diff --git a/core/general-client/example/simple_client.cpp b/core/general-client/example/simple_client.cpp
index fc89146731fd9ddae0fd1e2d0b0a06b301dbcdbf..cd60018880e7cb99a128b7346999e7daee1b3412 100644
--- a/core/general-client/example/simple_client.cpp
+++ b/core/general-client/example/simple_client.cpp
@@ -27,6 +27,92 @@ using baidu::paddle_serving::client::PredictorOutputs;
 DEFINE_string(server_port, "127.0.0.1:9292", "");
 DEFINE_string(client_conf, "serving_client_conf.prototxt", "");
 DEFINE_string(test_type, "brpc", "");
+DEFINE_string(sample_type, "fit_a_line", "");
+
+namespace {
+int prepare_fit_a_line(PredictorInputs& input, std::vector<std::string>& fetch_name) {
+  std::vector<float> float_feed = {0.0137f, -0.1136f, 0.2553f, -0.0692f,
+            0.0582f, -0.0727f, -0.1583f, -0.0584f,
+            0.6283f, 0.4919f, 0.1856f, 0.0795f, -0.0332f};
+  std::vector<int> float_shape = {1, 13};
+  std::string feed_name = "x";
+  fetch_name = {"price"};
+  std::vector<int> lod;
+  input.add_float_data(float_feed, feed_name, float_shape, lod);
+  return 0;
+}
+
+int prepare_bert(PredictorInputs& input, std::vector<std::string>& fetch_name) {
+  float input_mask[] = {
+      1.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+      0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+      0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+      0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+      0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+      0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+      0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+      0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+      0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+      0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f,
+      0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f};
+  long position_ids[] = {
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+      0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,  0, 0, 0, 0, 0, 0, 0};
+  long input_ids[] = {
+      101, 0,    0,    0,   0,    0,    0,    0,    0,    0,    0,    0, 0,
+      0,   0,    0,    0,   0,    0,    0,    0,    0,    0,    0,    0, 0,
+      0,   0,    0,    0,   0,    0,    0,    0,    0,    0,    0,    0, 0,
+      0,   0,    0,    0,   0,    0,    0,    0,    0,    0,    0,    0, 0,
+      0,   0,    0,    0,   0,    0,    0,    0,    0,    0,    0,    0, 0,
+      0,   0,    0,    0,   0,    0,    0,    0,    0,    0,    0,    0, 0,
+      0,   0,    0,    0,   0,    0,    0,    0,    0,    0,    0,    0, 0,
+      0,   0,    0,    0,   0,    0,    0,    0,    0,    0,    0,    0, 0,
+      0,   0,    0,    0,   0,    0,    0,    0,    0,    0,    0,    0, 0,
+      0,   0,    0,    0,   0,    0,    0,    0,    0,    0,    0};
+  long segment_ids[] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
+                        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0};
+  {
+    std::vector<float> float_feed(std::begin(input_mask), std::end(input_mask));
+    std::vector<int> float_shape = {1, 128, 1};
+    std::string feed_name = "input_mask";
+    std::vector<int> lod;
+    input.add_float_data(float_feed, feed_name, float_shape, lod);
+  }
+  {
+    std::vector<int64_t> feed(std::begin(position_ids), std::end(position_ids));
+    std::vector<int> shape = {1, 128, 1};
+    std::string feed_name = "position_ids";
+    std::vector<int> lod;
+    input.add_int64_data(feed, feed_name, shape, lod);
+  }
+  {
+    std::vector<int64_t> feed(std::begin(input_ids), std::end(input_ids));
+    std::vector<int> shape = {1, 128, 1};
+    std::string feed_name = "input_ids";
+    std::vector<int> lod;
+    input.add_int64_data(feed, feed_name, shape, lod);
+  }
+  {
+    std::vector<int64_t> feed(std::begin(segment_ids), std::end(segment_ids));
+    std::vector<int> shape = {1, 128, 1};
+    std::string feed_name = "segment_ids";
+    std::vector<int> lod;
+    input.add_int64_data(feed, feed_name, shape, lod);
+  }
+  
+  fetch_name = {"pooled_output"};
+  return 0;
+}
+} // namespace
 
 int main(int argc, char* argv[]) {
 
@@ -34,9 +120,11 @@ int main(int argc, char* argv[]) {
   std::string url = FLAGS_server_port;
   std::string conf = FLAGS_client_conf;
   std::string test_type = FLAGS_test_type;
+  std::string sample_type = FLAGS_sample_type;
   LOG(INFO) << "url = " << url << ";"
             << "client_conf = " << conf << ";"
-            << "type = " << test_type;
+            << "test_type = " << test_type
+            << "sample_type = " << sample_type;
   std::unique_ptr<ServingClient> client;
   if (test_type == "brpc") {
     client.reset(new ServingBrpcClient());
@@ -50,18 +138,19 @@ int main(int argc, char* argv[]) {
     return 0;
   }
 
-  std::vector<float> float_feed = {0.0137f, -0.1136f, 0.2553f, -0.0692f,
-            0.0582f, -0.0727f, -0.1583f, -0.0584f,
-            0.6283f, 0.4919f, 0.1856f, 0.0795f, -0.0332f};
-  std::vector<int> float_shape = {1, 13};
-  std::string feed_name = "x";
-  std::vector<std::string> fetch_name = {"price"};
-  std::vector<int> lod;
-
   PredictorInputs input;
   PredictorOutputs output;
+  std::vector<std::string> fetch_name;
 
-  input.add_float_data(float_feed, feed_name, float_shape, lod);
+  if (sample_type == "fit_a_line") {
+    prepare_fit_a_line(input, fetch_name);
+  }
+  else if (sample_type == "bert") {
+    prepare_bert(input, fetch_name);
+  }
+  else {
+    prepare_fit_a_line(input, fetch_name);
+  }
 
   if (client->predict(input, output, fetch_name, 0) != 0) {
     LOG(ERROR) << "Failed to predict!";