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cuda support and Layer Split + per-op executors

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This commit is contained in:
Abhishek Gola
2026-06-08 18:06:28 +05:30
parent a5e4c04903
commit 72ffdfc170
32 changed files with 995 additions and 328 deletions
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52
modules/dnn/test/test_model.cpp
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@@ -690,17 +690,31 @@ static void topK(const Mat& probs, std::vector<std::pair<int, float> >& result,
}
}
typedef testing::TestWithParam<Target> Reproducibility_ResNet50_ONNX;
// Returns the CPU (OpenCV backend) and CUDA backend/target pairs for benchmarking.
static std::vector<tuple<Backend, Target> > resnet50BackendsAndTargets()
{
std::vector<tuple<Backend, Target> > targets;
targets.push_back(make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU));
#ifdef HAVE_CUDA
for (auto target : getAvailableTargets(DNN_BACKEND_CUDA))
targets.push_back(make_tuple(DNN_BACKEND_CUDA, target));
#endif
return targets;
}
typedef testing::TestWithParam<tuple<Backend, Target> > Reproducibility_ResNet50_ONNX;
TEST_P(Reproducibility_ResNet50_ONNX, Accuracy)
{
Target targetId = GetParam();
Backend backendId = get<0>(GetParam());
Target targetId = get<1>(GetParam());
applyTestTag(targetId == DNN_TARGET_CPU ? CV_TEST_TAG_MEMORY_512MB : CV_TEST_TAG_MEMORY_1GB);
ASSERT_TRUE(ocl::useOpenCL() || targetId == DNN_TARGET_CPU || targetId == DNN_TARGET_CPU_FP16);
ASSERT_TRUE(ocl::useOpenCL() || targetId == DNN_TARGET_CPU || targetId == DNN_TARGET_CPU_FP16
|| backendId == DNN_BACKEND_CUDA);
std::string modelname = _tf("onnx/models/resnet50v1.onnx", false);
Net net = readNetFromONNX(modelname);
net.setPreferableBackend(DNN_BACKEND_OPENCV);
net.setPreferableBackend(backendId);
net.setPreferableTarget(targetId);
if (targetId == DNN_TARGET_CPU_FP16)
@@ -738,9 +752,37 @@ TEST_P(Reproducibility_ResNet50_ONNX, Accuracy)
for (int i = 0; i < K; i++) {
EXPECT_NEAR(ref[i].second, res[i].second, eps);
}
// Benchmark: warmup runs followed by timed runs, reporting avg/min/max forward time.
const int numWarmup = 5;
const int numRuns = 30;
for (int i = 0; i < numWarmup; i++)
{
net.setInput(input);
net.forward();
}
double timeMin = DBL_MAX, timeMax = 0.0, timeSum = 0.0;
for (int i = 0; i < numRuns; i++)
{
net.setInput(input);
TickMeter tm;
tm.start();
net.forward();
tm.stop();
double t = tm.getTimeMilli();
timeSum += t;
timeMin = std::min(timeMin, t);
timeMax = std::max(timeMax, t);
}
std::cout << "[ BENCHMARK ] ResNet50 ONNX (backend=" << backendId << ", target=" << targetId << ") over "
<< numRuns << " runs: avg=" << (timeSum / numRuns) << " ms"
<< ", min=" << timeMin << " ms"
<< ", max=" << timeMax << " ms" << std::endl;
}
INSTANTIATE_TEST_CASE_P(/**/, Reproducibility_ResNet50_ONNX,
testing::ValuesIn(getAvailableTargets(DNN_BACKEND_OPENCV)));
testing::ValuesIn(resnet50BackendsAndTargets()));
typedef testing::TestWithParam<Target> Reproducibility_ResNet50_QDQ_ONNX;
TEST_P(Reproducibility_ResNet50_QDQ_ONNX, Accuracy)