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| name: Send workflows to OpenTelemetry (BETA) | ||
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| on: | ||
| workflow_run: | ||
| workflows: | ||
| - Android ARM64 with vcpkg | ||
| - Documentation | ||
| - Cleanup PIP caches | ||
| - Code snippets | ||
| - Code Style | ||
| - Code coverage | ||
| - Coverity (Ubuntu 20.04, Python 3.11) | ||
| - Fedora (RHEL), Python 3.9 | ||
| - Linux (Ubuntu 20.04, Python 3.11) | ||
| - Linux ARM64 (Ubuntu 20.04, Python 3.11) | ||
| - Linux Static CC (Ubuntu 22.04, Python 3.11, Clang) | ||
| - Linux RISC-V with Conan (Ubuntu 22.04, Python 3.10) | ||
| - macOS (Python 3.11) | ||
| - macOS ARM64 (Python 3.11) | ||
| - MO | ||
| - Python API Checks | ||
| - Webassembly | ||
| - Windows (VS 2019, Python 3.11) | ||
| - Windows Conditional Compilation (VS 2022, Python 3.11) | ||
| types: | ||
| - completed | ||
|
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| permissions: read-all | ||
|
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| jobs: | ||
| otel-export-trace: | ||
| name: OpenTelemetry Export Trace | ||
| runs-on: ubuntu-latest | ||
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| steps: | ||
| - name: Export Workflow Trace | ||
| uses: inception-health/otel-export-trace-action@7eabc7de1f4753f0b45051b44bb0ba46d05a21ef | ||
| with: | ||
| otlpEndpoint: grpc://api.honeycomb.io:443/ | ||
| otlpHeaders: ${{ secrets.OTLP_HEADERS }} | ||
| githubToken: ${{ secrets.GITHUB_TOKEN }} | ||
| runId: ${{ github.event.workflow_run.id }} |
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| @@ -1,5 +1,5 @@ | ||
| { | ||
| "p": "OpenVINO 2022.1 has introduced OpenVINO API 2.0. For more information on transition steps from the previous API, see the <a href=\"https://docs.openvino.ai/latest/openvino_2_0_transition_guide.html\">transition guide</a>", | ||
| "p": "", | ||
| "version": "1", | ||
| "style": "info" | ||
| "style": "warning" | ||
| } |
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102 changes: 102 additions & 0 deletions
102
src/frontends/onnx/frontend/src/op/layer_normalization.cpp
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| // Copyright (C) 2018-2024 Intel Corporation | ||
| // SPDX-License-Identifier: Apache-2.0 | ||
| // | ||
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| #include "op/layer_normalization.hpp" | ||
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| #include "exceptions.hpp" | ||
| #include "openvino/op/add.hpp" | ||
| #include "openvino/op/broadcast.hpp" | ||
| #include "openvino/op/concat.hpp" | ||
| #include "openvino/op/constant.hpp" | ||
| #include "openvino/op/convert.hpp" | ||
| #include "openvino/op/convert_like.hpp" | ||
| #include "openvino/op/divide.hpp" | ||
| #include "openvino/op/multiply.hpp" | ||
| #include "openvino/op/negative.hpp" | ||
| #include "openvino/op/reduce_mean.hpp" | ||
| #include "openvino/op/reshape.hpp" | ||
| #include "openvino/op/shape_of.hpp" | ||
| #include "openvino/op/slice.hpp" | ||
| #include "openvino/op/sqrt.hpp" | ||
| #include "openvino/op/subtract.hpp" | ||
| #include "ov_models/ov_builders/reshape.hpp" | ||
| #include "utils/common.hpp" | ||
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| using namespace ov::op; | ||
| using namespace ov::op::v0; | ||
| using namespace ov::op::v1; | ||
| using namespace ov::op::v8; | ||
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| OPENVINO_SUPPRESS_DEPRECATED_START | ||
| namespace ngraph { | ||
| namespace onnx_import { | ||
| namespace op { | ||
| namespace set_1 { | ||
|
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| ov::OutputVector layer_normalization(const Node& node) { | ||
| const auto inputs = node.get_ng_inputs(); | ||
| const auto num_inputs = inputs.size(); | ||
| CHECK_VALID_NODE(node, | ||
| num_inputs == 2 || num_inputs == 3, | ||
| "LayerNormalization expects 2 or 3 input tensors. Got: ", | ||
| num_inputs); | ||
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| const auto& X = inputs.at(0); | ||
| const auto& Scale = inputs.at(1); | ||
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| auto axis = node.get_attribute_value<std::int64_t>("axis", -1); | ||
| double epsilon = node.get_attribute_value<double>("epsilon", 1e-5); | ||
| int64_t stash_type_i = | ||
