text: /* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
  
  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 <gtest/gtest.h>
  #include "gflags/gflags.h"
  #include "paddle/fluid/inference/tests/test_helper.h"
  
  DEFINE_string(dirname, "", "Directory of the inference model.");
  
  TEST(inference, word2vec) {
    if (FLAGS_dirname.empty()) {
      LOG(FATAL) << "Usage: ./example --dirname=path/to/your/model";
    }
  
    LOG(INFO) << "FLAGS_dirname: " << FLAGS_dirname << std::endl;
    std::string dirname = FLAGS_dirname;
  
    // 0. Call `paddle::framework::InitDevices()` initialize all the devices
    // In unittests, this is done in paddle/testing/paddle_gtest_main.cc
  
    paddle::framework::LoDTensor first_word, second_word, third_word, fourth_word;
    paddle::framework::LoD lod{{0, 1}};
    int64_t dict_size = 2072;  // Hard-coding the size of dictionary
  
    SetupLoDTensor(first_word, lod, static_cast<int64_t>(0), dict_size);
    SetupLoDTensor(second_word, lod, static_cast<int64_t>(0), dict_size);
    SetupLoDTensor(third_word, lod, static_cast<int64_t>(0), dict_size);
    SetupLoDTensor(fourth_word, lod, static_cast<int64_t>(0), dict_size);
  
    std::vector<paddle::framework::LoDTensor*> cpu_feeds;
    cpu_feeds.push_back(&first_word);
    cpu_feeds.push_back(&second_word);
    cpu_feeds.push_back(&third_word);
    cpu_feeds.push_back(&fourth_word);
  
    paddle::framework::LoDTensor output1;
    std::vector<paddle::framework::LoDTensor*> cpu_fetchs1;
    cpu_fetchs1.push_back(&output1);
  
    // Run inference on CPU
    TestInference<paddle::platform::CPUPlace>(dirname, cpu_feeds, cpu_fetchs1);
    LOG(INFO) << output1.lod();
    LOG(INFO) << output1.dims();
  
  #ifdef PADDLE_WITH_CUDA
    paddle::framework::LoDTensor output2;
    std::vector<paddle::framework::LoDTensor*> cpu_fetchs2;
    cpu_fetchs2.push_back(&output2);
  
    // Run inference on CUDA GPU
    TestInference<paddle::platform::CUDAPlace>(dirname, cpu_feeds, cpu_fetchs2);
    LOG(INFO) << output2.lod();
    LOG(INFO) << output2.dims();
  
    CheckError<float>(output1, output2);
  #endif
  }
  