chore: import upstream snapshot with attribution

test/cpp/inference/infer_ut/test_LeViT.cc

@@ -0,0 +1,253 @@
+// Copyright (c) 2021 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 "test_suite.h"  // NOLINT
+#ifdef PADDLE_WITH_GPU
+#include <cuda_runtime.h>
+#endif
+
+DEFINE_string(modeldir, "", "Directory of the inference model.");
+
+namespace paddle_infer {
+
+paddle::test::Record PrepareInput(int batch_size) {
+  // init input data
+  int channel = 3;
+  int width = 224;
+  int height = 224;
+  paddle::test::Record image_Record;
+  int input_num = batch_size * channel * width * height;
+  std::vector<float> input_data(input_num, 1);
+  image_Record.data = input_data;
+  image_Record.shape = std::vector<int>{batch_size, channel, width, height};
+  image_Record.type = paddle::PaddleDType::FLOAT32;
+  return image_Record;
+}
+
+TEST(gpu_tester_LeViT, analysis_gpu_bz1) {
+  // init input data
+  std::map<std::string, paddle::test::Record> my_input_data_map;
+  my_input_data_map["x"] = PrepareInput(1);
+  // init output data
+  std::map<std::string, paddle::test::Record> infer_output_data,
+      truth_output_data;
+  // prepare ground truth config
+  paddle_infer::Config config, config_no_ir;
+  config_no_ir.SetModel(FLAGS_modeldir + "/inference.pdmodel",
+                        FLAGS_modeldir + "/inference.pdiparams");
+  config_no_ir.SwitchIrOptim(false);
+  // prepare inference config
+  config.SetModel(FLAGS_modeldir + "/inference.pdmodel",
+                  FLAGS_modeldir + "/inference.pdiparams");
+  // get ground truth by disable ir
+  paddle_infer::services::PredictorPool pred_pool_no_ir(config_no_ir, 1);
+  SingleThreadPrediction(
+      pred_pool_no_ir.Retrieve(0), &my_input_data_map, &truth_output_data, 1);
+  // get infer results
+  paddle_infer::services::PredictorPool pred_pool(config, 1);
+  SingleThreadPrediction(
+      pred_pool.Retrieve(0), &my_input_data_map, &infer_output_data);
+  // check outputs
+  CompareRecord(&truth_output_data, &infer_output_data);
+  std::cout << "finish test" << std::endl;
+}
+
+TEST(tensorrt_tester_LeViT, trt_fp32_bz2) {
+  // init input data
+  std::map<std::string, paddle::test::Record> my_input_data_map;
+  my_input_data_map["x"] = PrepareInput(2);
+  // init output data
+  std::map<std::string, paddle::test::Record> infer_output_data,
+      truth_output_data;
+  // prepare ground truth config
+  paddle_infer::Config config, config_no_ir;
+  config_no_ir.SetModel(FLAGS_modeldir + "/inference.pdmodel",
+                        FLAGS_modeldir + "/inference.pdiparams");
+  config_no_ir.SwitchIrOptim(false);
+  // prepare inference config
+  config.SetModel(FLAGS_modeldir + "/inference.pdmodel",
+                  FLAGS_modeldir + "/inference.pdiparams");
+  config.EnableUseGpu(100, 0);
+  config.EnableTensorRtEngine(
+      1 << 20, 2, 50, paddle_infer::PrecisionType::kFloat32, false, false);
+  // get ground truth by disable ir
+  paddle_infer::services::PredictorPool pred_pool_no_ir(config_no_ir, 1);
+  SingleThreadPrediction(
+      pred_pool_no_ir.Retrieve(0), &my_input_data_map, &truth_output_data, 1);
+  // get infer results
+  paddle_infer::services::PredictorPool pred_pool(config, 1);
+  SingleThreadPrediction(
+      pred_pool.Retrieve(0), &my_input_data_map, &infer_output_data);
+  // check outputs
+  CompareRecord(&truth_output_data, &infer_output_data);
+  std::cout << "finish test" << std::endl;
+}
+
+TEST(tensorrt_tester_LeViT, serial_diff_batch_trt_fp32) {
+  int max_batch_size = 5;
+  // prepare ground truth config
+  paddle_infer::Config config, config_no_ir;
+  config_no_ir.SetModel(FLAGS_modeldir + "/inference.pdmodel",
+                        FLAGS_modeldir + "/inference.pdiparams");
+  config_no_ir.SwitchIrOptim(false);
+  paddle_infer::services::PredictorPool pred_pool_no_ir(config_no_ir, 1);
+  // prepare inference config
+  config.SetModel(FLAGS_modeldir + "/inference.pdmodel",
+                  FLAGS_modeldir + "/inference.pdiparams");
+  config.EnableUseGpu(100, 0);
+  config.EnableTensorRtEngine(1 << 20,
+                              max_batch_size,
+                              50,
+                              paddle_infer::PrecisionType::kFloat32,
+                              false,
+                              false);
+  paddle_infer::services::PredictorPool pred_pool(config, 1);
+
+  for (int i = 1; i < max_batch_size; i++) {
+    // init input data
+    std::map<std::string, paddle::test::Record> my_input_data_map;
+    my_input_data_map["x"] = PrepareInput(i);
+    // init output data
+    std::map<std::string, paddle::test::Record> infer_output_data,
+        truth_output_data;
+    // get ground truth by disable ir
+    SingleThreadPrediction(
+        pred_pool_no_ir.Retrieve(0), &my_input_data_map, &truth_output_data, 1);
