// Copyright (C) 2018-2020 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//

#include <string>
#include "ngraph_reader_tests.hpp"
TEST_F(NGraphReaderTests, ConvertMulAddToScaleShift) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="256"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>64</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="mul" type="Multiply" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>64</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="broadcast2_data" type="Const" version="opset1">
            <data offset="320" size="256"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>64</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="4" name="add" type="Add" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>64</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="5" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="4" to-port="0"/>
        <edge from-layer="3" from-port="0" to-layer="4" to-port="1"/>
        <edge from-layer="4" from-port="2" to-layer="5" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="add" precision="FP32" type="ScaleShift">
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
            <weights offset="0" size="256"/>
            <biases offset="256" size="256"/>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 6422528);
}

TEST_F(NGraphReaderTests, ConvertMulAddToPower) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="4"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="mul" type="Multiply" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="broadcast2_data" type="Const" version="opset1">
            <data offset="68" size="4"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="4" name="add" type="Add" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="5" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="4" to-port="0"/>
        <edge from-layer="3" from-port="0" to-layer="4" to-port="1"/>
        <edge from-layer="4" from-port="2" to-layer="5" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="add" precision="FP32" type="Power">
            <data power="1.000000" scale="127.500000" shift="0.820000"/>
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";

    compareIRs(model, modelV5, 6422528, [](Blob::Ptr& weights) {
                // Set scale/shift constants
                auto* scale = reinterpret_cast<float *>(weights->buffer().as<int8_t*>() + 0);
                scale[0] = 127.5;

                auto* shift = reinterpret_cast<float *>(weights->buffer().as<int8_t*>() + 68);
                shift[0] = 0.82;
            });
}

TEST_F(NGraphReaderTests, ConvertMulToPower) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="4"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="mul" type="Multiply" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="mul" precision="FP32" type="Power">
            <data power="1.000000" scale="127.500000" shift="0.000000"/>
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 6422528, [](Blob::Ptr& weights) {
                // Set scale/shift constants
                auto* scale = reinterpret_cast<float *>(weights->buffer().as<int8_t*>() + 0);
                scale[0] = 127.5;

                auto* shift = reinterpret_cast<float *>(weights->buffer().as<int8_t*>() + 68);
                shift[0] = 0;
            });
}

TEST_F(NGraphReaderTests, ConvertMulToPower2) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="4"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="mul" type="Multiply" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="mul" precision="FP32" type="Power">
            <data power="1.000000" scale="127.500000" shift="0.000000"/>
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";

    compareIRs(model, modelV5, 6422528, [](Blob::Ptr& weights) {
        // Set scale/shift constants
        float *scale = reinterpret_cast<float *>(weights->buffer().as<int8_t *>() + 0);
        scale[0] = 127.5;

        float *shift = reinterpret_cast<float *>(weights->buffer().as<int8_t *>() + 68);
        shift[0] = 0;
    });
}

TEST_F(NGraphReaderTests, ConvertAddToPower) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="4"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="add" type="Add" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="add" precision="FP32" type="Power">
            <data power="1.000000" scale="1.000000" shift="1.000000"/>
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 6422528, [](Blob::Ptr& weights) {
                // Set scale/shift constants
                auto* scale = reinterpret_cast<float *>(weights->buffer().as<int8_t*>() + 0);
                scale[0] = 1;

                auto* shift = reinterpret_cast<float *>(weights->buffer().as<int8_t*>() + 68);
                shift[0] = 127;
            });
}

TEST_F(NGraphReaderTests, ConvertMulToScaleShift) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="256"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>64</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="mul" type="Multiply" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>64</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="mul" precision="FP32" type="ScaleShift">
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
            <weights offset="0" size="256"/>
            <biases offset="256" size="256"/>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 6422528);
}

TEST_F(NGraphReaderTests, ConvertAddToScaleShift) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="256"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>64</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="add" type="Add" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>64</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="add" precision="FP32" type="ScaleShift">
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
            <weights offset="0" size="256"/>
            <biases offset="256" size="256"/>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 6422528);
}

