cnstream/modules/unitest/inference2/test_infer_params.cpp

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 *  Licensed under the Apache License, Version 2.0 (the "License");
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#include <gtest/gtest.h>

#include <memory>
#include <string>
#include <list>

#include "cnstream_logging.hpp"

#include "inferencer2.hpp"
#include "video_postproc.hpp"
#include "video_preproc.hpp"
#include "test_base.hpp"

namespace cnstream {

TEST(Inferencer2, CheckParamSet) {
  std::string ssd_model_path = GetExePath() + "../../data/models/MLU270/Primary_Detector/ssd/resnet34_ssd.cambricon";
  std::string model_path = GetExePath() + "../../data/models/resnet50_nhwc.model";
  std::string infer_name = "detector";
  std::unique_ptr<Inferencer2> infer(new Inferencer2(infer_name));

  ModuleParamSet param;
  param.clear();
  param["postproc_name"] = "empty_postproc";
  if (infer_server::Predictor::Backend() == "magicmind") {
    param["model_path"] = model_path;
    EXPECT_TRUE(infer->CheckParamSet(param));
  } else {
    param["model_path"] = ssd_model_path;
    EXPECT_TRUE(infer->CheckParamSet(param));
    param["func_name"] = "subnet0";
    EXPECT_TRUE(infer->CheckParamSet(param));
  }

  param["preproc_name"] = "empty_preproc";
  EXPECT_TRUE(infer->CheckParamSet(param));
  param["device_id"] = "no_number";  // device id must be a number
  EXPECT_FALSE(infer->CheckParamSet(param));
  param["device_id"] = "0";
  EXPECT_TRUE(infer->CheckParamSet(param));

  param["engine_num"] = "no_number";  // engine num must be a number
  EXPECT_FALSE(infer->CheckParamSet(param));
  param["engine_num"] = "1";
  EXPECT_TRUE(infer->CheckParamSet(param));

  param["batching_timeout"] = "no_number";  // batching timeout must be a number
  EXPECT_FALSE(infer->CheckParamSet(param));
  param["batching_timeout"] = "100";
  EXPECT_TRUE(infer->CheckParamSet(param));

  // batch strategy must be one of them
  std::list<std::string> batch_strategy = {"static", "STATIC", "dynamic", "DYNAMIC"};
  param["batch_strategy"] = "error_type";
  EXPECT_FALSE(infer->CheckParamSet(param));
  for (auto type : batch_strategy) {
    param["batch_strategy"] = type;
    EXPECT_TRUE(infer->CheckParamSet(param));
  }

  // data order must be NCHW or NHWC
  std::list<std::string> data_order = {"NCHW", "NHWC"};
  param["data_order"] = "error_type";
  EXPECT_FALSE(infer->CheckParamSet(param));
  for (auto type : data_order) {
    param["data_order"] = type;
    EXPECT_TRUE(infer->CheckParamSet(param));
  }

  param["threshold"] = "0.5";
  EXPECT_TRUE(infer->CheckParamSet(param));

  // show stats must be one of bool_type
  std::list<std::string> bool_type = {"1", "true", "True", "TRUE", "0", "false", "False", "FALSE"};
  param["show_stats"] = "error_type";
  EXPECT_FALSE(infer->CheckParamSet(param));
  for (auto type : bool_type) {
    param["show_stats"] = type;
    EXPECT_TRUE(infer->CheckParamSet(param));
  }

  // object_infer must be one of bool_type
  param["object_infer"] = "error_type";
  EXPECT_FALSE(infer->CheckParamSet(param));
  for (auto type : bool_type) {
    param["object_infer"] = type;
    EXPECT_TRUE(infer->CheckParamSet(param));
  }

  // keep_aspect_ratio must be one of bool_type
  param["keep_aspect_ratio"] = "error_type";
  EXPECT_FALSE(infer->CheckParamSet(param));
  for (auto type : bool_type) {
    param["keep_aspect_ratio"] = type;
    EXPECT_TRUE(infer->CheckParamSet(param));
  }

  // normalize must be one of bool_type
  param["normalize"] = "error_type";
  EXPECT_FALSE(infer->CheckParamSet(param));
  for (auto type : bool_type) {
    param["normalize"] = type;
    EXPECT_TRUE(infer->CheckParamSet(param));
  }

  // model_input_pixel_format must be one of format
  std::list<std::string> format = {"RGBA32", "BGRA32", "ARGB32", "ABGR32", "RGB24", "BGR24"};
  param["model_input_pixel_format"] = "error_type";
  EXPECT_FALSE(infer->CheckParamSet(param));
  for (auto type : format) {
    param["model_input_pixel_format"] = type;
    EXPECT_TRUE(infer->CheckParamSet(param));
  }

  // TODO(dmh): test mean and std
}

}  // namespace cnstream