chore: import upstream snapshot with attribution

test/cpp/inference/api/trt_quant_int8_test.cc

@@ -0,0 +1,68 @@
+/* Copyright (c) 2019 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 <glog/logging.h>
+#include <gtest/gtest.h>
+
+#include <numeric>
+
+#include "paddle/common/flags.h"
+#include "test/cpp/inference/api/trt_test_helper.h"
+
+namespace paddle {
+namespace inference {
+
+TEST(quant_int8, resnet50) {
+  std::string model_dir = FLAGS_infer_model;
+  AnalysisConfig config;
+  config.EnableUseGpu(1000, 0);
+  config.SetModel(model_dir);
+  config.EnableTensorRtEngine(
+      1 << 30, 1, 1, AnalysisConfig::Precision::kInt8, false, false);
+  std::map<std::string, std::vector<int>> min_input_shape = {
+      {"image", {1, 1, 3, 3}}};
+  std::map<std::string, std::vector<int>> max_input_shape = {
+      {"image", {1, 1, 10, 10}}};
+  std::map<std::string, std::vector<int>> opt_input_shape = {
+      {"image", {1, 1, 3, 3}}};
+
+  config.SetTRTDynamicShapeInfo(
+      min_input_shape, max_input_shape, opt_input_shape);
+  auto predictor = CreatePaddlePredictor(config);
+  auto input_names = predictor->GetInputNames();
+  int channels = 1;
+  int height = 3;
+  int width = 3;
+  int input_num = channels * height * width * 1;
+
+  float *input = new float[input_num];
+  memset(input, 0, input_num * sizeof(float));
+  auto input_t = predictor->GetInputTensor(input_names[0]);
+  input_t->Reshape({1, channels, height, width});
+  input_t->copy_from_cpu(input);
+
+  ASSERT_TRUE(predictor->ZeroCopyRun());
+
+  std::vector<float> out_data;
+  auto output_names = predictor->GetOutputNames();
+  auto output_t = predictor->GetOutputTensor(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>());
+  out_data.resize(out_num);
+  output_t->copy_to_cpu(out_data.data());
+}
+
+}  // namespace inference
+}  // namespace paddle