diff --git a/paddle/fluid/operators/bpr_loss_op.h b/paddle/fluid/operators/bpr_loss_op.h
index ea817bb2391ba9b038cfb58de118fc8c32b7c428..ab68165942a25d3d9c2fd7c84f4d43d8b1d722fa 100644
--- a/paddle/fluid/operators/bpr_loss_op.h
+++ b/paddle/fluid/operators/bpr_loss_op.h
@@ -22,7 +22,9 @@ namespace paddle {
 namespace operators {
 
 using Tensor = framework::Tensor;
-
+/*Todo:
+ *Find a way to adapt TolerableValue, using blas or eigen.
+ */
 template <typename T>
 struct TolerableValue {
   HOSTDEVICE T operator()(const T& x) const {
@@ -86,27 +88,27 @@ class BprLossGradientOpKernel : public framework::OpKernel<T> {
     auto* dx = ctx.Output<Tensor>(framework::GradVarName("X"));
 
     const int step_size = x->dims()[0];
-    const int num_classes_ = x->dims()[1];
-    T* dx_ = dx->mutable_data<T>(ctx.GetPlace());
-    const T* dy_ = dy->data<T>();
-    const T* x_ = x->data<T>();
-    const int64_t* label_pos_ = label_pos->data<int64_t>();
+    const int num_classes = x->dims()[1];
+    T* dx_data = dx->mutable_data<T>(ctx.GetPlace());
+    const T* dy_data = dy->data<T>();
+    const T* x_data = x->data<T>();
+    const int64_t* label_pos_data = label_pos->data<int64_t>();
 
     for (size_t sample_id = 0; sample_id < step_size; sample_id++) {
-      for (size_t x_offset = sample_id * num_classes_;
-           x_offset < (sample_id + 1) * num_classes_; x_offset++) {
-        dx_[x_offset] = static_cast<T>(0);
+      for (size_t x_offset = sample_id * num_classes;
+           x_offset < (sample_id + 1) * num_classes; x_offset++) {
+        dx_data[x_offset] = static_cast<T>(0);
       }
-      auto p_index = sample_id * num_classes_ + label_pos_[sample_id];
-      for (size_t ni = 0; ni < num_classes_; ni++) {
-        if (label_pos_[sample_id] == ni) continue;
-        auto n_index = sample_id * num_classes_ + ni;
-        auto grad_ =
-            -dy_[sample_id] /
-            ((num_classes_ - 1) *
-             (1.0f + TolerableValue<T>()(std::exp(x_[p_index] - x_[n_index]))));
-        dx_[p_index] += grad_;
-        dx_[n_index] -= grad_;
+      auto p_index = sample_id * num_classes + label_pos_data[sample_id];
+      for (size_t ni = 0; ni < num_classes; ni++) {
+        if (label_pos_data[sample_id] == ni) continue;
+        auto n_index = sample_id * num_classes + ni;
+        auto grad_ = -dy_data[sample_id] /
+                     ((num_classes - 1) *
+                      (1.0f + TolerableValue<T>()(std::exp(x_data[p_index] -
+                                                           x_data[n_index]))));
+        dx_data[p_index] += grad_;
+        dx_data[n_index] -= grad_;
       }
     }
   }