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Merge pull request #24092 from Aser-Abdelfatah:GSoC_Support_GatherElements_ONNX

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GSoC Add ONNX Support for GatherElements #24092

Merge with: https://github.com/opencv/opencv_extra/pull/1082
Adds support to the ONNX operator GatherElements [operator docs](https://github.com/onnx/onnx/blob/main/docs/Operators.md#GatherElements)
Added tests to opencv_extra at pull request https://github.com/opencv/opencv_extra/pull/1082

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
Aser Atawya
2023-10-18 00:41:47 -07:00
committed by GitHub
parent 014e8485b5
commit 240b245105
8 changed files with 303 additions and 3 deletions
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modules/dnn/perf/perf_layer.cpp
+51
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@@ -633,6 +633,56 @@ PERF_TEST_P_(Layer_LayerNormExpanded, DISABLED_LayerNormExpanded)
test_layer({N, H ,W});
}
struct Layer_GatherElements : public TestBaseWithParam<tuple<Backend, Target> >
{
void test_layer(const std::vector<int>& data_shape, const std::vector<int>& indices_shape, int axis = 0)
{
int backendId = get<0>(GetParam());
int targetId = get<1>(GetParam());
Mat data(data_shape, CV_32FC1);
Mat indices(indices_shape, CV_32FC1);
randu(data, 0.f, 1.f);
randu(indices, 0, data_shape[axis]);
Net net;
LayerParams lp;
lp.type = "GatherElements";
lp.name = "testLayer";
lp.set("axis", axis);
int id = net.addLayerToPrev(lp.name, lp.type, lp);
net.connect(0, 0, id, 0);
net.connect(0, 1, id, 1);
// warmup
{
std::vector<String> inpNames(3);
inpNames[0] = "data";
inpNames[1] = "indices";
net.setInputsNames(inpNames);
net.setInput(data, inpNames[0]);
net.setInput(indices, inpNames[1]);
net.setPreferableBackend(backendId);
net.setPreferableTarget(targetId);
Mat out = net.forward();
}
TEST_CYCLE()
{
Mat res = net.forward();
}
SANITY_CHECK_NOTHING();
}
};
PERF_TEST_P_(Layer_GatherElements, GatherElements)
{
test_layer({2700, 1, 2914}, {2700, 1, 81}, 2);
}
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
@@ -642,6 +692,7 @@ INSTANTIATE_TEST_CASE_P(/**/, Layer_Scatter, testing::Values(std::make_tuple(DNN
INSTANTIATE_TEST_CASE_P(/**/, Layer_ScatterND, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));
INSTANTIATE_TEST_CASE_P(/**/, Layer_LayerNorm, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));
INSTANTIATE_TEST_CASE_P(/**/, Layer_LayerNormExpanded, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));
INSTANTIATE_TEST_CASE_P(/**/, Layer_GatherElements, testing::Values(std::make_tuple(DNN_BACKEND_OPENCV, DNN_TARGET_CPU)));
typedef TestBaseWithParam<tuple<Vec4i, int, bool, tuple<Backend, Target> > > Layer_FullyConnected;