diff --git a/paddle/gserver/layers/CRFLayer.cpp b/paddle/gserver/layers/CRFLayer.cpp
index 16cc7384884f7f12f5d022afb7bdb6de6c7fc2c9..0b544420097e9150f8489731b6379dea633e992c 100644
--- a/paddle/gserver/layers/CRFLayer.cpp
+++ b/paddle/gserver/layers/CRFLayer.cpp
@@ -42,8 +42,7 @@ bool CRFLayer::init(const LayerMap& layerMap,
   CHECK_EQ(parameters_[0]->getSize(), numClasses_ * (numClasses_ + 2));
 
   parameter_ = parameters_[0];
-  weight_.reset(
-      new Weight(numClasses_ + 2, numClasses_, parameter_));
+  weight_.reset(new Weight(numClasses_ + 2, numClasses_, parameter_));
 
   // We don't need sequenceStartPositions because each sample of output_ is
   // for the cost of one sequence.
@@ -95,16 +94,18 @@ void CRFLayer::backward(const UpdateCallback& callback) {
   for (int i = 0; i < numSequences; ++i) {
     crfs_[i].backward(output.value->getData() + numClasses_ * starts[i],
                       label.ids->getData() + starts[i],
-                      starts[i + 1] - starts[i], needWGrad);
-    real instanceWeight = weightLayer_ ?
-      getInputValue(*weightLayer_)->getElement(i, 0) : real(1.0f);
+                      starts[i + 1] - starts[i],
+                      needWGrad);
+    real instanceWeight = weightLayer_
+                              ? getInputValue(*weightLayer_)->getElement(i, 0)
+                              : real(1.0f);
     instanceWeight *= coeff_;
 
     MatrixPtr grad = output.grad->subRowMatrix(starts[i], starts[i + 1]);
     grad->add(*crfs_[i].getXGrad(), real(1.0f), instanceWeight);
     if (needWGrad) {
-      weight_->getWGrad()->add(*crfs_[i].getWGrad(), real(1.0f),
-          instanceWeight);
+      weight_->getWGrad()->add(
+          *crfs_[i].getWGrad(), real(1.0f), instanceWeight);
     }
   }
 
diff --git a/paddle/gserver/layers/CRFLayer.h b/paddle/gserver/layers/CRFLayer.h
index 000c48e2d55d1352eb38d648b5c55c00fb4c3050..3c7192913fa76d79ee7b194dcd600f06d5e10a74 100644
--- a/paddle/gserver/layers/CRFLayer.h
+++ b/paddle/gserver/layers/CRFLayer.h
@@ -37,9 +37,9 @@ protected:
   size_t numClasses_;
   ParameterPtr parameter_;
   std::vector<LinearChainCRF> crfs_;
-  LayerPtr weightLayer_;  // weight for each sequence
+  LayerPtr weightLayer_;            // weight for each sequence
   std::unique_ptr<Weight> weight_;  // parameters
-  real coeff_;            // weight for the layer
+  real coeff_;                      // weight for the layer
 };
 
 }  // namespace paddle
diff --git a/paddle/gserver/tests/test_CRFLayerGrad.cpp b/paddle/gserver/tests/test_CRFLayerGrad.cpp
index ad5149306caa8cfc7c60f09e20c54a43e52904bc..6985977aed920aaa4b94d4bed2114f54caec5584 100644
--- a/paddle/gserver/tests/test_CRFLayerGrad.cpp
+++ b/paddle/gserver/tests/test_CRFLayerGrad.cpp
@@ -21,13 +21,10 @@ limitations under the License. */
 #include "TestUtil.h"
 #include "LayerGradUtil.h"
 
-using namespace paddle; // NOLINT
+using namespace paddle;  // NOLINT
 
-P_DECLARE_bool(use_gpu);
-P_DECLARE_int32(gpu_id);
-P_DECLARE_double(checkgrad_eps);
-P_DECLARE_bool(thread_local_rand_use_global_seed);
-P_DECLARE_bool(prev_batch_state);
+DECLARE_int32(gpu_id);
+DECLARE_bool(thread_local_rand_use_global_seed);
 
 static inline bool getNextSequence(std::vector<int>& seq, int numClasses) {
   for (auto& v : seq) {
@@ -96,8 +93,8 @@ TEST(CRFLayer, cost) {
 
       real diff = fabs(trueCost - cost);
       diff /= fabs(cost) < fabs(trueCost) ? fabs(cost) : fabs(trueCost);
-      VLOG(1) << "cost=" << cost << " trueCost=" << trueCost
-        << " diff=" << diff << std::endl;
+      VLOG(1) << "cost=" << cost << " trueCost=" << trueCost << " diff=" << diff
+              << std::endl;
       if (typeid(real) == typeid(double)) {  // NOLINT
         EXPECT_LE(diff, 1e-10);
       } else {
@@ -107,9 +104,7 @@ TEST(CRFLayer, cost) {
   }
 }
 
-inline real epsilon() {
-  return typeid(real) == typeid(double) ? 1e-10 : 0.06;
-}
+inline real epsilon() { return typeid(real) == typeid(double) ? 1e-10 : 0.06; }
 
 TestConfig initTestConfig(size_t numClasses, bool withWeight) {
   TestConfig config;
@@ -117,16 +112,17 @@ TestConfig initTestConfig(size_t numClasses, bool withWeight) {
   config.layerConfig.set_size(numClasses);
   config.biasSize = 0;
 
-  config.inputDefs.push_back({INPUT_SEQUENCE_DATA, "layer_0",
-      numClasses, numClasses * (numClasses + 2)});
+  config.inputDefs.push_back({INPUT_SEQUENCE_DATA,
+                              "layer_0",
+                              numClasses,
+                              numClasses * (numClasses + 2)});
   config.layerConfig.add_inputs();
-  config.inputDefs.push_back({INPUT_SEQUENCE_LABEL, "layer_label",
-      numClasses, 0});
+  config.inputDefs.push_back(
+      {INPUT_SEQUENCE_LABEL, "layer_label", numClasses, 0});
   config.layerConfig.add_inputs();
 
   if (withWeight) {
-    config.inputDefs.push_back({INPUT_DENSE_DIM_DATA, "layer_weight",
-        1, 0});
+    config.inputDefs.push_back({INPUT_DENSE_DIM_DATA, "layer_weight", 1, 0});
     config.layerConfig.add_inputs();
   }