/* 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 #include "../test_helper.h" #include "../test_include.h" int main() { #ifdef PADDLE_MOBILE_FPGA paddle_mobile::PaddleMobile paddle_mobile; #endif #ifdef PADDLE_MOBILE_CPU paddle_mobile::PaddleMobile paddle_mobile; #endif paddle_mobile.SetThreadNum(1); bool optimize = true; auto time1 = time(); if (paddle_mobile.Load(g_googlenet, optimize)) { auto time2 = paddle_mobile::time(); std::cout << "load cost :" << paddle_mobile::time_diff(time1, time2) << "ms" << std::endl; std::vector input; std::vector output; std::vector dims{1, 3, 224, 224}; GetInput(g_test_image_1x3x224x224, &input, dims); // warmup for (int i = 0; i < 10; ++i) { output = paddle_mobile.Predict(input, dims); } auto time3 = time(); for (int i = 0; i < 10; ++i) { output = paddle_mobile.Predict(input, dims); } auto time4 = time(); std::cout << "predict cost: " << time_diff(time3, time4) / 10 << "ms\n"; } return 0; }