IVGCVSW-3381 Break up LayerTests.hpp into more manageable files

Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: Icf39434f09fd340ad664cb3b97b8bee6d9da4838

1 files changed, 0 insertions, 430 deletions

diff --git a/src/backends/backendsCommon/test/StridedSliceTestImpl.hpp b/src/backends/backendsCommon/test/StridedSliceTestImpl.hpp
deleted file mode 100644
index f15602c37b..0000000000
--- a/src/backends/backendsCommon/test/StridedSliceTestImpl.hpp
+++ /dev/null
@@ -1,430 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#pragma once
-
-#include <ResolveType.hpp>
-#include "WorkloadTestUtils.hpp"
-
-#include <armnn/ArmNN.hpp>
-#include <armnn/Tensor.hpp>
-#include <armnn/TypesUtils.hpp>
-
-#include <backendsCommon/CpuTensorHandle.hpp>
-#include <backendsCommon/IBackendInternal.hpp>
-#include <backendsCommon/WorkloadFactory.hpp>
-
-#include <test/TensorHelpers.hpp>
-
-namespace
-{
-
-template<typename T, std::size_t InDim, std::size_t OutDim>
-LayerTestResult<T, OutDim> StridedSliceTestImpl(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::TensorInfo& inputTensorInfo,
-    armnn::TensorInfo& outputTensorInfo,
-    std::vector<float>& inputData,
-    std::vector<float>& outputExpectedData,
-    armnn::StridedSliceQueueDescriptor descriptor,
-    const float qScale = 1.0f,
-    const int32_t qOffset = 0)
-{
-    if(armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(qScale);
-        inputTensorInfo.SetQuantizationOffset(qOffset);
-
-        outputTensorInfo.SetQuantizationScale(qScale);
-        outputTensorInfo.SetQuantizationOffset(qOffset);
-    }
-
-    boost::multi_array<T, InDim> input =
-        MakeTensor<T, InDim>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData));
-
-    LayerTestResult<T, OutDim> ret(outputTensorInfo);
-    ret.outputExpected =
-        MakeTensor<T, OutDim>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, outputExpectedData));
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle =
-        workloadFactory.CreateTensorHandle(inputTensorInfo);
-
-    std::unique_ptr<armnn::ITensorHandle> outputHandle =
-        workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateStridedSlice(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-
-    CopyDataToITensorHandle(inputHandle.get(), input.data());
-
-    ExecuteWorkload(*workload, memoryManager);
-
-    CopyDataFromITensorHandle(ret.output.data(), outputHandle.get());
-
-    return ret;
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> StridedSlice4DTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo;
-    armnn::TensorInfo outputTensorInfo;
-
-    unsigned int inputShape[]  = {3, 2, 3, 1};
-    unsigned int outputShape[] = {1, 2, 3, 1};
-
-    armnn::StridedSliceQueueDescriptor desc;
-    desc.m_Parameters.m_Begin  = {1, 0, 0, 0};
-    desc.m_Parameters.m_End    = {2, 2, 3, 1};
-    desc.m_Parameters.m_Stride = {1, 1, 1, 1};
-
-    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
-    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
-
-    std::vector<float> input = std::vector<float>(
-    {
-        1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
-
-        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
-
-        5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f
-    });
-
-    std::vector<float> outputExpected = std::vector<float>(
-    {
-        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f
-    });
-
-    return StridedSliceTestImpl<T, 4, 4>(
-        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> StridedSlice4DReverseTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo;
-    armnn::TensorInfo outputTensorInfo;
-
-    unsigned int inputShape[]  = {3, 2, 3, 1};
-    unsigned int outputShape[] = {1, 2, 3, 1};
-
-    armnn::StridedSliceQueueDescriptor desc;
-    desc.m_Parameters.m_Begin  = {1, -1, 0, 0};
-    desc.m_Parameters.m_End    = {2, -3, 3, 1};
-    desc.m_Parameters.m_Stride = {1, -1, 1, 1};
-
-    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
-    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
-
