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Benchmarking SNPE Neural Network Performance in OpenPilot

This benchmark test suite evaluates the performance of SNPE (Snapdragon Neural Processing Engine) model execution in the OpenPilot system. It measures model inference times across different runtime processors (DSP, GPU, CPU) and handles tensor operations for neural network processing.

Test Coverage Overview

The test suite provides comprehensive coverage of SNPE model execution and performance benchmarking:

Runtime processor availability checking (DSP, GPU, CPU)
Model loading and initialization verification
Tensor input/output handling
Performance timing measurements
Batch processing of test frames

Implementation Analysis

The implementation follows a systematic approach to benchmarking neural network performance:

The test utilizes SNPE’s C++ API for model execution, with separate test modes for continuous benchmarking and batch processing. It implements precise timing measurements using clock_gettime() and handles tensor operations through SNPE’s tensor factory interface.

Technical Details

Key technical components include:

SNPE C++ SDK integration
Runtime processor detection and selection
Binary file I/O for test frame loading
Tensor creation and management
Nanosecond-precision timing measurements
Error handling and reporting system

Best Practices Demonstrated

The benchmark demonstrates several testing best practices:

Error handling is comprehensive with dedicated error reporting functions. Memory management uses RAII principles through std::unique_ptr. The code maintains clear separation between setup, execution, and measurement phases while providing detailed logging for debugging and analysis.

commaai/openpilot

selfdrive/modeld/tests/snpe_benchmark/benchmark.cc

            
#include <SNPE/SNPE.hpp>
#include <SNPE/SNPEBuilder.hpp>
#include <SNPE/SNPEFactory.hpp>
#include <DlContainer/IDlContainer.hpp>
#include <DlSystem/DlError.hpp>
#include <DlSystem/ITensor.hpp>
#include <DlSystem/ITensorFactory.hpp>
#include <iostream>
#include <fstream>
#include <sstream>

using namespace std;

int64_t timespecDiff(struct timespec *timeA_p, struct timespec *timeB_p) {
  return ((timeA_p->tv_sec * 1000000000) + timeA_p->tv_nsec) - ((timeB_p->tv_sec * 1000000000) + timeB_p->tv_nsec);
}

void PrintErrorStringAndExit() {
  cout << "ERROR!" << endl;
  const char* const errStr = zdl::DlSystem::getLastErrorString();
  std::cerr << errStr << std::endl;
  std::exit(EXIT_FAILURE);
}


zdl::DlSystem::Runtime_t checkRuntime() {
  static zdl::DlSystem::Version_t Version = zdl::SNPE::SNPEFactory::getLibraryVersion();
  static zdl::DlSystem::Runtime_t Runtime;
  std::cout << "SNPE Version: " << Version.asString().c_str() << std::endl; //Print Version number
  if (zdl::SNPE::SNPEFactory::isRuntimeAvailable(zdl::DlSystem::Runtime_t::DSP)) {
    std::cout << "Using DSP runtime" << std::endl;
    Runtime = zdl::DlSystem::Runtime_t::DSP;
  } else if (zdl::SNPE::SNPEFactory::isRuntimeAvailable(zdl::DlSystem::Runtime_t::GPU)) {
    std::cout << "Using GPU runtime" << std::endl;
    Runtime = zdl::DlSystem::Runtime_t::GPU;
  } else {
    std::cout << "Using cpu runtime" << std::endl;
    Runtime = zdl::DlSystem::Runtime_t::CPU;
  }
  return Runtime;
}

void test(char *filename) {
  static zdl::DlSystem::Runtime_t runtime = checkRuntime();
  std::unique_ptr<zdl::DlContainer::IDlContainer> container;
  container = zdl::DlContainer::IDlContainer::open(filename);

  if (!container) { PrintErrorStringAndExit(); }
  cout << "start build" << endl;
  std::unique_ptr<zdl::SNPE::SNPE> snpe;
  {
    snpe = NULL;
    zdl::SNPE::SNPEBuilder snpeBuilder(container.get());
    snpe = snpeBuilder.setOutputLayers({})
      .setRuntimeProcessor(runtime)
      .setUseUserSuppliedBuffers(false)
      //.setDebugMode(true)
      .build();
    if (!snpe) {
      cout << "ERROR!" << endl;
      const char* const errStr = zdl::DlSystem::getLastErrorString();
      std::cerr << errStr << std::endl;
    }
    cout << "ran snpeBuilder" << endl;
  }

  const auto &strList_opt = snpe->getInputTensorNames();
  if (!strList_opt) throw std::runtime_error("Error obtaining input tensor names");

  cout << "get input tensor names done" << endl;
  const auto &strList = *strList_opt;
  static zdl::DlSystem::TensorMap inputTensorMap;
  static zdl::DlSystem::TensorMap outputTensorMap;
  vector<std::unique_ptr<zdl::DlSystem::ITensor> > inputs;
  for (int i = 0; i < strList.size(); i++) {
    cout << "input name: " << strList.at(i) << endl;