| node.get_attribute_value<int64_t>("stash_type", | ||
| static_cast<int64_t>(ONNX_NAMESPACE::TensorProto_DataType_FLOAT)); | ||
| element::Type stash_type = common::get_ov_element_type(stash_type_i); | ||
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| // following calculations are kept as close to the onnx\defs.cc description as possible | ||
| auto FloatEpsilon = Constant::create(ov::element::f32, Shape{}, {epsilon}); | ||
| auto Epsilon = std::make_shared<Convert>(FloatEpsilon, stash_type); | ||
| auto XShape = std::make_shared<ShapeOf>(X); | ||
| auto Rank = std::make_shared<v3::ShapeOf>(XShape); | ||
| auto Zero1D = Constant::create(ov::element::i64, {1}, {0}); | ||
| auto One1D = Constant::create(ov::element::i64, {1}, {1}); | ||
| auto Axis1D = Constant::create(ov::element::i64, {1}, {axis}); | ||
| auto PrefixShape = std::make_shared<Slice>(XShape, Zero1D, Axis1D, One1D); | ||
| ov::Output<ov::Node> NumReducedAxes = (axis >= 0 ? std::make_shared<Subtract>(Rank, Axis1D)->output(0) | ||
| : std::make_shared<Negative>(Axis1D)->output(0)); | ||
| auto SuffixShape = std::make_shared<v3::Broadcast>(One1D, NumReducedAxes); | ||
| auto ReducedShape = std::make_shared<Concat>(ov::OutputVector{PrefixShape, SuffixShape}, 0); | ||
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| auto X2D = util::flatten(X, static_cast<int>(axis)); | ||
| auto XU = std::make_shared<Convert>(X2D, stash_type); | ||
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| auto Mean2D = std::make_shared<ReduceMean>(XU, One1D, true); | ||
| auto Square = std::make_shared<Multiply>(XU, XU); | ||
| auto MeanOfSquare = std::make_shared<ReduceMean>(Square, One1D, true); | ||
| auto SquareOfMean = std::make_shared<Multiply>(Mean2D, Mean2D); | ||
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| auto Var = std::make_shared<Subtract>(MeanOfSquare, SquareOfMean); | ||
| auto VarPlusEpsilon = std::make_shared<Add>(Var, Epsilon); | ||
| auto StdDev = std::make_shared<Sqrt>(VarPlusEpsilon); | ||
| auto Deviation = std::make_shared<Subtract>(XU, Mean2D); | ||
| auto Normalized = std::make_shared<Divide>(Deviation, StdDev); | ||
| auto NormalizedT = std::make_shared<ConvertLike>(Normalized, X); | ||
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| auto Scale2D = util::flatten(Scale, 0); | ||
| auto Scaled = std::make_shared<Multiply>(NormalizedT, Scale2D); | ||
| ov::Output<ov::Node> Biased = | ||
| (num_inputs == 3 ? std::make_shared<Add>(Scaled, util::flatten(inputs.at(2), 0))->output(0) | ||
| : Scaled->output(0)); | ||
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| auto Y = std::make_shared<Reshape>(Biased, XShape, false); | ||
| auto InvStdDev2D = std::make_shared<Divide>(Constant::create(stash_type, {1}, {1}), StdDev); | ||
| auto Mean = std::make_shared<Reshape>(Mean2D, ReducedShape, false); | ||
| auto InvStdDev = std::make_shared<Reshape>(InvStdDev2D, ReducedShape, false); | ||
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| return ov::OutputVector{Y, Mean, InvStdDev}; | ||
| } | ||
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| } // namespace set_1 | ||
| } // namespace op | ||
| } // namespace onnx_import | ||
| } // namespace ngraph | ||
| OPENVINO_SUPPRESS_DEPRECATED_END |
20 changes: 20 additions & 0 deletions
20
src/frontends/onnx/frontend/src/op/layer_normalization.hpp
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| Original file line number | Diff line number | Diff line change |
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| // Copyright (C) 2018-2024 Intel Corporation | ||
| // SPDX-License-Identifier: Apache-2.0 | ||
| // | ||
| #pragma once | ||
|
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| #include "openvino/core/deprecated.hpp" | ||
| OPENVINO_SUPPRESS_DEPRECATED_START | ||
|
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| #include "onnx_import/core/node.hpp" | ||
|
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| namespace ngraph { | ||
| namespace onnx_import { | ||
| namespace op { | ||
| namespace set_1 { | ||
| ov::OutputVector layer_normalization(const Node& node); | ||
| } // namespace set_1 | ||
| } // namespace op | ||
| } // namespace onnx_import | ||
| } // namespace ngraph | ||
| OPENVINO_SUPPRESS_DEPRECATED_END |
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