openvino/inference-engine/tests/functional/plugin/cpu/single_layer_tests/mvn.cpp

// Copyright (C) 2018-2021 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
//

#include <shared_test_classes/single_layer/mvn.hpp>
#include "ngraph_functions/builders.hpp"
#include "test_utils/cpu_test_utils.hpp"
#include "test_utils/fusing_test_utils.hpp"

using namespace InferenceEngine;
using namespace CPUTestUtils;

namespace CPULayerTestsDefinitions {

typedef std::tuple<
        LayerTestsDefinitions::mvn1Params,
        CPUSpecificParams,
        fusingSpecificParams,
        Precision, // CNNNetwork input precision
        Precision> // CNNNetwork output precision
MvnLayerCPUTestParamSet;

class MvnLayerCPUTest : public testing::WithParamInterface<MvnLayerCPUTestParamSet>,
                        virtual public LayerTestsUtils::LayerTestsCommon, public CpuTestWithFusing {
public:
    static std::string getTestCaseName(testing::TestParamInfo<MvnLayerCPUTestParamSet> obj) {
        LayerTestsDefinitions::mvn1Params basicParamsSet;
        CPUSpecificParams cpuParams;
        fusingSpecificParams fusingParams;
        Precision inputPrecision, outputPrecision;
        std::tie(basicParamsSet, cpuParams, fusingParams, inputPrecision, outputPrecision) = obj.param;

        std::ostringstream result;
        result << LayerTestsDefinitions::Mvn1LayerTest::getTestCaseName(testing::TestParamInfo<LayerTestsDefinitions::mvn1Params>(
                basicParamsSet, 0));

        result << "_" << "CNNInpPrc=" << inputPrecision.name();
        result << "_" << "CNNOutPrc=" << outputPrecision.name();

        result << CPUTestsBase::getTestCaseName(cpuParams);

        result << CpuTestWithFusing::getTestCaseName(fusingParams);

        return result.str();
    }
protected:
    void SetUp() override {
        LayerTestsDefinitions::mvn1Params basicParamsSet;
        CPUSpecificParams cpuParams;
        fusingSpecificParams fusingParams;
        std::tie(basicParamsSet, cpuParams, fusingParams, inPrc, outPrc) = this->GetParam();

        std::tie(inFmts, outFmts, priority, selectedType) = cpuParams;
        std::tie(postOpMgrPtr, fusedOps) = fusingParams;

        InferenceEngine::SizeVector inputShapes;
        InferenceEngine::Precision netPrecision;
        ngraph::AxisSet axes;
        bool acrossChanels, normalizeVariance;
        double eps;
        std::tie(inputShapes, netPrecision, axes, acrossChanels, normalizeVariance, eps, targetDevice) = basicParamsSet;
        auto netPrc = FuncTestUtils::PrecisionUtils::convertIE2nGraphPrc(netPrecision);
        auto param = ngraph::builder::makeParams(netPrc, {inputShapes});
        auto paramOuts = ngraph::helpers::convert2OutputVector(ngraph::helpers::castOps2Nodes<ngraph::op::Parameter>(param));
        auto mvn = ngraph::builder::makeMVN(paramOuts[0], acrossChanels, normalizeVariance, eps);
        if (!axes.empty()) {
             mvn = ngraph::builder::makeMVN(paramOuts[0], axes, normalizeVariance, eps);
        }

        selectedType = getPrimitiveType() + "_" + inPrc.name();

        threshold = 0.015f;
        function = makeNgraphFunction(netPrc, param, mvn, "mvn");
    }
};

TEST_P(MvnLayerCPUTest, CompareWithRefs) {
    SKIP_IF_CURRENT_TEST_IS_DISABLED()