+    // get infer results
+    SingleThreadPrediction(
+        pred_pool.Retrieve(0), &my_input_data_map, &infer_output_data);
+    // check outputs
+    CompareRecord(&truth_output_data, &infer_output_data);
+  }
+  std::cout << "finish test" << std::endl;
+}
+
+TEST(tensorrt_tester_LeViT, multi_thread4_trt_fp32_bz2) {
+  int thread_num = 4;
+  // init input data
+  std::map<std::string, paddle::test::Record> my_input_data_map;
+  my_input_data_map["x"] = PrepareInput(2);
+  // init output data
+  std::map<std::string, paddle::test::Record> infer_output_data,
+      truth_output_data;
+  // prepare ground truth config
+  paddle_infer::Config config, config_no_ir;
+  config_no_ir.SetModel(FLAGS_modeldir + "/inference.pdmodel",
+                        FLAGS_modeldir + "/inference.pdiparams");
+  config_no_ir.SwitchIrOptim(false);
+  // prepare inference config
+  config.SetModel(FLAGS_modeldir + "/inference.pdmodel",
+                  FLAGS_modeldir + "/inference.pdiparams");
+  config.EnableUseGpu(100, 0);
+  config.EnableTensorRtEngine(
+      1 << 20, 2, 50, paddle_infer::PrecisionType::kFloat32, false, false);
+  // get ground truth by disable ir
+  paddle_infer::services::PredictorPool pred_pool_no_ir(config_no_ir, 1);
+  SingleThreadPrediction(
+      pred_pool_no_ir.Retrieve(0), &my_input_data_map, &truth_output_data, 1);
+
+  // get infer results from multi threads
+  std::vector<std::thread> threads;
+  services::PredictorPool pred_pool(config, thread_num);
+  for (int i = 0; i < thread_num; ++i) {
+    threads.emplace_back(paddle::test::SingleThreadPrediction,
+                         pred_pool.Retrieve(i),
+                         &my_input_data_map,
+                         &infer_output_data,
+                         10);
+  }
+
+  // thread join & check outputs
+  for (int i = 0; i < thread_num; ++i) {
+    LOG(INFO) << "join tid : " << i;
+    threads[i].join();
+    CompareRecord(&truth_output_data, &infer_output_data);
+  }
+
+  std::cout << "finish multi-thread test" << std::endl;
+}
+
+#ifdef PADDLE_WITH_GPU
+TEST(tensorrt_tester_LeViT, multi_stream_thread4_trt_fp32_bz2) {
+  int thread_num = 4;
+
+  // init stream
+  std::vector<cudaStream_t> streams(thread_num);
+  for (size_t i = 0; i < thread_num; ++i) {
+    cudaStreamCreate(&streams[i]);
+  }
+
+  // init input data
+  std::map<std::string, paddle::test::Record> my_input_data_map;
+  my_input_data_map["x"] = PrepareInput(2);
+  // init output data
+  std::map<std::string, paddle::test::Record> infer_output_data,
+      truth_output_data;
+  // prepare ground truth config
+  paddle_infer::Config config, config_no_ir;
+  config_no_ir.SetModel(FLAGS_modeldir + "/inference.pdmodel",
+                        FLAGS_modeldir + "/inference.pdiparams");
+  config_no_ir.SwitchIrOptim(false);
+  // prepare inference config
+  config.SetModel(FLAGS_modeldir + "/inference.pdmodel",
+                  FLAGS_modeldir + "/inference.pdiparams");
+  config.EnableUseGpu(100, 0);
+  config.EnableTensorRtEngine(
+      1 << 20, 2, 50, paddle_infer::PrecisionType::kFloat32, false, false);
+  // get ground truth by disable ir
+
+  paddle_infer::services::PredictorPool pred_pool_no_ir(config_no_ir, 1);
+  SingleThreadPrediction(
+      pred_pool_no_ir.Retrieve(0), &my_input_data_map, &truth_output_data, 1);
+
+  // get infer results from multi threads
+  std::vector<std::thread> threads;
+  config.SetExecStream(streams[0]);
+  config.pass_builder()->DeletePass("add_support_int8_pass");
+  auto main_predictor = CreatePredictor(config);
+  std::vector<decltype(main_predictor)> predictors;
+  for (size_t i = 0; i < thread_num - 1; ++i) {
+    predictors.push_back(std::move(main_predictor->Clone(streams[i + 1])));
+    LOG(INFO) << "predictors[" << i << "] stream is "
+              << predictors[i]->GetExecStream();
+  }
+  predictors.push_back(std::move(main_predictor));
+  LOG(INFO) << "predictors[" << thread_num - 1 << "] stream is "
+            << predictors[thread_num - 1]->GetExecStream();
+  for (int i = 0; i < thread_num; ++i) {
+    threads.emplace_back(paddle::test::SingleThreadPrediction,
+                         predictors[i].get(),
+                         &my_input_data_map,
+                         &infer_output_data,
+                         10);
+  }
+
+  // thread join & check outputs
+  for (int i = 0; i < thread_num; ++i) {
+    LOG(INFO) << "join tid : " << i;
+    threads[i].join();
+    CompareRecord(&truth_output_data, &infer_output_data);
+  }
+
+  std::cout << "finish multi-thread test" << std::endl;
+}
+#endif
+
+}  // namespace paddle_infer
+
+int main(int argc, char** argv) {
+  ::testing::InitGoogleTest(&argc, argv);
+  gflags::ParseCommandLineFlags(&argc, &argv, true);
+  return RUN_ALL_TESTS();
+}