diff --git a/paddle/fluid/operators/sampling_id_op.h b/paddle/fluid/operators/sampling_id_op.h
index 3d724e3ae726fb5b91843d603d434103ae6201d8..7ad25fa13ae8ace963dba5c66a57118e4267737e 100644
--- a/paddle/fluid/operators/sampling_id_op.h
+++ b/paddle/fluid/operators/sampling_id_op.h
@@ -40,7 +40,7 @@ class SamplingIdKernel : public framework::OpKernel<T> {
 
     std::vector<T> ids(batch_size);
     for (size_t i = 0; i < batch_size; ++i) {
-      double r = this->get_rand();
+      double r = this->getRandReal();
       int idx = width - 1;
       for (int j = 0; j < width; ++j) {
         if ((r -= ins_vector[i * width + j]) < 0) {
@@ -60,17 +60,23 @@ class SamplingIdKernel : public framework::OpKernel<T> {
     framework::TensorFromVector(ids, context.device_context(), output);
   }
 
-  double get_rand() const {
+ private:
+  double getRandReal() const {
+    std::call_once(init_flag_, &SamplingIdKernel::getRndInstance);
+    return rnd();
+  }
+
+  static void getRndInstance() {
     // Will be used to obtain a seed for the random number engine
     std::random_device rd;
     // Standard mersenne_twister_engine seeded with rd()
     std::mt19937 gen(rd());
     std::uniform_real_distribution<> dis(0, 1);
-    return dis(gen);
+    rnd = std::bind(dis, gen);
   }
 
- private:
-  unsigned int defaultSeed = 0;
+  static std::once_flag init_flag_;
+  static std::function<> rnd;
 };
 }  // namespace operators
 }  // namespace paddle