chore: import upstream snapshot with attribution

test/cpp/inference/api/analyzer_capi_tester.cc

@@ -0,0 +1,98 @@
+/* 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 <stddef.h>
+#include <stdint.h>
+#include <stdio.h>
+
+#include <string>
+#include <vector>
+
+#include "paddle/fluid/inference/capi/paddle_c_api.h"
+#include "test/cpp/inference/api/tester_helper.h"
+
+namespace paddle {
+namespace inference {
+namespace analysis {
+
+void zero_copy_run() {
+  std::string model_dir = FLAGS_infer_model;
+  std::string prog_file = model_dir + "/model";
+  std::string params_file = model_dir + "/params";
+  PD_AnalysisConfig *config = PD_NewAnalysisConfig();
+  PD_DisableGpu(config);
+  PD_SetCpuMathLibraryNumThreads(config, 10);
+  PD_SwitchSpecifyInputNames(config, true);
+  PD_SwitchIrDebug(config, true);
+  PD_SetModel(config, prog_file.c_str(), params_file.c_str());
+  bool use_feed_fetch = PD_UseFeedFetchOpsEnabled(config);
+  EXPECT_FALSE(use_feed_fetch);
+  bool specify_input_names = PD_SpecifyInputName(config);
+  EXPECT_TRUE(specify_input_names);
+
+  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]();
+
+  int shape[4] = {batch_size, channels, height, width};
+  int shape_size = 4;
+  int in_size = 1;
+  int out_size;
+  PD_ZeroCopyData *inputs = new PD_ZeroCopyData;
+  PD_ZeroCopyData *outputs = new PD_ZeroCopyData;
+  inputs->data = static_cast<void *>(input);
+  inputs->dtype = PD_FLOAT32;
+  inputs->name = new char[5];
+  inputs->name[0] = 'd';
+  inputs->name[1] = 'a';
+  inputs->name[2] = 't';
+  inputs->name[3] = 'a';
+  inputs->name[4] = '\0';
+  inputs->shape = shape;
+  inputs->shape_size = shape_size;
+
+  PD_PredictorZeroCopyRun(config, inputs, in_size, &outputs, &out_size);
+
+  delete[] input;
+  delete[] inputs;
+  delete[] outputs;
+}
+
+TEST(PD_PredictorZeroCopyRun, zero_copy_run) { zero_copy_run(); }
+
+#ifdef PADDLE_WITH_DNNL
+TEST(PD_AnalysisConfig, profile_onednn) {
+  std::string model_dir = FLAGS_infer_model;
+  std::string prog_file = model_dir + "/model";
+  std::string params_file = model_dir + "/params";
+  PD_AnalysisConfig *config = PD_NewAnalysisConfig();
+  PD_DisableGpu(config);
+  PD_SetCpuMathLibraryNumThreads(config, 10);
+  PD_SwitchSpecifyInputNames(config, true);
+  PD_SwitchIrDebug(config, true);
+  PD_EnableONEDNN(config);
+  bool onednn_enable = PD_OnednnEnabled(config);
+  EXPECT_TRUE(onednn_enable);
+  PD_EnableOnednnBfloat16(config);
+  PD_SetOnednnCacheCapacity(config, 0);
+  PD_SetModel(config, prog_file.c_str(), params_file.c_str());
+  PD_DeleteAnalysisConfig(config);
+}
+#endif
+
+}  // namespace analysis
+}  // namespace inference
+}  // namespace paddle