diff --git a/paddle/fluid/inference/tests/api/analyzer_resnet50_tester.cc b/paddle/fluid/inference/tests/api/analyzer_resnet50_tester.cc
index c2151eea0823f80feb17b014c1f739d2a15ae862..cd04d888a503aaa53efbcd76ae98d5e5242e1a3f 100644
--- a/paddle/fluid/inference/tests/api/analyzer_resnet50_tester.cc
+++ b/paddle/fluid/inference/tests/api/analyzer_resnet50_tester.cc
@@ -30,25 +30,7 @@ void SetConfig(AnalysisConfig *cfg) {
 }
 
 void SetInput(std::vector<std::vector<PaddleTensor>> *inputs) {
-  PADDLE_ENFORCE_EQ(FLAGS_test_all_data, 0, "Only have single batch of data.");
-
-  PaddleTensor input;
-  // channel=3, height/width=318
-  std::vector<int> shape({FLAGS_batch_size, 3, 318, 318});
-  input.shape = shape;
-  input.dtype = PaddleDType::FLOAT32;
-
-  // fill input data, for profile easily, do not use random data here.
-  size_t size = FLAGS_batch_size * 3 * 318 * 318;
-  input.data.Resize(size * sizeof(float));
-  float *input_data = static_cast<float *>(input.data.data());
-  for (size_t i = 0; i < size; i++) {
-    *(input_data + i) = static_cast<float>(i) / size;
-  }
-
-  std::vector<PaddleTensor> input_slots;
-  input_slots.assign({input});
-  (*inputs).emplace_back(input_slots);
+  SetFakeImageInput(inputs, FLAGS_infer_model);
 }
 
 // Easy for profiling independently.
diff --git a/paddle/fluid/inference/tests/api/tester_helper.h b/paddle/fluid/inference/tests/api/tester_helper.h
index 19c3f532d5dcb7588793fa21fa179f6b48649103..79468da03a5064a37ee7471cd7ce2b7769a5c786 100644
--- a/paddle/fluid/inference/tests/api/tester_helper.h
+++ b/paddle/fluid/inference/tests/api/tester_helper.h
@@ -25,6 +25,7 @@
 #include "paddle/fluid/inference/api/analysis_predictor.h"
 #include "paddle/fluid/inference/api/helper.h"
 #include "paddle/fluid/inference/api/paddle_inference_pass.h"
+#include "paddle/fluid/inference/tests/test_helper.h"
 #include "paddle/fluid/platform/profiler.h"
 
 DEFINE_string(infer_model, "", "model path");
@@ -105,6 +106,35 @@ std::unordered_map<std::string, int> GetFuseStatis(PaddlePredictor *predictor,
   return fuse_statis;
 }
 
+void SetFakeImageInput(std::vector<std::vector<PaddleTensor>> *inputs,
+                       const std::string &dirname,
+                       const bool is_combined = true) {
+  // Set fake_image_data
+  PADDLE_ENFORCE_EQ(FLAGS_test_all_data, 0, "Only have single batch of data.");
+  std::vector<std::vector<int64_t>> feed_target_shapes =
+      GetFeedTargetShapes(dirname, is_combined);
+  int dim1 = feed_target_shapes[0][1];
+  int dim2 = feed_target_shapes[0][2];
+  int dim3 = feed_target_shapes[0][3];
+
+  PaddleTensor input;
+  std::vector<int> shape({FLAGS_batch_size, dim1, dim2, dim3});
+  input.shape = shape;
+  input.dtype = PaddleDType::FLOAT32;
+
+  // fill input data, for profile easily, do not use random data here.
+  size_t size = FLAGS_batch_size * dim1 * dim2 * dim3;
+  input.data.Resize(size * sizeof(float));
+  float *input_data = static_cast<float *>(input.data.data());
+  for (size_t i = 0; i < size; i++) {
+    *(input_data + i) = static_cast<float>(i) / size;
+  }
+
+  std::vector<PaddleTensor> input_slots;
+  input_slots.assign({input});
+  (*inputs).emplace_back(input_slots);
+}
+
 void TestOneThreadPrediction(
     const AnalysisConfig &config,
     const std::vector<std::vector<PaddleTensor>> &inputs,
diff --git a/paddle/fluid/inference/tests/test_helper.h b/paddle/fluid/inference/tests/test_helper.h
index 94f0550df57e79fa68c135f5c9c4b7effe6ac156..e26094c0dbc6497ec79492cb049821c1059c28c8 100644
--- a/paddle/fluid/inference/tests/test_helper.h
+++ b/paddle/fluid/inference/tests/test_helper.h
@@ -101,8 +101,8 @@ std::unique_ptr<paddle::framework::ProgramDesc> InitProgram(
     // Hard-coding the file names of program and parameters in unittest.
     // The file names should be consistent with that used in Python API
     //  `fluid.io.save_inference_model`.
-    std::string prog_filename = "__model_combined__";
-    std::string param_filename = "__params_combined__";
+    std::string prog_filename = "model";
+    std::string param_filename = "params";
     inference_program =
         paddle::inference::Load(executor, scope, dirname + "/" + prog_filename,
                                 dirname + "/" + param_filename);
@@ -261,5 +261,3 @@ void TestInference(const std::string& dirname,
 
   delete scope;
 }
-
-USE_PASS(graph_to_program_pass);