diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index a772125df64aaf2eafe6cb9e022f62cc29043eb7..83fe9af768964003130d02b7d913ad1c2102dd1d 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -22,7 +22,7 @@
     -   id: clang-format-with-version-check
         name: clang-format
         description: Format files with ClangFormat.
-        entry: ./.clang_format.hook -i
+        entry: bash ./.clang_format.hook -i
         language: system
         files: \.(c|cc|cxx|cpp|cu|h|hpp|hxx|proto)$
 -   repo: https://github.com/PaddlePaddle/pre-commit-golang
diff --git a/paddle/capi/CMakeLists.txt b/paddle/capi/CMakeLists.txt
index 11022d17541476c97a2b29be8eb8fecce7e39435..dde99ab3400be4e61bfe119fc272270518acf070 100644
--- a/paddle/capi/CMakeLists.txt
+++ b/paddle/capi/CMakeLists.txt
@@ -53,7 +53,10 @@ add_custom_target(paddle_capi_whole ALL
 set_target_properties(paddle_capi_whole
   PROPERTIES IMPORTED_LOCATION ${CMAKE_CURRENT_BINARY_DIR}/${capi_whole_library})
 
+set(LINK_FLAGS " -Wl,--retain-symbols-file ${CMAKE_CURRENT_SOURCE_DIR}/export.sym -Wl,--version-script ${CMAKE_CURRENT_SOURCE_DIR}/export.map")
+# TODO: merge mkl into paddle_capi_shared
 add_library(paddle_capi_shared SHARED ${CAPI_SOURCES})
+set_target_properties(paddle_capi_shared	PROPERTIES LINK_FLAGS "${LINK_FLAGS}")
 target_include_directories(paddle_capi_shared PUBLIC ${CMAKE_CURRENT_BINARY_DIR})
 link_paddle_exe(paddle_capi_shared)
 
diff --git a/paddle/capi/export.map b/paddle/capi/export.map
new file mode 100644
index 0000000000000000000000000000000000000000..8d673f675dd5511f554bff9519a8c078e11868bd
--- /dev/null
+++ b/paddle/capi/export.map
@@ -0,0 +1,6 @@
+{
+	global:
+		paddle_*;
+	local:
+		*;
+};
diff --git a/paddle/capi/export.sym b/paddle/capi/export.sym
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/paddle/gserver/layers/SequenceSliceLayer.cpp b/paddle/gserver/layers/SequenceSliceLayer.cpp
index 6f6577445f56c17d2c43d21a19a086c985714658..d3a83fad276a384ab3fddd5349912c56be6f3cc0 100644
--- a/paddle/gserver/layers/SequenceSliceLayer.cpp
+++ b/paddle/gserver/layers/SequenceSliceLayer.cpp
@@ -130,6 +130,8 @@ void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts,
   CHECK(starts || ends) << "At least one of the start or end indices "
                         << "should be given.";
 
+  bool hasSubseq = getInput(0).hasSubseq();
+
   outSeqStartPos_.resize(1, 0);
   outSubSeqStartPos_.resize(1, 0);
   selectedRows_.clear();
@@ -151,14 +153,13 @@ void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts,
         int seqLen = endPos - begPos + 1;
         CHECK_GT(seqLen, 0U);
         for (int m = begPos; m <= endPos; ++m) selectedRows_.push_back(m);
-        inputSeqInfoVec_.size() > 1
+        hasSubseq
             ? outSubSeqStartPos_.push_back(outSubSeqStartPos_.back() + seqLen)
             : outSeqStartPos_.push_back(outSeqStartPos_.back() + seqLen);
       }
       rowIdx++;
     }
-    if (inputSeqInfoVec_.size() > 1)
-      outSeqStartPos_.push_back(outSubSeqStartPos_.back());
+    if (hasSubseq) outSeqStartPos_.push_back(outSubSeqStartPos_.back());
   }
 
   if (useGpu_) {
@@ -175,7 +176,7 @@ void SequenceSliceLayer::calSelectedRows(const MatrixPtr starts,
   output_.sequenceStartPositions->copyFrom(
       outSeqStartPos_.data(), outSeqStartPos_.size(), false);
 
-  if (inputSeqInfoVec_.size() > 1) {
+  if (hasSubseq) {
     ICpuGpuVector::resizeOrCreate(
         output_.subSequenceStartPositions, outSubSeqStartPos_.size(), false);
     output_.subSequenceStartPositions->copyFrom(
@@ -204,10 +205,11 @@ void SequenceSliceLayer::forward(PassType passType) {
     copySliceIdsToCpu();
   }
 
-  // calculate the selected row indices in a batch,
-  // and build the output sequence information.
-  calSelectedRows(startIdsOnCpu_ ? startIdsOnCpu_ : nullptr,
-                  endIdsOnCpu_ ? endIdsOnCpu_ : nullptr);
+  /*
+   * calculate the selected row indices in a batch, and build the output
+   * sequence information.
+   */
+  calSelectedRows(startIdsOnCpu_, endIdsOnCpu_);
 
   resetOutput(selectedRows_.size(), getSize());
 
diff --git a/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp b/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp
index d560ca650bc5b156de280a2a0d698b67eb032907..e1d4ae16176433b898ba88dd60550e44b4fe37be 100644
--- a/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp
+++ b/paddle/gserver/tests/test_SeqSliceLayerGrad.cpp
@@ -30,6 +30,8 @@ const int MAX_SEQ_NUM = 17;
 const int MAX_SEQ_LEN = 23;
 const int MAX_BEAM_SIZE = 13;
 
+const size_t SEED = (size_t)(time(NULL));
+
 vector<real> randSampling(real range, int n) {
   CHECK_GE(range, n);
   vector<real> num(range);
@@ -46,7 +48,7 @@ void genSeqInfo(vector<int>& seqStartPos, vector<int>& subSeqStartPos) {
   seqStartPos.resize(1, 0);
   subSeqStartPos.resize(1, 0);
 
-  srand((size_t)(time(NULL)));
+  srand(SEED);
   int seqNum = 1 + (rand() % MAX_SEQ_NUM);
   for (int i = 0; i < seqNum; ++i) {
     int subSeqNum = 1 + (rand() % MAX_SEQ_NUM);
diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py
index f323b017c06bb3d0f2c69de0faccb04258ccd2ad..862265f2cdeef1da5623bfe618008030caa98636 100755
--- a/python/paddle/trainer_config_helpers/layers.py
+++ b/python/paddle/trainer_config_helpers/layers.py
@@ -2607,15 +2607,15 @@ def img_pool_layer(input,
         assert input.num_filters is not None
         num_channels = input.num_filters
 
-    assert type(pool_type) in [AvgPooling, MaxPooling, CudnnAvgPooling,
-                               CudnnMaxPooling], \
-        "only (Cudnn)AvgPooling, (Cudnn)MaxPooling are supported"
-
     if pool_type is None:
         pool_type = MaxPooling()
     elif isinstance(pool_type, AvgPooling):
         pool_type.name = 'avg'
 
+    assert type(pool_type) in [AvgPooling, MaxPooling, CudnnAvgPooling,
+                               CudnnMaxPooling], \
+        "only (Cudnn)AvgPooling, (Cudnn)MaxPooling are supported"
+
     type_name = pool_type.name + '-projection' \
         if (
         isinstance(pool_type, AvgPooling) or isinstance(pool_type, MaxPooling)) \