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Merge pull request #25518 from alexlyulkov:al/fixed-gemm-openvino

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Fixed OpenVINO gemm layer #25518

Fixed OpenVINO gemm layer
The problem was that our layer didn't properly handle all the possible gemm options in OpenVINO mode
Fixes #25472

### 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:
alexlyulkov 2024-05-14 17:41:19 +03:00 committed by GitHub
parent f4e5438401
commit 03507e06b4
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GPG Key ID: B5690EEEBB952194
2 changed files with 40 additions and 36 deletions
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74
modules/dnn/src/layers/gemm_layer.cpp
View File

@ -289,48 +289,54 @@ public:
virtual Ptr<BackendNode> initNgraph(const std::vector<Ptr<BackendWrapper> >& inputs,
const std::vector<Ptr<BackendNode> >& nodes) CV_OVERRIDE
{
auto ieInpNode = nodes[0].dynamicCast<InfEngineNgraphNode>()->node;
std::shared_ptr<ov::Node> matmul;
ov::Output<ov::Node> nodeA = nodes[0].dynamicCast<InfEngineNgraphNode>()->node;
ov::Output<ov::Node> nodeB;
if (const_B)
nodeB = std::make_shared<ov::op::v0::Constant>(ov::element::f32, getShape(blobs[0]), blobs[0].data);
else
nodeB = nodes[1].dynamicCast<InfEngineNgraphNode>()->node;
if (nodes.size() == 2)
int flatten_axis = nodeA.get_shape().size() - nodeB.get_shape().size();
if (flatten_axis > 0) {
std::vector<int> shape(1 + flatten_axis, 0);
shape[shape.size() - 1] = -1;
nodeA = std::make_shared<ov::op::v1::Reshape>(
nodeA,
std::make_shared<ov::op::v0::Constant>(ov::element::i32, ov::Shape{shape.size()}, shape.data()),
true);
}
std::shared_ptr<ov::Node> nodeAB = std::make_shared<ov::op::v0::MatMul>(nodeA, nodeB, trans_a, trans_b);
if (alpha != 1.0f)
{
auto& inp2 = nodes[1].dynamicCast<InfEngineNgraphNode>()->node;
matmul = std::make_shared<ov::op::v0::MatMul>(ieInpNode, inp2, trans_a, trans_b);
nodeAB = std::make_shared<ov::op::v1::Multiply>(
nodeAB,
std::make_shared<ov::op::v0::Constant>(ov::element::f32, ov::Shape{1}, &alpha));
}
if (!have_bias)
return Ptr<BackendNode>(new InfEngineNgraphNode(nodeAB));
ov::Output<ov::Node> nodeC;
if (const_C)
{
auto shape_C = blobs.back().total() == blobs.back().size[0] ? ov::Shape{blobs.back().total()} : getShape(blobs.back());
nodeC = std::make_shared<ov::op::v0::Constant>(ov::element::f32, shape_C, blobs.back().data);
}
else
{
std::shared_ptr<ov::Node> ieWeights = std::make_shared<ov::op::v0::Constant>(ov::element::f32, getShape(blobs[0]), blobs[0].data);
int flatten_axis = ieInpNode.get_shape().size() - ieWeights->get_shape().size();
if (flatten_axis > 0) {
std::vector<int> shape(1 + flatten_axis, 0);
shape[shape.size() - 1] = -1;
ieInpNode = std::make_shared<ov::op::v1::Reshape>(
ieInpNode,
std::make_shared<ov::op::v0::Constant>(ov::element::i32, ov::Shape{shape.size()}, shape.data()),
true
);
}
matmul = std::make_shared<ov::op::v0::MatMul>(ieInpNode, ieWeights, trans_a, trans_b);
}
if (alpha != 1.0f) {
matmul = std::make_shared<ov::op::v1::Multiply>(matmul,
std::make_shared<ov::op::v0::Constant>(ov::element::f32, ov::Shape{1}, &alpha)
);
nodeC = nodes.back().dynamicCast<InfEngineNgraphNode>()->node;
}
if (have_bias && const_C) {
Mat bias = blobs.back();
auto shape = bias.total() == bias.size[0] ? ov::Shape{bias.total()} : getShape(bias);
std::shared_ptr<ov::Node> bias_node = std::make_shared<ov::op::v0::Constant>(ov::element::f32, shape, bias.data);
if (beta != 1.0f) {
bias_node = std::make_shared<ov::op::v1::Multiply>(bias_node,
std::make_shared<ov::op::v0::Constant>(ov::element::f32, ov::Shape{1}, &beta)
);
}
matmul = std::make_shared<ov::op::v1::Add>(matmul, bias_node, ov::op::AutoBroadcastType::NUMPY);
if (beta != 1.0f)
{
nodeC = std::make_shared<ov::op::v1::Multiply>(
nodeC,
std::make_shared<ov::op::v0::Constant>(ov::element::f32, ov::Shape{1}, &beta));
}
return Ptr<BackendNode>(new InfEngineNgraphNode(matmul));
auto nodeGemm = std::make_shared<ov::op::v1::Add>(nodeAB, nodeC, ov::op::AutoBroadcastType::NUMPY);
return Ptr<BackendNode>(new InfEngineNgraphNode(nodeGemm));
}
#endif // HAVE_DNN_NGRAPH

2
modules/dnn/test/test_onnx_conformance_layer_parser_denylist.inl.hpp
View File

@ -121,8 +121,6 @@
"test_gemm_all_attributes",
"test_gemm_alpha",
"test_gemm_beta",
"test_gemm_default_matrix_bias",
"test_gemm_default_no_bias",
"test_gemm_default_scalar_bias",
"test_gemm_default_single_elem_vector_bias",
"test_gemm_default_vector_bias",