Function TEST

test/cpp/inference/api/paddle_infer_api_test.cc:23–60

namespace paddle_infer {

TEST(Predictor, use_gpu) {
  LOG(INFO) << GetVersion();
  UpdateDllFlag("conv_workspace_size_limit", "4000");
  std::string model_dir = FLAGS_infer_model + "/model";
  Config config;
  config.EnableNewIR(false);
  config.SetModel(model_dir + "/model", model_dir + "/params");
  config.EnableUseGpu(100, 0);

  auto predictor = CreatePredictor(config);
  auto pred_clone = predictor->Clone();

  std::vector<int> in_shape = {1, 3, 318, 318};
  int in_num =
      std::accumulate(in_shape.begin(), in_shape.end(), 1, [](int &a, int &b) {
        return a * b;
      });

  std::vector<float> input(in_num, 0);

  auto input_names = predictor->GetInputNames();
  auto input_t = predictor->GetInputHandle(input_names[0]);

  input_t->Reshape(in_shape);
  input_t->CopyFromCpu(input.data());
  predictor->Run();

  auto output_names = predictor->GetOutputNames();
  auto output_t = predictor->GetOutputHandle(output_names[0]);
  std::vector<int> output_shape = output_t->shape();
  int out_num = std::accumulate(
      output_shape.begin(), output_shape.end(), 1, std::multiplies<int>());

  std::vector<float> out_data;
  out_data.resize(out_num);
  output_t->CopyToCpu(out_data.data());
  predictor->ClearIntermediateTensor();
}

TEST(PredictorPool, basic) {
  LOG(INFO) << GetVersion();