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Fix for OpenVINO 2024.0

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Remove support OpenVINO lower than 2022.1 release
Remove legacy InferenceEngine wrappers
This commit is contained in:
Oleg Pipikin
2024-03-11 20:23:48 +04:00
parent 625eebad54
commit 6da2ddcf0e
48 changed files with 646 additions and 1677 deletions
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modules/dnn/src/layers/layer_norm.cpp
+9 -16
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@@ -263,42 +263,35 @@ public:
const std::vector<Ptr<BackendNode> >& nodes) CV_OVERRIDE {
auto ieInpNode = nodes[0].dynamicCast<InfEngineNgraphNode>()->node;
const auto &input_shape = ieInpNode.get_shape();
std::shared_ptr<ngraph::Node> mvn, result;
std::shared_ptr<ov::Node> mvn, result;
// mvn
#if INF_ENGINE_VER_MAJOR_LE(INF_ENGINE_RELEASE_2021_2)
// https://docs.openvino.ai/2021.4/api/ngraph_python_api/_autosummary/ngraph.opset3.mvn.html?highlight=mvn#ngraph.opset3.mvn
bool across_channels = false;
bool normalize_variance = true;
mvn = std::make_shared<ngraph::op::MVN>(ieInpNode, across_channels, normalize_variance, epsilon);
#else
// https://docs.openvino.ai/2023.1/openvino_docs_ops_normalization_MVN_6.html
std::vector<int64_t> axes_v(input_shape.size() - axis);
std::iota(axes_v.begin(), axes_v.end(), axis);
auto axes = std::make_shared<ngraph::op::Constant>(ngraph::element::i64, ngraph::Shape{axes_v.size()}, axes_v.data());
auto axes = std::make_shared<ov::op::v0::Constant>(ov::element::i64, ov::Shape{axes_v.size()}, axes_v.data());
bool normalize_variance = true;
mvn = std::make_shared<ngraph::op::v6::MVN>(ieInpNode, axes, normalize_variance, epsilon, ngraph::op::MVNEpsMode::INSIDE_SQRT);
#endif
mvn = std::make_shared<ov::op::v6::MVN>(ieInpNode, axes, normalize_variance, epsilon, ov::op::MVNEpsMode::INSIDE_SQRT);
// layer norm = scale * mvn + bias
auto scale = nodes[1].dynamicCast<InfEngineNgraphNode>()->node;
ngraph::Output<ngraph::Node> bias;
ov::Output<ov::Node> bias;
if (nodes.size() == 3) {
bias = nodes[2].dynamicCast<InfEngineNgraphNode>()->node;
}
if (axis == -1 || axis == input_shape.size() - 1) { // special case for 1D tensor (2D mat)
std::vector<int64_t> shared_shape_v(input_shape.size(), 1);
shared_shape_v.back() = -1;
auto shared_shape = std::make_shared<ngraph::op::Constant>(ngraph::element::i64, ngraph::Shape{shared_shape_v.size()}, shared_shape_v.data());
scale = std::make_shared<ngraph::op::v1::Reshape>(scale, shared_shape, true);
auto shared_shape = std::make_shared<ov::op::v0::Constant>(ov::element::i64, ov::Shape{shared_shape_v.size()}, shared_shape_v.data());
scale = std::make_shared<ov::op::v1::Reshape>(scale, shared_shape, true);
if (nodes.size() == 3) {
bias = std::make_shared<ngraph::op::v1::Reshape>(bias, shared_shape, true);
bias = std::make_shared<ov::op::v1::Reshape>(bias, shared_shape, true);
}
}
result = std::make_shared<ngraph::op::v1::Multiply>(mvn, scale);
result = std::make_shared<ov::op::v1::Multiply>(mvn, scale);
if (nodes.size() == 3) {
result = std::make_shared<ngraph::op::v1::Add>(result, bias);
result = std::make_shared<ov::op::v1::Add>(result, bias);
}
return Ptr<BackendNode>(new InfEngineNgraphNode(result));