diff --git a/paddle/fluid/operators/dequantize_log_op.cc b/paddle/fluid/operators/dequantize_log_op.cc
index bfd26061e329f0bd6bf52d5fec818ec168eaf1df..2ecd54f7edde63ab5f5256694117cfb15be69384 100644
--- a/paddle/fluid/operators/dequantize_log_op.cc
+++ b/paddle/fluid/operators/dequantize_log_op.cc
@@ -31,9 +31,9 @@ struct DequantizeFunctor<platform::CPUDeviceContext, T> {
     int ind = in->numel();
     for (size_t i = 0; i < (unsigned)ind; i++) {
       if (input_data[i] < 0) {
-        output_data[i] = -std::pow(2.0, dict_data[input_data[i] + 128]);
+        output_data[i] = -dict_data[input_data[i] + 128];
       } else {
-        output_data[i] = std::pow(2.0, dict_data[input_data[i]]);
+        output_data[i] = dict_data[input_data[i]];
       }
     }
   }
diff --git a/paddle/fluid/operators/dequantize_log_op.cu b/paddle/fluid/operators/dequantize_log_op.cu
index 57bad318ab6b649b9ad9dd1a316f75ff7e8d86a5..9f63f8ed6f52019a8d15d2a4ecc3ec0ecc85e165 100644
--- a/paddle/fluid/operators/dequantize_log_op.cu
+++ b/paddle/fluid/operators/dequantize_log_op.cu
@@ -26,9 +26,9 @@ __global__ void KeDequantize(const T* in, const float* dict, int num,
   const int idx = threadIdx.x + blockIdx.x * blockDim.x;
   if (idx < num) {
     if (in[idx] < 0) {
-      out[idx] = -std::pow(static_cast<float>(2.0), dict[in[idx] + 128]);
+      out[idx] = -dict[in[idx] + 128];
     } else {
-      out[idx] = std::pow(static_cast<float>(2.0), dict[in[idx]]);
+      out[idx] = dict[in[idx]];
     }
   }
 }
diff --git a/python/paddle/fluid/tests/unittests/test_dequantize_log_op.py b/python/paddle/fluid/tests/unittests/test_dequantize_log_op.py
index 6c6f0811bbb8a1474a6c783feaf565a7877f9200..3ad1f05f92d58c9fa9e82611283a8bf0b7af237e 100644
--- a/python/paddle/fluid/tests/unittests/test_dequantize_log_op.py
+++ b/python/paddle/fluid/tests/unittests/test_dequantize_log_op.py
@@ -26,9 +26,9 @@ def dequantize_log(x, dict_data):
     output_data_f = output_data.flatten()
     for i in range(x_f.size):
         if x_f[i] < 0:
-            output_data_f[i] = -np.power(2, dict_data[x_f[i] + 128])
+            output_data_f[i] = -dict_data[x_f[i] + 128]
         else:
-            output_data_f[i] = np.power(2, dict_data[x_f[i]])
+            output_data_f[i] = dict_data[x_f[i]]
     return output_data_f.reshape(x.shape)