Remove onnx_custom_op doc (#10638)
* Remove onnx_custom_op doc * Remove test * Fixed tests
This commit is contained in:
Ilya Churaev
GitHub
parent
f2bbd5bbb8
commit
806ce96899
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@ -86,11 +86,6 @@ ov_model_convert("${OpenVINO_SOURCE_DIR}/${rel_path}"
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"${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/test_model_zoo/onnx_import"
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ie_onnx_import_out_files)
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set(rel_path "docs/onnx_custom_op")
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ov_model_convert("${OpenVINO_SOURCE_DIR}/${rel_path}"
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"${CMAKE_RUNTIME_OUTPUT_DIRECTORY}/test_model_zoo/docs/models"
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docs_onnx_out_files)
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if(ENABLE_TESTS)
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if(ENABLE_OV_ONNX_FRONTEND AND ENABLE_REQUIREMENTS_INSTALL)
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find_package(PythonInterp 3 REQUIRED)
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@ -17,9 +17,6 @@ if(NOT ENABLE_DOCKER)
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set(OpenVINO_DIR ${CMAKE_BINARY_DIR})
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endif()
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if(ENABLE_OV_ONNX_FRONTEND)
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add_subdirectory(onnx_custom_op)
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endif()
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add_subdirectory(template_extension)
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set(all_docs_targets
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@ -1045,7 +1045,6 @@ EXCLUDE_SYMBOLS = InferenceEngine::details \
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EXAMPLE_PATH = "@OpenVINO_SOURCE_DIR@" \
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"@OpenVINO_SOURCE_DIR@/docs/HOWTO/" \
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"@OpenVINO_SOURCE_DIR@/docs/" \
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"@OpenVINO_SOURCE_DIR@/docs/onnx_custom_op/" \
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"@OpenVINO_SOURCE_DIR@/docs/template_extension/" \
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"@OpenVINO_SOURCE_DIR@/docs/template_extension/old/" \
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"@OpenVINO_SOURCE_DIR@/docs/template_extension/new/" \
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@ -1,18 +0,0 @@
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# Copyright (C) 2018-2022 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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#
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# [cmake:onnx_custom_op]
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set(CMAKE_CXX_STANDARD 11)
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set(TARGET_NAME "onnx_custom_op")
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find_package(OpenVINO REQUIRED COMPONENTS ONNX)
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add_library(${TARGET_NAME} STATIC onnx_custom_op.cpp onnx_custom_op.hpp)
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target_link_libraries(${TARGET_NAME} PUBLIC openvino::core openvino::frontend::onnx)
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# [cmake:onnx_custom_op]
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# Enable code style check
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add_clang_format_target(${TARGET_NAME}_clang FOR_TARGETS ${TARGET_NAME})
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@ -1,52 +0,0 @@
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ir_version: 3
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producer_name: "nGraph ONNX Importer"
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graph {
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node {
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input: "in"
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output: "out"
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name: "customrelu"
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op_type: "CustomRelu"
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domain: "com.example"
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attribute {
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name: "alpha"
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type: FLOAT
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f: 2
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}
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attribute {
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name: "beta"
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type: FLOAT
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f: 3
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}
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}
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name: "custom relu graph"
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input {
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name: "in"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim {
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dim_value: 8
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}
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}
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}
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}
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}
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output {
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name: "out"
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type {
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tensor_type {
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elem_type: 1
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shape {
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dim {
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dim_value: 8
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}
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}
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}
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}
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}
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}
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opset_import {
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domain: "com.example"
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version: 1
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}
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@ -1,57 +0,0 @@
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// Copyright (C) 2018-2022 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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//! [onnx_custom_op:headers]
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// onnx_import/onnx_utils.hpp provides ngraph::onnx_import::register_operator function, that registers operator in ONNX importer's set.
