
-  output = exp(output * (-1));
+    return 0.0;
+  });
+ 
   maxInput.each_row() += log(sum(output));
   output = input - maxInput;
 }