-    std::vector<float> input = std::vector<float>(
-    {
-        1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
-
-        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
-
-        5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f
-    });
-
-    std::vector<float> outputExpected = std::vector<float>(
-    {
-        4.0f, 4.0f, 4.0f, 3.0f, 3.0f, 3.0f
-    });
-
-    return StridedSliceTestImpl<T, 4, 4>(
-        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> StridedSliceSimpleStrideTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo;
-    armnn::TensorInfo outputTensorInfo;
-
-    unsigned int inputShape[]  = {3, 2, 3, 1};
-    unsigned int outputShape[] = {2, 1, 2, 1};
-
-    armnn::StridedSliceQueueDescriptor desc;
-    desc.m_Parameters.m_Begin  = {0, 0, 0, 0};
-    desc.m_Parameters.m_End    = {3, 2, 3, 1};
-    desc.m_Parameters.m_Stride = {2, 2, 2, 1};
-
-    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
-    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
-
-    std::vector<float> input = std::vector<float>(
-    {
-        1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
-
-        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
-
-        5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f
-    });
-
-    std::vector<float> outputExpected = std::vector<float>(
-    {
-        1.0f, 1.0f,
-
-        5.0f, 5.0f
-    });
-
-    return StridedSliceTestImpl<T, 4, 4>(
-        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> StridedSliceSimpleRangeMaskTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo;
-    armnn::TensorInfo outputTensorInfo;
-
-    unsigned int inputShape[]  = {3, 2, 3, 1};
-    unsigned int outputShape[] = {3, 2, 3, 1};
-
-    armnn::StridedSliceQueueDescriptor desc;
-    desc.m_Parameters.m_Begin     = {1, 1, 1, 1};
-    desc.m_Parameters.m_End       = {1, 1, 1, 1};
-    desc.m_Parameters.m_Stride    = {1, 1, 1, 1};
-    desc.m_Parameters.m_BeginMask = (1 << 4) - 1;
-    desc.m_Parameters.m_EndMask   = (1 << 4) - 1;
-
-    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
-    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
-
-    std::vector<float> input = std::vector<float>(
-    {
-        1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
-
-        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
-
-        5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f
-    });
-
-    std::vector<float> outputExpected = std::vector<float>(
-    {
-        1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f,
-
-        3.0f, 3.0f, 3.0f, 4.0f, 4.0f, 4.0f,
-
-        5.0f, 5.0f, 5.0f, 6.0f, 6.0f, 6.0f
-    });
-
-    return StridedSliceTestImpl<T, 4, 4>(
-        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 2> StridedSliceShrinkAxisMaskTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo;
-    armnn::TensorInfo outputTensorInfo;
-
-    unsigned int inputShape[]  = {3, 2, 3, 1};
-    unsigned int outputShape[] = {3, 1};
-
-    armnn::StridedSliceQueueDescriptor desc;
-    desc.m_Parameters.m_Begin          = {0, 0, 1, 0};
-    desc.m_Parameters.m_End            = {1, 1, 1, 1};
-    desc.m_Parameters.m_Stride         = {1, 1, 1, 1};
-    desc.m_Parameters.m_EndMask        = (1 << 4) - 1;
-    desc.m_Parameters.m_ShrinkAxisMask = (1 << 1) | (1 << 2);
-
-    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
-    outputTensorInfo = armnn::TensorInfo(2, outputShape, ArmnnType);
-
-    std::vector<float> input = std::vector<float>(
-    {
-        1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f,
-
-        7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f,
-
-        13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f
-    });
-
-    std::vector<float> outputExpected = std::vector<float>(
-    {
-        2.0f, 8.0f, 14.0f
-    });
-
-    return StridedSliceTestImpl<T, 4, 2>(
-        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 3> StridedSlice3DTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo;
-    armnn::TensorInfo outputTensorInfo;
-
-    unsigned int inputShape[]  = {3, 3, 3};
