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, 35 insertions, 4645 deletions

diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp
index bb21202731..a4c09a63dc 100644
--- a/src/backends/backendsCommon/test/LayerTests.hpp
+++ b/src/backends/backendsCommon/test/LayerTests.hpp
@@ -2,4658 +2,48 @@
 // Copyright © 2017 Arm Ltd. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
-#pragma once
-
-#include <armnn/ArmNN.hpp>
-#include <armnn/Tensor.hpp>
 
-#include <backendsCommon/test/layerTests/LayerTestResult.hpp>
+#pragma once
 
+#include <backendsCommon/test/layerTests/ActivationTestImpl.hpp>
 #include <backendsCommon/test/layerTests/AdditionTestImpl.hpp>
+#include <backendsCommon/test/layerTests/BatchNormalizationTestImpl.hpp>
+#include <backendsCommon/test/layerTests/BatchToSpaceNdTestImpl.hpp>
+#include <backendsCommon/test/layerTests/ConcatTestImpl.hpp>
+#include <backendsCommon/test/layerTests/ConvertFp16ToFp32TestImpl.hpp>
+#include <backendsCommon/test/layerTests/ConvertFp32ToFp16TestImpl.hpp>
+#include <backendsCommon/test/layerTests/Conv2dTestImpl.hpp>
+#include <backendsCommon/test/layerTests/ConstantTestImpl.hpp>
+#include <backendsCommon/test/layerTests/DebugTestImpl.hpp>
+#include <backendsCommon/test/layerTests/DequantizeTestImpl.hpp>
+#include <backendsCommon/test/layerTests/DetectionPostProcessTestImpl.hpp>
 #include <backendsCommon/test/layerTests/DivisionTestImpl.hpp>
 #include <backendsCommon/test/layerTests/EqualTestImpl.hpp>
+#include <backendsCommon/test/layerTests/FakeQuantizationTestImpl.hpp>
+#include <backendsCommon/test/layerTests/FloorTestImpl.hpp>
+#include <backendsCommon/test/layerTests/FullyConnectedTestImpl.hpp>
+#include <backendsCommon/test/layerTests/GatherTestImpl.hpp>
 #include <backendsCommon/test/layerTests/GreaterTestImpl.hpp>
+#include <backendsCommon/test/layerTests/L2NormalizationTestImpl.hpp>
+#include <backendsCommon/test/layerTests/LstmTestImpl.hpp>
 #include <backendsCommon/test/layerTests/MaximumTestImpl.hpp>
+#include <backendsCommon/test/layerTests/MeanTestImpl.hpp>
 #include <backendsCommon/test/layerTests/MinimumTestImpl.hpp>
 #include <backendsCommon/test/layerTests/MultiplicationTestImpl.hpp>
+#include <backendsCommon/test/layerTests/NormalizationTestImpl.hpp>
+#include <backendsCommon/test/layerTests/PadTestImpl.hpp>
+#include <backendsCommon/test/layerTests/PermuteTestImpl.hpp>
+#include <backendsCommon/test/layerTests/Pooling2dTestImpl.hpp>
+#include <backendsCommon/test/layerTests/PreluTestImpl.hpp>
+#include <backendsCommon/test/layerTests/QuantizeTestImpl.hpp>
+#include <backendsCommon/test/layerTests/ReshapeTestImpl.hpp>
+#include <backendsCommon/test/layerTests/ResizeTestImpl.hpp>
+#include <backendsCommon/test/layerTests/RsqrtTestImpl.hpp>
+#include <backendsCommon/test/layerTests/SoftmaxTestImpl.hpp>
+#include <backendsCommon/test/layerTests/SpaceToBatchNdTestImpl.hpp>
+#include <backendsCommon/test/layerTests/SpaceToDepthTestImpl.hpp>
+#include <backendsCommon/test/layerTests/SplitterTestImpl.hpp>
+#include <backendsCommon/test/layerTests/StackTestImpl.hpp>
+#include <backendsCommon/test/layerTests/StridedSliceTestImpl.hpp>
 #include <backendsCommon/test/layerTests/SubtractionTestImpl.hpp>
-
-#include <Half.hpp>
-#include "TensorCopyUtils.hpp"
-#include "WorkloadTestUtils.hpp"
-#include "TensorUtils.hpp"
-#include "Permute.hpp"
-
-#include <backendsCommon/CpuTensorHandle.hpp>
-#include <backendsCommon/IBackendInternal.hpp>
-#include <backendsCommon/IMemoryManager.hpp>
-#include <reference/workloads/Decoders.hpp>
-#include <reference/workloads/Encoders.hpp>
-#include <test/TensorHelpers.hpp>
-
-#include <boost/multi_array.hpp>
-#include <boost/assert.hpp>
-
-#include <array>
-
-// Layer callables.
-
-namespace armnn
-{
-class IWorkloadFactory;
-}
-
-LayerTestResult<float, 4> SimpleConvolution2d3x5Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> SimpleConvolution2d3x3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> SimpleConvolution2d3x3Stride2x2Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> SimpleConvolution2d3x3NhwcTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled);
-
-LayerTestResult<float, 4> Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::DataLayout layout);
-
-LayerTestResult<float, 4> Convolution2dAsymmetricPaddingTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::DataLayout layout);
-
-LayerTestResult<float,   4> Convolution1dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled);
-
-LayerTestResult<uint8_t, 4> Convolution1dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled);
-
-LayerTestResult<float, 4> DepthwiseConvolution2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> Convolution2d3x3Dilation3x3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> Convolution2d2x3x3Dilation3x3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> Convolution2d2x2Dilation2x2Padding2x2Stride3x3Test(
-    armnn::IWorkloadFactory &workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr &memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> DepthwiseConvolution2d3x3Dilation3x3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> DepthwiseConvolution2d2x3x3Dilation3x3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> DepthwiseConvolution2dMult4Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-template<armnn::DataType ArmnnType, armnn::DataType ArmnnBType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> DepthwiseConvolution2dMult2Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> DepthwiseConvolution2dDepthNhwcTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled);
-
-LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul1Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul64Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> DepthwiseConvolution2dAsymmetricTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> SimpleDepthwiseConvolution2d3x3Dilation3x3NhwcTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> CompareDepthwiseConvolution2dFloatTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    const armnn::DataLayout layout);
-
-LayerTestResult<uint8_t, 4> CompareDepthwiseConvolution2dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    const armnn::DataLayout layout);
-
-LayerTestResult<float,   4> SimpleMaxPooling2dSize2x2Stride2x2Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool forceNoPadding);
-
-LayerTestResult<uint8_t, 4> SimpleMaxPooling2dSize2x2Stride2x2Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool forceNoPadding);
-
-LayerTestResult<int16_t, 4> SimpleMaxPooling2dSize2x2Stride2x2Int16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool forceNoPadding);
-
