diff --git a/paddle/operators/prelu_op.h b/paddle/operators/prelu_op.h
index f88ce94dc865f4ca8ddb9e20c22136ee384bdfe2..ece2a836a65e6508580bc32b84f7833388ce55f3 100644
--- a/paddle/operators/prelu_op.h
+++ b/paddle/operators/prelu_op.h
@@ -26,17 +26,17 @@ using platform::Transform;
 template <typename T>
 class PReluFunctor {
  public:
-  explicit PReluFunctor(const T& alpha) : alpha_(alpha) {}
+  explicit PReluFunctor(const T* alpha) : alpha_(alpha) {}
 
   HOSTDEVICE T operator()(const T& x) const {
     if (x > 0)
       return x;
     else
-      return x * alpha_;
+      return x * (*alpha_);
   }
 
  private:
-  T alpha_;
+  const T* alpha_;
 };
 
 template <typename Place, typename T>
@@ -50,30 +50,29 @@ class PReluKernel : public framework::OpKernel {
     const T* x_ptr = x->data<T>();
     T* o_ptr = out->mutable_data<T>(context.GetPlace());
 
-    auto alpha_val = alpha->data<T>()[0];
-    // auto alpha = static_cast<T>(context.Attr<AttrType>("alpha"));
+    auto* alpha_ptr = alpha->data<T>();
 
     int numel = x->numel();
 
     auto place = context.GetPlace();
-    Transform(place, x_ptr, x_ptr + numel, o_ptr, PReluFunctor<T>(alpha_val));
+    Transform(place, x_ptr, x_ptr + numel, o_ptr, PReluFunctor<T>(alpha_ptr));
   }
 };
 
 template <typename T>
 class PReluGradFunctor {
  public:
-  explicit PReluGradFunctor(const T& alpha) : alpha_(alpha) {}
+  explicit PReluGradFunctor(const T* alpha) : alpha_(alpha) {}
 
   HOSTDEVICE T operator()(const T& out, const T& dout) const {
     if (out > 0)
       return dout;
     else
-      return dout * alpha_;
+      return dout * (*alpha_);
   }
 
  private:
-  T alpha_;
+  const T* alpha_;
 };
 
 template <typename Place, typename T>
@@ -85,7 +84,7 @@ class PReluGradKernel : public framework::OpKernel {
 
     auto* out = context.Input<Tensor>("Out");
     auto* alpha = context.Input<Tensor>("Alpha");
-    auto alpha_val = alpha->data<T>()[0];
+    auto* alpha_ptr = alpha->data<T>();
 
     T* dx_ptr = dx->mutable_data<T>(context.GetPlace());
     const T* dout_ptr = dout->data<T>();
@@ -94,7 +93,9 @@ class PReluGradKernel : public framework::OpKernel {
 
     auto place = context.GetPlace();
     Transform(place, out_ptr, out_ptr + numel, dout_ptr, dx_ptr,
-              PReluGradFunctor<T>(alpha_val));
+              PReluGradFunctor<T>(alpha_ptr));
+
+    // TODO (Zhuoyuan): add dalpha upgrade when GPU kernels ready
   }
 };
 
diff --git a/python/paddle/v2/framework/tests/test_prelu_op.py b/python/paddle/v2/framework/tests/test_prelu_op.py
index cbf2e6b2a88ce15ecb513dbf1f7973ce12930235..b74812e96917a28a5aa5d7dd3113e3e958c92cdc 100644
--- a/python/paddle/v2/framework/tests/test_prelu_op.py
+++ b/python/paddle/v2/framework/tests/test_prelu_op.py
@@ -3,13 +3,15 @@ import numpy as np
 from op_test import OpTest
 
 
-class PreluTest(OpTest):
+class PReluTest(OpTest):
     def setUp(self):
         self.op_type = "prelu"
-        self.inputs = {'X': np.random.normal(size=(10, 10)).astype("float32")}
-        self.attrs = {'alpha': 0.1}
+        x_np = np.random.normal(size=(10, 10)).astype("float32")
+        alpha_np = np.array([.1])
+        self.inputs = {'X': x_np, 'Alpha': alpha_np}
         out_np = np.maximum(self.inputs['X'], 0.)
-        out_np = out_np + np.minimum(self.inputs['X'], 0.) * self.attrs['alpha']
+        out_np = out_np + np.minimum(self.inputs['X'],
+                                     0.) * self.inputs['Alpha']
         assert out_np is not self.inputs['X']
         self.outputs = {'Out': out_np}