    Run();
    CheckPluginRelatedResults(executableNetwork, "MVN");
}

namespace {
const std::vector<std::vector<size_t>> inputShapes_1D = {
        {5},
        {16},
};

const std::vector<std::vector<size_t>> inputShapes_2D = {
        {1, 32},
        {16, 64},
};

const std::vector<std::vector<size_t>> inputShapes_3D = {
        {1, 32, 17},
        {1, 37, 9},
        {1, 16, 4},
};

const std::vector<std::vector<size_t>> inputShapes_4D = {
        {1, 16, 5, 8},
        {2, 19, 5, 10},
        {7, 32, 2, 8},
        {5, 8, 3, 5},
        {1, 2, 7, 5},
        {1, 4, 5, 5},
        {1, 7, 3, 5},
        {1, 15, 9, 5},
        {4, 41, 6, 9}
};

const std::vector<std::vector<size_t>> inputShapes_5D = {
        {1, 32, 8, 1, 6},
        {1, 9, 1, 15, 9},
        {6, 64, 6, 1, 18},
        {2, 31, 2, 9, 1},
        {10, 16, 5, 10, 6}
};

const std::vector<bool> acrossChannels = {
        true,
        false
};

const std::vector<bool> normalizeVariance = {
        true,
        false
};

const std::vector<double> epsilon = {
        0.000000001
};

const std::vector<ngraph::AxisSet> emptyReductionAxes = {{}};

std::vector<Precision> inpPrc = {Precision::I8, Precision::BF16, Precision::FP32};
std::vector<Precision> outPrc = {Precision::BF16, Precision::FP32};

std::vector<CPUSpecificParams> cpuParams_4D = {
        CPUSpecificParams({nhwc}, {nhwc}, {}, {}),
        CPUSpecificParams({nChw16c}, {nChw16c}, {}, {}),
        CPUSpecificParams({nchw}, {nchw}, {}, {})
};

std::vector<CPUSpecificParams> cpuParams_5D = {
        CPUSpecificParams({ndhwc}, {ndhwc}, {}, {}),
        CPUSpecificParams({nCdhw16c}, {nCdhw16c}, {}, {}),
        CPUSpecificParams({ncdhw}, {ncdhw}, {}, {})
};

std::vector<fusingSpecificParams> fusingParamsSet {
        emptyFusingSpec,
        /* activations */
        fusingRelu,
        fusingElu,
        fusingTanh,
        fusingSwish,
        /* FQ */
        fusingFakeQuantizePerChannel,
        fusingFakeQuantizePerChannelRelu,
        fusingFakeQuantizePerTensorRelu,
        /* another patterns */
        fusingScaleShift,
};

const auto Mvn3D = ::testing::Combine(
        ::testing::Combine(
            ::testing::ValuesIn(inputShapes_3D),
            ::testing::Values(InferenceEngine::Precision::FP32),
            ::testing::ValuesIn(emptyReductionAxes),
            ::testing::ValuesIn(acrossChannels),
            ::testing::ValuesIn(normalizeVariance),
            ::testing::ValuesIn(epsilon),
            ::testing::Values(CommonTestUtils::DEVICE_CPU)),
        ::testing::Values(emptyCPUSpec),
        ::testing::ValuesIn(fusingParamsSet),
        ::testing::ValuesIn(inpPrc),
        ::testing::ValuesIn(outPrc));

INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs_Mvn3D, MvnLayerCPUTest, Mvn3D, MvnLayerCPUTest::getTestCaseName);

const auto Mvn4D = ::testing::Combine(
        ::testing::Combine(
                ::testing::ValuesIn(inputShapes_4D),
                ::testing::Values(InferenceEngine::Precision::FP32),
                ::testing::ValuesIn(emptyReductionAxes),
                ::testing::ValuesIn(acrossChannels),
                ::testing::ValuesIn(normalizeVariance),
                ::testing::ValuesIn(epsilon),
                ::testing::Values(CommonTestUtils::DEVICE_CPU)),
        ::testing::ValuesIn(filterCPUSpecificParams(cpuParams_4D)),
        ::testing::ValuesIn(fusingParamsSet),
        ::testing::ValuesIn(inpPrc),
        ::testing::ValuesIn(outPrc));

INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs_Mvn4D, MvnLayerCPUTest, Mvn4D, MvnLayerCPUTest::getTestCaseName);

const auto Mvn5D = ::testing::Combine(
        ::testing::Combine(
                ::testing::ValuesIn(inputShapes_5D),
                ::testing::Values(InferenceEngine::Precision::FP32),
                ::testing::ValuesIn(emptyReductionAxes),
                ::testing::ValuesIn(acrossChannels),
                ::testing::ValuesIn(normalizeVariance),
                ::testing::ValuesIn(epsilon),
                ::testing::Values(CommonTestUtils::DEVICE_CPU)),
        ::testing::ValuesIn(filterCPUSpecificParams(cpuParams_5D)),
        ::testing::ValuesIn(fusingParamsSet),
        ::testing::ValuesIn(inpPrc),
        ::testing::ValuesIn(outPrc));

INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs_Mvn5D, MvnLayerCPUTest, Mvn5D, MvnLayerCPUTest::getTestCaseName);

// 1D 2D case
std::vector<fusingSpecificParams> fusingUnaryEltwiseParamsSet {
        /* activations */
        fusingRelu,
        fusingElu,
        fusingTanh,
        fusingSwish,
};

const auto Mvn1D = ::testing::Combine(
        ::testing::Combine(
                ::testing::ValuesIn(inputShapes_1D),
                ::testing::Values(InferenceEngine::Precision::FP32),
                ::testing::ValuesIn(emptyReductionAxes),
                ::testing::ValuesIn(acrossChannels),
                ::testing::ValuesIn(normalizeVariance),
                ::testing::ValuesIn(epsilon),
                ::testing::Values(CommonTestUtils::DEVICE_CPU)),
        ::testing::Values(emptyCPUSpec),
        ::testing::ValuesIn(fusingUnaryEltwiseParamsSet),
        ::testing::ValuesIn(inpPrc),
        ::testing::ValuesIn(outPrc));

INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs_Mvn1D, MvnLayerCPUTest, Mvn1D, MvnLayerCPUTest::getTestCaseName);

// 2D no transformed
const auto Mvn2D = ::testing::Combine(
        ::testing::Combine(
                ::testing::ValuesIn(inputShapes_2D),
                ::testing::Values(InferenceEngine::Precision::FP32),
                ::testing::ValuesIn(emptyReductionAxes),
                ::testing::Values(false),
                ::testing::ValuesIn(normalizeVariance),
                ::testing::ValuesIn(epsilon),
        ::testing::Values(CommonTestUtils::DEVICE_CPU)),
        ::testing::Values(emptyCPUSpec),
        ::testing::ValuesIn(fusingParamsSet),
        ::testing::ValuesIn(inpPrc),
        ::testing::ValuesIn(outPrc));

INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs_Mvn2D, MvnLayerCPUTest, Mvn2D, MvnLayerCPUTest::getTestCaseName);

// 2d transformed
const auto Mvn2DTrans = ::testing::Combine(
        ::testing::Combine(
                ::testing::ValuesIn(inputShapes_2D),
                ::testing::Values(InferenceEngine::Precision::FP32),
                ::testing::ValuesIn(emptyReductionAxes),
                ::testing::Values(true),
                ::testing::ValuesIn(normalizeVariance),
                ::testing::ValuesIn(epsilon),
        ::testing::Values(CommonTestUtils::DEVICE_CPU)),
        ::testing::Values(emptyCPUSpec),
        ::testing::ValuesIn(fusingUnaryEltwiseParamsSet),
        ::testing::ValuesIn(inpPrc),
        ::testing::ValuesIn(outPrc));

INSTANTIATE_TEST_SUITE_P(smoke_CompareWithRefs_MVN2DTrans, MvnLayerCPUTest, Mvn2DTrans, MvnLayerCPUTest::getTestCaseName);

} // namespace
} // namespace CPULayerTestsDefinitions