chore: import upstream snapshot with attribution

test/cpp/inference/api/analyzer_capi_exp_tester.cc

@@ -0,0 +1,90 @@
+/* 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 <glog/logging.h>
+#include <gtest/gtest.h>
+
+#include <cstddef>
+#include <cstdint>
+#include <cstdio>
+#include <string>
+#include <vector>
+
+#include "paddle/common/flags.h"
+#include "paddle/fluid/inference/capi_exp/pd_config.h"
+#include "paddle/fluid/inference/capi_exp/pd_inference_api.h"
+#include "paddle/fluid/inference/capi_exp/pd_utils.h"
+
+PD_DEFINE_string(infer_model, "", "model path");
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+void predictor_run() {
+  std::string model_dir = FLAGS_infer_model;
+  std::string prog_file = model_dir + "/model";
+  std::string params_file = model_dir + "/params";
+  PD_Config *config = PD_ConfigCreate();
+  PD_ConfigDisableGpu(config);
+  PD_ConfigSetCpuMathLibraryNumThreads(config, 10);
+  PD_ConfigSwitchIrDebug(config, TRUE);
+  PD_ConfigSetModel(config, prog_file.c_str(), params_file.c_str());
+  PD_Cstr *config_summary = PD_ConfigSummary(config);
+  LOG(INFO) << config_summary->data;
+
+  PD_Predictor *predictor = PD_PredictorCreate(config);
+  PD_Tensor *tensor = PD_PredictorGetInputHandle(predictor, "data");
+
+  const int batch_size = 1;
+  const int channels = 3;
+  const int height = 318;
+  const int width = 318;
+  float *input = new float[batch_size * channels * height * width]();
+
+  std::array<int32_t, 4> shape = {batch_size, channels, height, width};
+  PD_TensorReshape(tensor, 4, shape.data());
+  PD_TensorCopyFromCpuFloat(tensor, input);
+  EXPECT_TRUE(PD_PredictorRun(predictor));
+
+  delete[] input;
+  PD_TensorDestroy(tensor);
+  PD_CstrDestroy(config_summary);
+  PD_PredictorDestroy(predictor);
+}
+
+TEST(PD_PredictorRun, predictor_run) { predictor_run(); }
+
+#ifdef PADDLE_WITH_DNNL
+TEST(PD_Config, profile_onednn) {
+  std::string model_dir = FLAGS_infer_model;
+  std::string prog_file = model_dir + "/model";
+  std::string params_file = model_dir + "/params";
+  PD_Config *config = PD_ConfigCreate();
+  PD_ConfigDisableGpu(config);
+  PD_ConfigSetCpuMathLibraryNumThreads(config, 10);
+  PD_ConfigSwitchIrDebug(config, TRUE);
+  PD_ConfigEnableONEDNN(config);
+  bool onednn_enable = PD_ConfigOnednnEnabled(config);
+  EXPECT_TRUE(onednn_enable);
+  PD_ConfigEnableOnednnBfloat16(config);
+  PD_ConfigSetOnednnCacheCapacity(config, 0);
+  PD_ConfigSetModel(config, prog_file.c_str(), params_file.c_str());
+  PD_ConfigDestroy(config);
+}
+#endif
+
+}  // namespace analysis
+}  // namespace inference
+}  // namespace paddle