[Mobile]Change filename of unit test. (#3365)

mobile/test/CMakeLists.txt

@@ -549,7 +549,7 @@ if (ENABLE_ALL_TEST)
         ADD_EXECUTABLE(test-net-performance net/test_net_performance.cpp test_helper.h test_include.h executor_for_test.h)
         target_link_libraries(test-net-performance paddle-mobile)
 
-        ADD_EXECUTABLE(test-inference-api-v2 net/test_inference_api_v2.cpp test_helper.h test_include.h executor_for_test.h)
+        ADD_EXECUTABLE(test-inference-ercy net/test_inference_ercy.cpp test_helper.h test_include.h executor_for_test.h)
         target_link_libraries(test-inference-api-v2 paddle-mobile)
 
         if (GPU_CL)
@@ -566,6 +566,6 @@ else ()
     ADD_EXECUTABLE(test-net-benchmark net/test_net_benchmark.cpp test_helper.h test_include.h)
     target_link_libraries(test-net-benchmark paddle-mobile)
 
-    ADD_EXECUTABLE(test-inference-api-v2 net/test_inference_api_v2.cpp test_helper.h test_include.h executor_for_test.h)
+    ADD_EXECUTABLE(test-inference-ercy net/test_inference_ercy.cpp test_helper.h test_include.h executor_for_test.h)
     target_link_libraries(test-inference-api-v2 paddle-mobile)
 endif ()

mobile/test/net/test_inference_m2fm.cpp

+/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include <iostream>
+#include "../test_helper.h"
+#include "io/paddle_inference_api.h"
+
+using namespace paddle_mobile;  // NOLINT
+
+PaddleMobileConfig GetConfig() {
+  PaddleMobileConfig config;
+  config.precision = PaddleMobileConfig::FP32;
+  config.device = PaddleMobileConfig::kGPU_CL;
+  config.pre_post_type = PaddleMobileConfig::NONE_PRE_POST;
+
+  config.prog_file = "../models/m2fm/model";
+  config.param_file = "../models/m2fm/params";
+  config.lod_mode = false;
+  config.load_when_predict = false;
+  return config;
+}
+
+int main() {
+  PaddleMobileConfig config = GetConfig();
+  auto predictor =
+      CreatePaddlePredictor<PaddleMobileConfig,
+                            PaddleEngineKind::kPaddleMobile>(config);
+
+  // factor
+  int factor_len = 1 * 256 * 1 * 1;
+  std::vector<float> factor_v;
+  std::vector<int64_t> factor_dims{1, 256, 1, 1};
+  GetInput<float>(g_test_image_1x3x224x224, &factor_v, factor_dims);
+
+  PaddleTensor factor;
+  factor.shape = std::vector<int>({1, 256, 1, 1});
+  factor.data = PaddleBuf(factor_v.data(), factor_len * sizeof(float));
+  factor.dtype = PaddleDType::FLOAT32;
+  factor.layout = LayoutType::LAYOUT_CHW;
+
+  // remap
+  int remap_len = 1 * 256 * 256 * 2;
+  std::vector<float> remap_v;
+  std::vector<int64_t> remap_dims{1, 256, 256, 2};
+  GetInput<float>(g_test_image_1x3x224x224, &remap_v, remap_dims);
+
+  PaddleTensor remap;
+  remap.shape = std::vector<int>({1, 256, 256, 2});
+  remap.data = PaddleBuf(remap_v.data(), remap_len * sizeof(float));
+  remap.dtype = PaddleDType::FLOAT32;
+  remap.layout = LayoutType::LAYOUT_CHW;
+
+  // image
+  int image_len = 1 * 3 * 256 * 256;
+  std::vector<float> image_v;
+  std::vector<int64_t> image_dims{1, 3, 256, 256};
+  GetInput<float>(g_test_image_1x3x224x224, &image_v, image_dims);
+
+  PaddleTensor image;
+  image.shape = std::vector<int>({1, 3, 256, 256});
+  image.data = PaddleBuf(image_v.data(), image_len * sizeof(float));
+  image.dtype = PaddleDType::FLOAT32;
+  image.layout = LayoutType::LAYOUT_CHW;
+
+  PaddleTensor output0;
+  output0.shape = std::vector<int>({});
+  output0.data = PaddleBuf();
+  output0.dtype = PaddleDType::FLOAT32;
+  output0.layout = LayoutType::LAYOUT_CHW;
+
+  PaddleTensor output1;
+  output1.shape = std::vector<int>({});
+  output1.data = PaddleBuf();
+  output1.dtype = PaddleDType::FLOAT32;
+  output1.layout = LayoutType::LAYOUT_CHW;
+
+  PaddleTensor output2;
+  output2.shape = std::vector<int>({});
+  output2.data = PaddleBuf();
+  output2.dtype = PaddleDType::FLOAT32;
+  output2.layout = LayoutType::LAYOUT_CHW;
+
+  PaddleTensor output3;
+  output3.shape = std::vector<int>({});
+  output3.data = PaddleBuf();
+  output3.dtype = PaddleDType::FLOAT32;
+  output3.layout = LayoutType::LAYOUT_CHW;
+
+  predictor->Feed("x2paddle_mul_factor", factor);
+  predictor->Feed("x2paddle_base_remap", remap);
+  predictor->Feed("x2paddle_image", image);
+  predictor->Run();
+  predictor->Fetch("save_infer_model/scale_0", &output0);
+  predictor->Fetch("save_infer_model/scale_1", &output1);
+  predictor->Fetch("save_infer_model/scale_2", &output2);
+  predictor->Fetch("save_infer_model/scale_3", &output3);
+
+  float* out_ptr0 = reinterpret_cast<float*>(output0.data.data());
+  float* out_ptr1 = reinterpret_cast<float*>(output1.data.data());
+  std::cout << " print output0 : " << std::endl;
+  int numel = output0.data.length() / sizeof(float);
+  int stride = numel / 20;
+  stride = stride > 0 ? stride : 1;
+  for (size_t j = 0; j < numel; j += stride) {
+    std::cout << out_ptr0[j] << " ";
+  }
+  std::cout << std::endl;
+
+  std::cout << " print output1 : " << std::endl;
+  numel = output1.data.length() / sizeof(float);
+  stride = numel / 20;
+  stride = stride > 0 ? stride : 1;
+  for (size_t j = 0; j < numel; j += stride) {
+    std::cout << out_ptr1[j] << " ";
+  }
+  std::cout << std::endl;
+
+  return 0;
+}