    const auto &inputDims_opt = snpe->getInputDimensions(strList.at(i));
    const auto &inputShape = *inputDims_opt;
    inputs.push_back(zdl::SNPE::SNPEFactory::getTensorFactory().createTensor(inputShape));
    inputTensorMap.add(strList.at(i), inputs[i].get());
  }

  struct timespec start, end;
  cout << "**** starting benchmark ****" << endl;
  for (int i = 0; i < 50; i++) {
    clock_gettime(CLOCK_MONOTONIC, &start);
    int err = snpe->execute(inputTensorMap, outputTensorMap);
    assert(err == true);
    clock_gettime(CLOCK_MONOTONIC, &end);
    uint64_t timeElapsed = timespecDiff(&end, &start);
    printf("time: %f ms
", timeElapsed*1.0/1e6);
  }
}

void get_testframe(int index, std::unique_ptr<zdl::DlSystem::ITensor> &input) {
  FILE * pFile;
  string filepath="/data/ipt/quantize_samples/sample_input_"+std::to_string(index);
  pFile = fopen(filepath.c_str(), "rb");
  int length = 1*6*160*320*4;
  float * frame_buffer = new float[length/4]; // 32/8
  fread(frame_buffer, length, 1, pFile);
  // std::cout << *(frame_buffer+length/4-1) << std::endl;
  std::copy(frame_buffer, frame_buffer+(length/4), input->begin());
  fclose(pFile);
}

void SaveITensor(const std::string& path, const zdl::DlSystem::ITensor* tensor)
{
   std::ofstream os(path, std::ofstream::binary);
   if (!os)
   {
      std::cerr << "Failed to open output file for writing: " << path << "
";
      std::exit(EXIT_FAILURE);
   }
   for ( auto it = tensor->cbegin(); it != tensor->cend(); ++it )
   {
      float f = *it;
      if (!os.write(reinterpret_cast<char*>(&f), sizeof(float)))
      {
         std::cerr << "Failed to write data to: " << path << "
";
         std::exit(EXIT_FAILURE);
      }
   }
}

void testrun(char* modelfile) {
  static zdl::DlSystem::Runtime_t runtime = checkRuntime();
  std::unique_ptr<zdl::DlContainer::IDlContainer> container;
  container = zdl::DlContainer::IDlContainer::open(modelfile);

  if (!container) { PrintErrorStringAndExit(); }
  cout << "start build" << endl;
  std::unique_ptr<zdl::SNPE::SNPE> snpe;
  {
    snpe = NULL;
    zdl::SNPE::SNPEBuilder snpeBuilder(container.get());
    snpe = snpeBuilder.setOutputLayers({})
      .setRuntimeProcessor(runtime)
      .setUseUserSuppliedBuffers(false)
      //.setDebugMode(true)
      .build();
    if (!snpe) {
      cout << "ERROR!" << endl;
      const char* const errStr = zdl::DlSystem::getLastErrorString();
      std::cerr << errStr << std::endl;
    }
    cout << "ran snpeBuilder" << endl;
  }

  const auto &strList_opt = snpe->getInputTensorNames();
  if (!strList_opt) throw std::runtime_error("Error obtaining input tensor names");
  cout << "get input tensor names done" << endl;

  const auto &strList = *strList_opt;
  static zdl::DlSystem::TensorMap inputTensorMap;
  static zdl::DlSystem::TensorMap outputTensorMap;

  assert(strList.size() == 1);
  const auto &inputDims_opt = snpe->getInputDimensions(strList.at(0));
  const auto &inputShape = *inputDims_opt;
  std::cout << "winkwink" << std::endl;

  for (int i=0; i<10000; i++) {
    std::unique_ptr<zdl::DlSystem::ITensor> input;
    input = zdl::SNPE::SNPEFactory::getTensorFactory().createTensor(inputShape);
    get_testframe(i, input);
    snpe->execute(input.get(), outputTensorMap);
    zdl::DlSystem::StringList tensorNames = outputTensorMap.getTensorNames();
    std::for_each(tensorNames.begin(), tensorNames.end(), [&](const char* name) {
      std::ostringstream path;
      path << "/data/opt/Result_" << std::to_string(i) << ".raw";
      auto tensorPtr = outputTensorMap.getTensor(name);
      SaveITensor(path.str(), tensorPtr);
    });
  }
}

int main(int argc, char* argv[]) {
  if (argc < 2) {
    printf("usage: %s <filename>
", argv[0]);
    return -1;
  }

  if (argc == 2) {
    while (true) test(argv[1]);
  } else if (argc == 3) {
    testrun(argv[1]);
  }
  return 0;
}