TEST_F(NGraphReaderTests, ConvertMulToEltwise) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="448"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>112</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="mul" type="Multiply" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>112</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="14" name="broadcast1_data" precision="FP32" type="Const">
            <output>
                <port id="1">
                    <dim>112</dim>
                    <dim>1</dim>
                </port>
            </output>
            <blobs>
                <custom offset="0" size="448"/>
            </blobs>
        </layer>
        <layer id="3" name="mul" precision="FP32" type="Eltwise">
            <data operation="prod" />
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1">
                    <dim>112</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
        <edge from-layer="14" from-port="1" to-layer="3" to-port="1"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 6422528);
}

TEST_F(NGraphReaderTests, ConvertAddToEltwise) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="448"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>112</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="add" type="Add" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>112</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="14" name="broadcast1_data" precision="FP32" type="Const">
            <output>
                <port id="1">
                    <dim>112</dim>
                    <dim>1</dim>
                </port>
            </output>
            <blobs>
                <custom offset="0" size="448"/>
            </blobs>
        </layer>
        <layer id="3" name="add" precision="FP32" type="Eltwise">
            <data operation="sum" />
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1">
                    <dim>112</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
        <edge from-layer="14" from-port="1" to-layer="3" to-port="1"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 6422528);
}

TEST_F(NGraphReaderTests, ReadAddNoBroadcastNetwork) {
    std::string model = R"V0G0N(
<net name="Add" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="data1" type="Const" version="opset1">
            <data offset="0" size="3211264"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="add" type="Add" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer name="output" type="Result" id="2" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="3" to-port="1"/>
        <edge from-layer="3" from-port="3" to-layer="2" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="data1" precision="FP32" type="Const">
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
            <blobs>
                <custom offset="0" size="3211264"/>
            </blobs>
        </layer>
        <layer id="3" name="add" precision="FP32" type="Eltwise">
            <data operation="sum"/>
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
        <edge from-layer="2" from-port="3" to-layer="3" to-port="1"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 3211264);
}

TEST_F(NGraphReaderTests, ReadMultiplyNoBroadcastNetwork) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="data1" type="Const" version="opset1">
            <data offset="0" size="3211264"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="mul" type="Multiply" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer name="output" type="Result" id="2" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="3" to-port="1"/>
        <edge from-layer="3" from-port="3" to-layer="2" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="data1" precision="FP32" type="Const">
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
            <blobs>
                <custom offset="0" size="3211264"/>
            </blobs>
        </layer>
        <layer id="3" name="mul" precision="FP32" type="Eltwise">
            <data operation="prod"/>
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
        <edge from-layer="2" from-port="3" to-layer="3" to-port="1"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 3211264);
}

TEST_F(NGraphReaderTests, RemoveAdd) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="4"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="add" type="Add" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="4" name="relu" type="ReLU" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="4" to-port="0"/>
        <edge from-layer="4" from-port="1" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="relu" precision="FP32" type="ReLU">
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 10, [](Blob::Ptr& weights) {
        // Set scale/shift constants
        auto* scale = reinterpret_cast<float *>(weights->buffer().as<int8_t*>() + 0);
        scale[0] = 0;
    });
}

TEST_F(NGraphReaderTests, RemoveMulAdd) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="4"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="mul" type="Multiply" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="broadcast2_data" type="Const" version="opset1">
            <data offset="68" size="4"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="4" name="add" type="Add" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="6" name="relu" precision="FP32" type="ReLU" version="opset1">
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="5" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="4" to-port="0"/>
        <edge from-layer="3" from-port="0" to-layer="4" to-port="1"/>
        <edge from-layer="4" from-port="2" to-layer="6" to-port="0"/>
        <edge from-layer="6" from-port="1" to-layer="5" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="relu" precision="FP32" type="ReLU">
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";

    compareIRs(model, modelV5, 100, [](Blob::Ptr& weights) {
        // Set scale/shift constants
        auto* scale = reinterpret_cast<float *>(weights->buffer().as<int8_t*>() + 0);
        scale[0] = 1.;

        auto* shift = reinterpret_cast<float *>(weights->buffer().as<int8_t*>() + 68);
        shift[0] = 0.;
    });
}

