diff --git a/paddle/parameter/ParameterUpdaterHook.cpp b/paddle/parameter/ParameterUpdaterHook.cpp
index 5e8c77ced03f5547f3d1145b1c7c4900a5223087..a581cc047dfe11105774e4b81d781100606d718f 100644
--- a/paddle/parameter/ParameterUpdaterHook.cpp
+++ b/paddle/parameter/ParameterUpdaterHook.cpp
@@ -20,6 +20,7 @@ limitations under the License. */
 #include <thread>
 #include <unordered_map>
 #include <vector>
+#include <algorithm>
 
 #include "paddle/math/Vector.h"
 #include "paddle/parameter/Parameter.h"
@@ -60,6 +61,7 @@ public:
     maskTemp_ = Vector::create(para->getSize(), false);
     maskTemp_->zeroMem();
     real* dataPtr = maskTemp_->getData();
+    size_t sparsityNum = para->getSize() * (1 - sparsityRatio_);
 
     VectorPtr vecCpu = Vector::create(para->getSize(), false);
     vecCpu->copyFrom(*vec);
@@ -67,10 +69,20 @@ public:
 
     for (size_t i = 0; i < para->getSize(); i++)
       param.push_back(std::make_pair(fabs(vecCpu->getData()[i]), i));
-    std::sort(param.begin(), param.end(), sortPairAscend);
 
-    for (size_t i = 0; i < para->getSize() * sparsityRatio_; i++)
-      dataPtr[param[i].second] = 1.0;
+    std::partial_sort(param.begin(),
+                      param.begin() + sparsityNum,
+                      param.end(),
+                      sortPairAscend);
+    for (size_t i = 0; i < sparsityNum; i++) dataPtr[param[i].second] = 1.0;
+
+    // Currently just use a mask vector for hack.
+    if (para->useGpu()) {
+      maskVec_ = Vector::create(para->getSize(), para->useGpu());
+      maskVec_->copyFrom(*maskTemp_);
+    } else {
+      maskVec_ = maskTemp_;
+    }
   }
 
   void init(Parameter* para) {
@@ -81,15 +93,6 @@ public:
     VLOG(3) << "Initialize Parameter " << para;
     SetDevice device(para->getDeviceId());
 
-    // Currently just use a mask vector for hack.
-    // @TODO(yuyang18): Implemented the mask operation in vector.
-    if (para->useGpu()) {
-      maskVec_ = Vector::create(para->getSize(), para->useGpu());
-      maskVec_->copyFrom(*maskTemp_);
-    } else {
-      maskVec_ = maskTemp_;
-    }
-
     auto& vec = para->getBuf(PARAMETER_VALUE);
     vec->dotMul(*maskVec_);
   }
@@ -136,11 +139,7 @@ static IParameterUpdaterHook* createImpl(
     const ParameterUpdaterHookConfig& config) {
   auto& type = config.type();
   if (type == "pruning") {
-    if (config.has_sparsity_ratio())
-      return new StaticPruningHook(config);
-    else
-      LOG(FATAL) << "There must be sparsity_ratio parameter for " << type
-                 << " Hook";
+    return new StaticPruningHook(config);
   }
 
   LOG(FATAL) << "Unknown Hook type:  " << type;
diff --git a/python/paddle/trainer/config_parser.py b/python/paddle/trainer/config_parser.py
index e0147b1b37c6574c65ce53e58eccaf6cede91a67..3a29c91807f023d9cae509ee729b2eeeb1038805 100644
--- a/python/paddle/trainer/config_parser.py
+++ b/python/paddle/trainer/config_parser.py
@@ -3175,8 +3175,8 @@ def ParameterHook(type, **kwargs):
         hook = ParameterUpdaterHookConfig()
         hook.type = type
         sparsity_ratio = kwargs.get('sparsity_ratio', None)
-        assert sparsity_ratio is not None
-        hook.sparsity_ratio = sparsity_ratio
+        if sparsity_ratio is not None:
+            hook.sparsity_ratio = sparsity_ratio
         return hook
     else:
         return None
diff --git a/python/paddle/trainer_config_helpers/attrs.py b/python/paddle/trainer_config_helpers/attrs.py
index 556701ca7a88c595c4c16fe5b24ccd5b72ae887d..27b54ffdea74e85d803e6cb5d497e5af7ee108a7 100644
--- a/python/paddle/trainer_config_helpers/attrs.py
+++ b/python/paddle/trainer_config_helpers/attrs.py
@@ -73,9 +73,11 @@ class HookAttribute(object):
     def __init__(self, type, sparsity_ratio=None):
         self.type = type
         self.sparsity_ratio = sparsity_ratio
-        assert is_compatible_with(self.sparsity_ratio,
-                                  float), 'sparisity_ratio must be float type'
-        assert self.sparsity_ratio <= 1 and self.sparsity_ratio >= 0, 'sparisity must be a flaot between [0, 1] '
+        if self.sparsity_ratio is not None:
+            assert is_compatible_with(
+                self.sparsity_ratio,
+                float), 'sparisity_ratio must be float type'
+            assert self.sparsity_ratio <= 1 and self.sparsity_ratio >= 0, 'sparisity must be a flaot between [0, 1] '
 
     def __call__(self):
         return ParameterHook(self.type, sparsity_ratio=self.sparsity_ratio)