-    unsigned int outputShape[] = {2, 2, 2};
-
-    armnn::StridedSliceQueueDescriptor desc;
-    desc.m_Parameters.m_Begin   = {0, 0, 0};
-    desc.m_Parameters.m_End     = {1, 1, 1};
-    desc.m_Parameters.m_Stride  = {2, 2, 2};
-    desc.m_Parameters.m_EndMask = (1 << 3) - 1;
-
-    inputTensorInfo = armnn::TensorInfo(3, inputShape, ArmnnType);
-    outputTensorInfo = armnn::TensorInfo(3, outputShape, ArmnnType);
-
-    std::vector<float> input = std::vector<float>(
-    {
-        1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f,
-
-        10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f,
-
-        19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f, 25.0f, 26.0f, 27.0f
-    });
-
-    std::vector<float> outputExpected = std::vector<float>(
-    {
-        1.0f, 3.0f, 7.0f, 9.0f,
-
-        19.0f, 21.0f, 25.0f, 27.0f
-    });
-
-    return StridedSliceTestImpl<T, 3, 3>(
-        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 3> StridedSlice3DReverseTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo;
-    armnn::TensorInfo outputTensorInfo;
-
-    unsigned int inputShape[]  = {3, 3, 3};
-    unsigned int outputShape[] = {2, 2, 2};
-
-    armnn::StridedSliceQueueDescriptor desc;
-    desc.m_Parameters.m_Begin  = {-1, -1, -1};
-    desc.m_Parameters.m_End    = {-4, -4, -4};
-    desc.m_Parameters.m_Stride = {-2, -2, -2};
-
-    inputTensorInfo = armnn::TensorInfo(3, inputShape, ArmnnType);
-    outputTensorInfo = armnn::TensorInfo(3, outputShape, ArmnnType);
-
-    std::vector<float> input = std::vector<float>(
-    {
-        1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f,
-
-        10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f, 17.0f, 18.0f,
-
-        19.0f, 20.0f, 21.0f, 22.0f, 23.0f, 24.0f, 25.0f, 26.0f, 27.0f
-    });
-
-    std::vector<float> outputExpected = std::vector<float>(
-    {
-        27.0f, 25.0f, 21.0f, 19.0f,
-
-        9.0f, 7.0f, 3.0f, 1.0f
-    });
-
-    return StridedSliceTestImpl<T, 3, 3>(
-        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 2> StridedSlice2DTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo;
-    armnn::TensorInfo outputTensorInfo;
-
-    unsigned int inputShape[]  = {3, 3};
-    unsigned int outputShape[] = {2, 2};
-
-    armnn::StridedSliceQueueDescriptor desc;
-    desc.m_Parameters.m_Begin   = {0, 0};
-    desc.m_Parameters.m_End     = {1, 1};
-    desc.m_Parameters.m_Stride  = {2, 2};
-    desc.m_Parameters.m_EndMask = (1 << 2) - 1;
-
-    inputTensorInfo = armnn::TensorInfo(2, inputShape, ArmnnType);
-    outputTensorInfo = armnn::TensorInfo(2, outputShape, ArmnnType);
-
-    std::vector<float> input = std::vector<float>(
-    {
-        1.0f, 2.0f, 3.0f,
-
-        4.0f, 5.0f, 6.0f,
-
-        7.0f, 8.0f, 9.0f
-    });
-
-    std::vector<float> outputExpected = std::vector<float>(
-    {
-        1.0f, 3.0f,
-
-        7.0f, 9.0f
-    });
-
-    return StridedSliceTestImpl<T, 2, 2>(
-        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 2> StridedSlice2DReverseTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo;
-    armnn::TensorInfo outputTensorInfo;
-
-    unsigned int inputShape[]  = {3, 3};
-    unsigned int outputShape[] = {2, 2};
-
-    armnn::StridedSliceQueueDescriptor desc;
-    desc.m_Parameters.m_Begin     = {0, 0};
-    desc.m_Parameters.m_End       = {1, 1};
-    desc.m_Parameters.m_Stride    = {-2, -2};
-    desc.m_Parameters.m_BeginMask = (1 << 2) - 1;
-    desc.m_Parameters.m_EndMask   = (1 << 2) - 1;
-
-    inputTensorInfo = armnn::TensorInfo(2, inputShape, ArmnnType);
-    outputTensorInfo = armnn::TensorInfo(2, outputShape, ArmnnType);
-
-    std::vector<float> input = std::vector<float>(
-    {
-        1.0f, 2.0f, 3.0f,
-
-        4.0f, 5.0f, 6.0f,
-
-        7.0f, 8.0f, 9.0f
-    });
-
-    std::vector<float> outputExpected = std::vector<float>(
-    {
-        9.0f, 7.0f,
-
-        3.0f, 1.0f
-    });
-
-    return StridedSliceTestImpl<T, 2, 2>(
-        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
-}
-
-} // anonymous namespace