diff --git a/paddle/fluid/framework/device_worker.cc b/paddle/fluid/framework/device_worker.cc
index 6ba596ab1592dddddf2111ba67578bd98a450056..a2b9dff2c10f142a26ca3acc160b1f4cb794c226 100644
--- a/paddle/fluid/framework/device_worker.cc
+++ b/paddle/fluid/framework/device_worker.cc
@@ -24,7 +24,7 @@ void DeviceWorker::SetDataFeed(DataFeed* data_feed) {
 }
 
 template <typename T>
-std::string PrintLodTensorType(LoDTensor* tensor, int64_t start, int64_t end) {
+std::string PrintLodTensorType(Tensor* tensor, int64_t start, int64_t end) {
   auto count = tensor->numel();
   if (start < 0 || end > count) {
     VLOG(3) << "access violation";
@@ -37,8 +37,7 @@ std::string PrintLodTensorType(LoDTensor* tensor, int64_t start, int64_t end) {
   return os.str();
 }
 
-std::string PrintLodTensorIntType(LoDTensor* tensor, int64_t start,
-                                  int64_t end) {
+std::string PrintLodTensorIntType(Tensor* tensor, int64_t start, int64_t end) {
   auto count = tensor->numel();
   if (start < 0 || end > count) {
     VLOG(3) << "access violation";
@@ -51,7 +50,7 @@ std::string PrintLodTensorIntType(LoDTensor* tensor, int64_t start,
   return os.str();
 }
 
-std::string PrintLodTensor(LoDTensor* tensor, int64_t start, int64_t end) {
+std::string PrintLodTensor(Tensor* tensor, int64_t start, int64_t end) {
   std::string out_val;
   if (tensor->type() == proto::VarType::FP32) {
     out_val = PrintLodTensorType<float>(tensor, start, end);
diff --git a/paddle/fluid/framework/device_worker.h b/paddle/fluid/framework/device_worker.h
index f75d7593fe9a50d385d0e669e5037fbc5d4eea5b..8c6c729a33a9c313537fd6285c87a545ade18d3f 100644
--- a/paddle/fluid/framework/device_worker.h
+++ b/paddle/fluid/framework/device_worker.h
@@ -45,7 +45,7 @@ limitations under the License. */
 namespace paddle {
 namespace framework {
 
-std::string PrintLodTensor(LoDTensor* tensor, int64_t start, int64_t end);
+std::string PrintLodTensor(Tensor* tensor, int64_t start, int64_t end);
 std::pair<int64_t, int64_t> GetTensorBound(LoDTensor* tensor, int index);
 bool CheckValidOutput(LoDTensor* tensor, size_t batch_size);
 
@@ -148,6 +148,7 @@ class DeviceWorker {
   FetchConfig fetch_config_;
   bool use_cvm_;
   bool no_cvm_;
+  std::vector<std::string> all_param_;
 };
 
 class CPUWorkerBase : public DeviceWorker {
diff --git a/paddle/fluid/framework/downpour_worker.cc b/paddle/fluid/framework/downpour_worker.cc
index b1a1b73a66e72d95c68089832b0f0381e9382f95..c36f010a9417b4af9eebf7d86236ad277c1d2081 100644
--- a/paddle/fluid/framework/downpour_worker.cc
+++ b/paddle/fluid/framework/downpour_worker.cc
@@ -807,7 +807,50 @@ void DownpourWorker::TrainFiles() {
         }
       }
       if (!need_skip) {
+#ifdef PADDLE_WITH_PSLIB
+        try {
+          op->Run(*thread_scope_, place_);
+        } catch (std::exception& e) {
+          fprintf(stderr, "error message: %s\n", e.what());
+          auto& ins_id_vec = device_reader_->GetInsIdVec();
+          size_t batch_size = device_reader_->GetCurBatchSize();
+          std::string s = "";
+          for (auto& ins_id : ins_id_vec) {
+            if (s != "") s += ",";
+            s += ins_id;
+          }
+          fprintf(stderr, "batch_size: %zu, ins_ids_vec: %s\n", batch_size,
+                  s.c_str());
+          s = "";
+          for (auto& param : all_param_) {
+            Variable* var = thread_scope_->FindVar(param);
+            if (var == nullptr) {
+              continue;
+            }
+            Tensor* tensor = nullptr;
+            int64_t len = 0;
+            if (var->IsType<framework::LoDTensor>()) {
+              tensor = var->GetMutable<LoDTensor>();
+              len = tensor->numel();
+            } else if (var->IsType<SelectedRows>()) {
+              auto selected_rows = var->GetMutable<SelectedRows>();
+              tensor = selected_rows->mutable_value();
+              len = tensor->numel();
+            }
+            if (!tensor->IsInitialized()) {
+              continue;
+            }
+            s += param + ":" + std::to_string(len) + ":";
+            s += PrintLodTensor(tensor, 0, len);
+            fprintf(stderr, "%s\n", s.c_str());
+            fflush(stderr);
+            s = "";
+          }
+          throw e;
+        }
+#else
         op->Run(*thread_scope_, place_);
+#endif
       }
     }
 
diff --git a/paddle/fluid/framework/hogwild_worker.cc b/paddle/fluid/framework/hogwild_worker.cc
index db6231e99193d96714e4205fa174444a4ffede83..79ecef43087d7066ca557da8a17edd5c6800e9b6 100644
--- a/paddle/fluid/framework/hogwild_worker.cc
+++ b/paddle/fluid/framework/hogwild_worker.cc
@@ -72,6 +72,7 @@ void HogwildWorker::CreateThreadScope(const ProgramDesc &program) {
   thread_scope_ = &root_scope_->NewScope();
 
   for (auto &var : block.AllVars()) {
+    all_param_.push_back(var->Name());
     if (var->Persistable()) {
       auto *ptr = root_scope_->Var(var->Name());
       InitializeVariable(ptr, var->GetType());
diff --git a/paddle/fluid/operators/cvm_op.cc b/paddle/fluid/operators/cvm_op.cc
index 155f8f518f9046e53659a348fbc202f80586cddb..eae8197b1a1c7f84fdbcfa6cda1459ce303abbab 100644
--- a/paddle/fluid/operators/cvm_op.cc
+++ b/paddle/fluid/operators/cvm_op.cc
@@ -27,19 +27,11 @@ class CVMOp : public framework::OperatorWithKernel {
 
   void InferShape(framework::InferShapeContext* ctx) const override {
     OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "CVM");
-    OP_INOUT_CHECK(ctx->HasInput("CVM"), "Input", "CVM", "CVM");
     OP_INOUT_CHECK(ctx->HasOutput("Y"), "Output", "Y", "CVM");
 
     auto x_dims = ctx->GetInputDim("X");
-    auto cvm_dims = ctx->GetInputDim("CVM");
     PADDLE_ENFORCE_EQ(x_dims.size(), 2UL, platform::errors::InvalidArgument(
                                               "Input(X)'s rank should be 2."));
-    PADDLE_ENFORCE_EQ(
-        cvm_dims.size(), 2UL,
-        platform::errors::InvalidArgument("Input(CVM)'s rank should be 2."));
-    PADDLE_ENFORCE_EQ(cvm_dims[1], 2UL, platform::errors::InvalidArgument(
-                                            "The 2nd dimension of "
-                                            "Input(CVM) should be 2."));
 
     if (ctx->Attrs().Get<bool>("use_cvm")) {
       ctx->SetOutputDim("Y", {x_dims[0], x_dims[1]});