TEST_F(NGraphReaderTests, RemoveAdd2) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="4" name="relu" type="ReLU" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="4"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="add" type="Add" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="4" to-port="0"/>
        <edge from-layer="4" from-port="1" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="add" precision="FP32" type="ReLU">
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 10, [](Blob::Ptr& weights) {
        // Set scale/shift constants
        auto* scale = reinterpret_cast<float *>(weights->buffer().as<int8_t*>() + 0);
        scale[0] = 0;
    });
}

TEST_F(NGraphReaderTests, RemoveAdd3) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="f32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="4" name="relu" type="ReLU" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="broadcast1_data" type="Const" version="opset1">
            <data offset="0" size="4"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="add" type="Add" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="6" name="broadcast2_data" type="Const" version="opset1">
            <data offset="4" size="4"/>
            <output>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="5" name="add2" type="Add" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="FP32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="output1" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
        <layer id="7" name="output2" type="Result" version="opset1">
            <input>
                <port id="0" precision="FP32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="4" to-port="0"/>
        <edge from-layer="4" from-port="1" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="4" from-port="1" to-layer="5" to-port="0"/>
        <edge from-layer="6" from-port="0" to-layer="5" to-port="1"/>
        <edge from-layer="5" from-port="2" to-layer="3" to-port="0"/>
        <edge from-layer="2" from-port="2" to-layer="7" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="FP32" batch="1">
    <layers>
        <layer id="0" name="data" precision="FP32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="relu" precision="FP32" type="ReLU">
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="1">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="4" name="add" precision="FP32" type="Power">
            <data power="1.000000" scale="1.000000" shift="0.000000"/>
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="5" name="add2" precision="FP32" type="Power">
            <data power="1.000000" scale="1.000000" shift="0.000000"/>
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
        <edge from-layer="3" from-port="1" to-layer="4" to-port="0"/>
        <edge from-layer="3" from-port="1" to-layer="5" to-port="0"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 10, [](Blob::Ptr& weights) {
        // Set scale/shift constants
        auto* scale = reinterpret_cast<float *>(weights->buffer().as<int8_t*>() + 0);
        scale[0] = 0;
        scale[1] = 0;
    });
}

TEST_F(NGraphReaderTests, ConvertAddToEltwise2) {
    std::string model = R"V0G0N(
<net name="Multiply" version="10">
    <layers>
        <layer id="0" name="data" type="Parameter" version="opset1">
            <data element_type="i32" shape="1,64,112,112"/>
            <output>
                <port id="0" precision="I32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="constant_1" type="Const" version="opset1">
            <data offset="0" size="4"/>
            <output>
                <port id="0" precision="I32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
        </layer>
        <layer id="2" name="add" type="Add" version="opset1">
            <input>
                <port id="0" precision="I32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1" precision="I32">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="2" precision="I32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="3" name="output" type="Result" version="opset1">
            <input>
                <port id="0" precision="I32">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </input>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
        <edge from-layer="2" from-port="2" to-layer="3" to-port="0"/>
    </edges>
</net>
)V0G0N";
    std::string modelV5 = R"V0G0N(
<net name="Convolution" version="5" precision="I32" batch="1">
    <layers>
        <layer id="0" name="data" precision="I32" type="Input">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
        <layer id="1" name="Constant_107" precision="I32" type="Const">
            <output>
                <port id="0">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </output>
            <blobs>
                <custom offset="0" size="4"/>
            </blobs>
        </layer>
        <layer id="2" name="add" precision="I32" type="Eltwise">
            <data operation="sum"/>
            <input>
                <port id="0">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
                <port id="1">
                    <dim>1</dim>
                    <dim>1</dim>
                    <dim>1</dim>
                </port>
            </input>
            <output>
                <port id="3">
                    <dim>1</dim>
                    <dim>64</dim>
                    <dim>112</dim>
                    <dim>112</dim>
                </port>
            </output>
        </layer>
    </layers>
    <edges>
        <edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
        <edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
    </edges>
</net>
)V0G0N";
    compareIRs(model, modelV5, 10);
}
