add test-net-benchmark (#1722)

test/CMakeLists.txt

@@ -520,4 +520,7 @@ if (NOT FOUND_MATCH)
 
     ADD_EXECUTABLE(test-conv-gpu operators/test_conv_gpu.cpp test_helper.h test_include.h)
     target_link_libraries(test-conv-gpu paddle-mobile)
+
+    ADD_EXECUTABLE(test-net-benchmark net/test_net_benchmark.cpp test_helper.h test_include.h)
+    target_link_libraries(test-net-benchmark paddle-mobile)
 endif ()

test/net/test_net_benchmark.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 "../test_include.h"
+
+int main() {
+  paddle_mobile::PaddleMobile<paddle_mobile::CPU> paddle_mobile;
+  paddle_mobile.SetThreadNum(1);
+  auto time1 = paddle_mobile::time();
+
+  auto isok =
+      paddle_mobile.Load(std::string(g_yolo) + "/model",
+                         std::string(g_yolo) + "/params", true, false, 1, true);
+  if (isok) {
+    auto time2 = paddle_mobile::time();
+    std::cout << "load cost :" << paddle_mobile::time_diff(time1, time1) << "ms"
+              << std::endl;
+
+    std::vector<float> input;
+    std::vector<int64_t> dims{1, 3, 64, 64};
+    GetInput<float>(g_test_image_1x3x224x224_banana, &input, dims);
+
+    paddle_mobile::framework::DDim ddim =
+        paddle_mobile::framework::make_ddim(dims);
+    Tensor feed_tensor(input, paddle_mobile::framework::make_ddim(dims));
+
+    // 预热十次
+    for (int i = 0; i < 10; ++i) {
+      //      auto vec_result = paddle_mobile.Predict(input, dims);
+      paddle_mobile.Feed("data", feed_tensor);
+      paddle_mobile.Predict();
+    }
+    auto time3 = paddle_mobile::time();
+    for (int i = 0; i < 100; ++i) {
+      //      auto vec_result = paddle_mobile.Predict(input, dims);
+      paddle_mobile.Feed("data", feed_tensor);
+      paddle_mobile.Predict();
+    }
+    auto time4 = paddle_mobile::time();
+    std::cout << "predict cost :"
+              << paddle_mobile::time_diff(time3, time4) / 100 << "ms"
+              << std::endl;
+  }
+
+  return 0;
+}