diff --git a/paddle/function/RowConvOp.cpp b/paddle/function/RowConvOp.cpp
index c3abb64971fd665324409c3adca44a7a5f827fd1..b6501e8f4db7fd33891cd80e07a6f36dd0b34532 100644
--- a/paddle/function/RowConvOp.cpp
+++ b/paddle/function/RowConvOp.cpp
@@ -136,6 +136,7 @@ public:
     // check
     CHECK_EQ(2UL, inputs.size());
     CHECK_EQ(1UL, outputs.size());
+    // TODO(qingqing): support ASSIGN_TO.
     CHECK_EQ(outputs[0].getArgType(), ADD_TO);
     CHECK(inputs[0].isSequenceArg() && outputs[0].isSequenceArg())
         << "SequenceArg required here.";
@@ -144,9 +145,7 @@ public:
     auto w = inputs[1];
     CHECK(in.data() && out.data() && in.getSequenceId().data());
     CHECK_EQ(in.shape().ndims(), 2UL);
-    CHECK_EQ(out.shape().ndims(), 2UL);
-    CHECK_EQ(in.shape()[1], out.shape()[1]);
-    CHECK_EQ(in.shape()[0], out.shape()[0]);
+    CHECK(in.shape() == out.shape());
     CHECK_EQ(w.shape()[1], in.shape()[1]);
 
     auto outMat = out.matrix<Device>();
@@ -176,6 +175,7 @@ public:
 
 template <DeviceType Device>
 class RowConvGradFunc : public FunctionBase {
+  // TODO(qingqing): split into RowConvDataFunc and RowConvWeightFunc
 public:
   void init(const FuncConfig& config) override {}
 
@@ -196,9 +196,8 @@ public:
     auto wGrad = outputs[1];
 
     CHECK_EQ(in.shape().ndims(), 2UL);
-    CHECK_EQ(outGrad.shape().ndims(), 2UL);
-    CHECK_EQ(in.shape()[1], outGrad.shape()[1]);
-    CHECK_EQ(in.shape()[0], outGrad.shape()[0]);
+    CHECK(in.shape() == inGrad.shape());
+    CHECK(in.shape() == outGrad.shape());
     CHECK_EQ(wGrad.shape()[1], in.shape()[1]);
 
     const auto outGMat = outGrad.matrix<Device>();
diff --git a/paddle/gserver/layers/RowConvLayer.cpp b/paddle/gserver/layers/RowConvLayer.cpp
index 5302e0e1a8f5489b65ae93161b26551237950d99..54d77999ad5b30a8d9f4feaa02d81417957544a7 100644
--- a/paddle/gserver/layers/RowConvLayer.cpp
+++ b/paddle/gserver/layers/RowConvLayer.cpp
@@ -43,13 +43,14 @@ void RowConvLayer::forward(PassType passType) {
   resetOutput(height, width);
 
   const auto startPos = getInput(0).sequenceStartPositions->getVector(useGpu_);
-  wDims_ = TensorShape({contexLength_, width});
+  MatrixPtr w = weight_->getW();
+  wDims_ = TensorShape({w->getHeight(), w->getWidth()});
 
   MatrixPtr outV = getOutputValue();
   BufferArgs inputs;
   BufferArgs outputs;
   inputs.addArg(*getInputValue(0), *startPos);
-  inputs.addArg(*weight_->getW(), wDims_);
+  inputs.addArg(*w, wDims_);
   outputs.addArg(*getOutputValue(), *startPos, ADD_TO);
 
   {
diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py
index 1fd62cda508bc53b09067e70671cfa733f0818df..1c3d776a4f36870ba1fb1128da863dffc29debd9 100755
--- a/python/paddle/trainer_config_helpers/layers.py
+++ b/python/paddle/trainer_config_helpers/layers.py
@@ -191,6 +191,14 @@ class LayerType(object):
     PAD_LAYER = "pad"
     MULTIPLEX_LAYER = "multiplex"
     ROW_CONV_LAYER = "row_conv"
+
+    PRINT_LAYER = 'print'
+    PRIORBOX_LAYER = 'priorbox'
+
+    CTC_LAYER = 'ctc'
+    WARP_CTC_LAYER = 'warp_ctc'
+    CRF_LAYER = 'crf'
+    CRF_DECODING_LAYER = 'crf_decoding'
     NCE_LAYER = 'nce'
 
     RANK_COST = 'rank-cost'