chore: import upstream snapshot with attribution

test/cpp/inference/api/analyzer_image_classification_tester.cc

@@ -0,0 +1,99 @@
+/* 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 <fstream>
+#include <iostream>
+
+#include "test/cpp/inference/api/tester_helper.h"
+
+PD_DEFINE_bool(disable_onednn_fc, false, "Disable usage of ONE-DNN's FC op");
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+void SetConfig(AnalysisConfig *cfg) {
+  cfg->SetModel(FLAGS_infer_model + "/model", FLAGS_infer_model + "/params");
+  cfg->DisableGpu();
+  cfg->SwitchIrOptim();
+  cfg->SwitchSpecifyInputNames();
+  cfg->SetCpuMathLibraryNumThreads(FLAGS_cpu_num_threads);
+  cfg->DeletePass("constant_folding_pass");
+}
+
+void SetInput(std::vector<std::vector<PaddleTensor>> *inputs) {
+  SetFakeImageInput(inputs, FLAGS_infer_model);
+}
+
+// Easy for profiling independently.
+void profile(bool use_onednn = false) {
+  AnalysisConfig cfg;
+  SetConfig(&cfg);
+
+  if (use_onednn) {
+    cfg.EnableONEDNN();
+    if (FLAGS_disable_onednn_fc) {
+      cfg.DisableOnednnFcPasses();
+    }
+  }
+  std::vector<std::vector<PaddleTensor>> outputs;
+
+  std::vector<std::vector<PaddleTensor>> input_slots_all;
+  SetInput(&input_slots_all);
+  TestPrediction(reinterpret_cast<const PaddlePredictor::Config *>(&cfg),
+                 input_slots_all,
+                 &outputs,
+                 FLAGS_num_threads);
+}
+
+TEST(Analyzer_resnet50, profile) { profile(); }
+#ifdef PADDLE_WITH_DNNL
+TEST(Analyzer_resnet50, profile_onednn) { profile(true /* use_onednn */); }
+#endif
+
+// Compare result of NativeConfig and AnalysisConfig
+void compare(bool use_onednn = false) {
+  AnalysisConfig cfg;
+  SetConfig(&cfg);
+  if (use_onednn) {
+    cfg.EnableONEDNN();
+    if (FLAGS_disable_onednn_fc) {
+      cfg.DisableOnednnFcPasses();
+    }
+  }
+
+  std::vector<std::vector<PaddleTensor>> input_slots_all;
+  SetInput(&input_slots_all);
+  CompareNativeAndAnalysis(
+      reinterpret_cast<const PaddlePredictor::Config *>(&cfg), input_slots_all);
+}
+
+TEST(Analyzer_resnet50, compare) { compare(); }
+#ifdef PADDLE_WITH_DNNL
+TEST(Analyzer_resnet50, compare_onednn) { compare(true /* use_onednn */); }
+#endif
+
+// Compare Deterministic result
+TEST(Analyzer_resnet50, compare_determine) {
+  AnalysisConfig cfg;
+  SetConfig(&cfg);
+  std::vector<std::vector<PaddleTensor>> input_slots_all;
+  SetInput(&input_slots_all);
+  CompareDeterministic(reinterpret_cast<const PaddlePredictor::Config *>(&cfg),
+                       input_slots_all);
+}
+
+}  // namespace analysis
+}  // namespace inference
+}  // namespace paddle