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#include <onnx_import/onnx_utils.hpp>
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// ngraph/opsets/opset5.hpp provides the declaration of predefined nGraph operator set
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#include <ngraph/opsets/opset5.hpp>
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//! [onnx_custom_op:headers]
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void register_custom_relu_operator() {
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// CustomRelu is defined as follows:
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// x >= 0 => f(x) = x * alpha
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// x < 0 => f(x) = x * beta
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//! [onnx_custom_op:register_operator]
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ngraph::onnx_import::register_operator(
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"CustomRelu", 1, "com.example", [](const ngraph::onnx_import::Node& onnx_node) -> ngraph::OutputVector {
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namespace opset = ngraph::opset5;
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ngraph::OutputVector ng_inputs{onnx_node.get_ng_inputs()};
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const ngraph::Output<ngraph::Node>& data = ng_inputs.at(0);
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// create constant node with a single element that's equal to zero
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std::shared_ptr<ngraph::Node> zero_node = opset::Constant::create(data.get_element_type(), ngraph::Shape{}, {0});
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// create a negative map for 'data' node, 1 for negative values , 0 for positive values or zero
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// then convert it from boolean type to `data.get_element_type()`
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std::shared_ptr<ngraph::Node> negative_map = std::make_shared<opset::Convert>(
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std::make_shared<opset::Less>(data, zero_node), data.get_element_type());
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// create a positive map for 'data' node, 0 for negative values , 1 for positive values or zero
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// then convert it from boolean type to `data.get_element_type()`
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std::shared_ptr<ngraph::Node> positive_map = std::make_shared<opset::Convert>(
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std::make_shared<opset::GreaterEqual>(data, zero_node), data.get_element_type());
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// fetch alpha and beta attributes from ONNX node
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float alpha = onnx_node.get_attribute_value<float>("alpha", 1); // if 'alpha' attribute is not provided in the model, then the default value is 1
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float beta = onnx_node.get_attribute_value<float>("beta");
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// create constant node with a single element 'alpha' with type f32
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std::shared_ptr<ngraph::Node> alpha_node = opset::Constant::create(ngraph::element::f32, ngraph::Shape{}, {alpha});
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// create constant node with a single element 'beta' with type f32
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std::shared_ptr<ngraph::Node> beta_node = opset::Constant::create(ngraph::element::f32, ngraph::Shape{}, {beta});
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return {
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std::make_shared<opset::Add>(
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std::make_shared<opset::Multiply>(alpha_node, std::make_shared<opset::Multiply>(data, positive_map)),
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std::make_shared<opset::Multiply>(beta_node, std::make_shared<opset::Multiply>(data, negative_map))
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)
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};
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});
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//! [onnx_custom_op:register_operator]
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}
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void unregister_custom_relu_operator() {
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//! [onnx_custom_op:unregister_operator]
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ngraph::onnx_import::unregister_operator("CustomRelu", 1, "com.example");
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//! [onnx_custom_op:unregister_operator]
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}
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@ -1,8 +0,0 @@
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// Copyright (C) 2018-2022 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#pragma once
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void register_custom_relu_operator();
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void unregister_custom_relu_operator();
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@ -12,12 +12,9 @@ set(INCLUDES ${CMAKE_CURRENT_SOURCE_DIR} $<TARGET_PROPERTY:openvino_intel_cpu_pl
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set(DEPENDENCIES openvino_intel_cpu_plugin)
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set(LINK_LIBRARIES funcSharedTests cpuSpecificRtInfo)
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if (ENABLE_OV_ONNX_FRONTEND)
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list(APPEND INCLUDES "${OpenVINO_SOURCE_DIR}/docs/onnx_custom_op")
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list(APPEND LINK_LIBRARIES onnx_custom_op)
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list(APPEND DEPENDENCIES template_extension onnx_custom_op)
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list(APPEND DEFINES TEST_MODELS="${TEST_MODEL_ZOO}")
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else()
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set(EXCLUDED_SOURCE_PATHS ${CMAKE_CURRENT_SOURCE_DIR}/extension ${CMAKE_CURRENT_SOURCE_DIR}/onnx)
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set(EXCLUDED_SOURCE_PATHS ${CMAKE_CURRENT_SOURCE_DIR}/onnx)
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endif()
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addIeTargetTest(
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@ -5,11 +5,8 @@
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#include <gtest/gtest.h>
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#include <ie_core.hpp>
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#include <ngraph/ngraph.hpp>
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#include <onnx_import/onnx_utils.hpp>
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#include <file_utils.h>
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#include <common_test_utils/test_assertions.hpp>
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#include <onnx_custom_op.hpp>
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class CustomAbsKernel : public InferenceEngine::ILayerExecImpl {
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public:
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@ -152,23 +149,6 @@ static std::string model_full_path(const char* path) {
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return FileUtils::makePath<char>(TEST_MODELS, path);
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}
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TEST(Extension, OnnxModelWithCustomAbs) {
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std::vector<float> input_values{1, -2, 3, -4, 5, -6, 7, -8, 9, -10};
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std::vector<float> expected{1, 4, 3, 8, 5, 12, 7, 16, 9, 20};
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InferenceEngine::Core ie;
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ie.AddExtension(std::make_shared<CustomAbsExtension>());
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ngraph::onnx_import::register_operator(
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CustomAbs::get_type_info_static().name, 1, "custom_domain", [](const ngraph::onnx_import::Node& node) -> ngraph::OutputVector {
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ngraph::OutputVector ng_inputs{node.get_ng_inputs()};
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return {std::make_shared<CustomAbs>(ng_inputs.at(0))};
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});
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auto network = ie.ReadNetwork(model_full_path("func_tests/models/custom_abs_op.onnx"));
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infer_model(ie, network, input_values, expected);
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ngraph::onnx_import::unregister_operator(CustomAbs::get_type_info_static().name, 1, "custom_domain");
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}
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TEST(Extension, XmlModelWithCustomAbs) {
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std::string model = R"V0G0N(
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<net name="Network" version="10">
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@ -293,15 +273,3 @@ TEST(Extension, OnnxModelWithExtensionFromDSO) {
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auto network = ie.ReadNetwork(model_full_path("func_tests/models/custom_template_op.onnx"));
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infer_model(ie, network, input_values, expected);
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}
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TEST(Extension, OnnxModelWithCustomReluDocsExample) {
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std::vector<float> input_values{0, -1, 2, -3, 4, -5, 6, -7};
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std::vector<float> expected{0, -3, 4, -9, 8, -15, 12, -21};
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register_custom_relu_operator();
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InferenceEngine::Core ie;
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auto network = ie.ReadNetwork(model_full_path("docs/models/custom_relu_model.onnx"));
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infer_model(ie, network, input_values, expected);
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unregister_custom_relu_operator();
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}
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