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Let part of the operators in nary_eltwise support cuda

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zoom 2022-10-21 13:11:22 +08:00
parent f378f02954
commit 11d492b0b9
3 changed files with 58 additions and 2 deletions
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12
modules/dnn/perf/perf_layer.cpp
View File

@ -55,6 +55,8 @@ struct Layer_Slice : public TestBaseWithParam<tuple<Backend, Target> >
}
};
static std::set<std::string> nary_eltwise_cuda_deny_ops = {"add", "equal", "greater", "less", "mean", "mul", "pow", "sub"};
struct Layer_NaryEltwise : public TestBaseWithParam<tuple<Backend, Target> >
{
void test_layer(const std::vector<int>& a_shape, const std::vector<int>& b_shape, const String op, bool isRef = false)
@ -62,6 +64,13 @@ struct Layer_NaryEltwise : public TestBaseWithParam<tuple<Backend, Target> >
int backendId = get<0>(GetParam());
int targetId = get<1>(GetParam());
if (!isRef && backendId == DNN_BACKEND_CUDA)
{
if (a_shape != b_shape)
throw SkipTestException("The test is skipped because inputs with different shapes are not supported.");
if (nary_eltwise_cuda_deny_ops.find(op) != nary_eltwise_cuda_deny_ops.end())
throw SkipTestException("The operator '" + op + "' is skipped because is not support with cuda currently.");
}
Mat a(a_shape, CV_32FC1);
Mat b(b_shape, CV_32FC1);
@ -410,6 +419,9 @@ PERF_TEST_P_(Layer_ScatterND, DISABLED_ScatterND_add)
INSTANTIATE_TEST_CASE_P(/**/, Layer_Slice, dnnBackendsAndTargets(false, false));
INSTANTIATE_TEST_CASE_P(/**/, Layer_NaryEltwise, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));
#ifdef HAVE_CUDA
INSTANTIATE_TEST_CASE_P(CUDA, Layer_NaryEltwise, testing::Values(std::make_tuple(DNN_BACKEND_CUDA, DNN_TARGET_CUDA)));
#endif
INSTANTIATE_TEST_CASE_P(/**/, Layer_Scatter, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));
INSTANTIATE_TEST_CASE_P(/**/, Layer_ScatterND, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));

41
modules/dnn/src/layers/nary_eltwise_layers.cpp
View File

@ -4,12 +4,18 @@
#include "../precomp.hpp"
#include "layers_common.hpp"
#include "../op_cuda.hpp"
#include <opencv2/dnn/shape_utils.hpp>
#include <algorithm>
#include <iterator>
#include <numeric>
#ifdef HAVE_CUDA
#include "../cuda4dnn/primitives/eltwise.hpp"
using namespace cv::dnn::cuda4dnn;
#endif
namespace cv
{
namespace dnn
@ -91,6 +97,9 @@ public:
virtual bool supportBackend(int backendId) CV_OVERRIDE
{
if (op == OPERATION::MAX || op == OPERATION::MIN || op == OPERATION::SUM ||
op == OPERATION::PROD || op == OPERATION::DIV)
return backendId == DNN_BACKEND_OPENCV || backendId == DNN_BACKEND_CUDA;
return backendId == DNN_BACKEND_OPENCV;
}
@ -641,6 +650,38 @@ public:
};
}
#ifdef HAVE_CUDA
Ptr<BackendNode> initCUDA(
void *context_,
const std::vector<Ptr<BackendWrapper>>& inputs,
const std::vector<Ptr<BackendWrapper>>& outputs
) override
{
auto context = reinterpret_cast<csl::CSLContext*>(context_);
auto input_wrapper = inputs[0].dynamicCast<CUDABackendWrapper>();
for (int i = 1; i < inputs.size(); i++)
{
auto from_wrapper = inputs[i].dynamicCast<CUDABackendWrapper>();
if (input_wrapper->getShape() != from_wrapper->getShape())
return Ptr<BackendNode>();
}
auto op_ = [this] {
switch (op) {
case OPERATION::MAX: return cuda4dnn::EltwiseOpType::MAX;
case OPERATION::MIN: return cuda4dnn::EltwiseOpType::MIN;
case OPERATION::SUM: return cuda4dnn::EltwiseOpType::SUM;
case OPERATION::PROD: return cuda4dnn::EltwiseOpType::PRODUCT;
case OPERATION::DIV: return cuda4dnn::EltwiseOpType::DIV;
default: CV_Error(Error::StsNotImplemented, "Other operators except MAX, MIN, SUM, PRODUCT and DIV are not supported with cuda.");
}
}();
return make_cuda_node<cuda4dnn::EltwiseOp>(preferableTarget, std::move(context->stream), op_, std::vector<float>());
}
#endif
virtual bool tryQuantize(const std::vector<std::vector<float> > &scales,
const std::vector<std::vector<int> > &zeropoints, LayerParams& params) CV_OVERRIDE
{

7
modules/dnn/src/op_cuda.cpp
View File

@ -86,8 +86,11 @@ void Net::Impl::initCUDABackend(const std::vector<LayerPin>& blobsToKeep_)
auto node = layerInstance->initCUDA(&context, ld.inputBlobsWrappers, ld.outputBlobsWrappers);
ld.backendNodes[DNN_BACKEND_CUDA] = node;
auto cudaNode = node.dynamicCast<CUDABackendNode>();
cudaInfo->workspace.require(cudaNode->get_workspace_memory_in_bytes());
if(!node.empty())
{
auto cudaNode = node.dynamicCast<CUDABackendNode>();
cudaInfo->workspace.require(cudaNode->get_workspace_memory_in_bytes());
}
}
if (blobsToKeep_.size() > 1)