-LayerTestResult<float,   4> SimpleMaxPooling2dSize3x3Stride2x4Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool forceNoPadding);
-
-LayerTestResult<uint8_t, 4> SimpleMaxPooling2dSize3x3Stride2x4Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool forceNoPadding );
-
-LayerTestResult<int16_t, 4> SimpleMaxPooling2dSize3x3Stride2x4Int16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool forceNoPadding );
-
-LayerTestResult<float,   4> SimpleMaxPooling2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout dataLayout);
-
-LayerTestResult<uint8_t, 4> SimpleMaxPooling2dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout dataLayout);
-
-LayerTestResult<int16_t, 4> SimpleMaxPooling2dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout dataLayout);
-
-LayerTestResult<float,   4> IgnorePaddingSimpleMaxPooling2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> IgnorePaddingSimpleMaxPooling2dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> IgnorePaddingSimpleMaxPooling2dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> IgnorePaddingMaxPooling2dSize3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> IgnorePaddingMaxPooling2dSize3Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> IgnorePaddingMaxPooling2dSize3Int16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> SimpleAveragePooling2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout dataLayout);
-
-LayerTestResult<uint8_t, 4> SimpleAveragePooling2dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout dataLayout);
-
-LayerTestResult<int16_t, 4> SimpleAveragePooling2dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout dataLayout);
-
-LayerTestResult<float,   4> LargeTensorsAveragePooling2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> LargeTensorsAveragePooling2dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> LargeTensorsAveragePooling2dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> IgnorePaddingAveragePooling2dSize3x2Stride2x2Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool forceNoPadding);
-
-LayerTestResult<float,   4> IgnorePaddingSimpleAveragePooling2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> IgnorePaddingSimpleAveragePooling2dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> IgnorePaddingSimpleAveragePooling2dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4>   IgnorePaddingSimpleAveragePooling2dNoPaddingTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> IgnorePaddingSimpleAveragePooling2dNoPaddingUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> IgnorePaddingSimpleAveragePooling2dNoPaddingInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> IgnorePaddingAveragePooling2dSize3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> IgnorePaddingAveragePooling2dSize3Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> IgnorePaddingAveragePooling2dSize3Int16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> SimpleL2Pooling2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout dataLayout);
-
-LayerTestResult<uint8_t, 4> SimpleL2Pooling2dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout dataLayout);
-
-LayerTestResult<int16_t, 4> SimpleL2Pooling2dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout dataLayout);
-
-LayerTestResult<float,   4> L2Pooling2dSize3Stride1Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride1Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> L2Pooling2dSize3Stride1Int16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> L2Pooling2dSize3Stride3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride3Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> L2Pooling2dSize3Stride3Int16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> L2Pooling2dSize3Stride4Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> L2Pooling2dSize3Stride4Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> L2Pooling2dSize3Stride4Int16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> L2Pooling2dSize7Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> L2Pooling2dSize7Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> L2Pooling2dSize7Int16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> L2Pooling2dSize9Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> L2Pooling2dSize9Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> L2Pooling2dSize9Int16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> IgnorePaddingSimpleL2Pooling2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> IgnorePaddingSimpleL2Pooling2dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> IgnorePaddingSimpleL2Pooling2dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> IgnorePaddingL2Pooling2dSize3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> IgnorePaddingL2Pooling2dSize3Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> IgnorePaddingL2Pooling2dSize3Int16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,   4> AsymmetricNonSquarePooling2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> AsymmetricNonSquarePooling2dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> AsymmetricNonSquarePooling2dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> ComparePooling2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    armnn::PoolingAlgorithm  poolingType);
-
-LayerTestResult<uint8_t, 4> ComparePooling2dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    armnn::PoolingAlgorithm  poolingType);
-
-LayerTestResult<int16_t, 4> ComparePooling2dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    armnn::PoolingAlgorithm  poolingType);
-
-LayerTestResult<float, 4> ConstantLinearActivationTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SimpleNormalizationAcrossTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SimpleNormalizationWithinTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float,4> SimpleNormalizationAcrossNhwcTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> SimpleSoftmaxTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    float beta);
-
-LayerTestResult<float, 2> SimpleAxisSoftmaxTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        float beta,
-        int axis);
-
-LayerTestResult<float, 3> Simple3dSoftmaxTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        float beta);
-
-LayerTestResult<float, 3> Simple3dAxisSoftmaxTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        float beta,
-        int axis);
-
-LayerTestResult<float, 4> Simple4dSoftmaxTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        float beta);
-
-LayerTestResult<float, 4> Simple4dAxisSoftmaxTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        float beta,
-        int axis);
-
-LayerTestResult<uint8_t, 2> SimpleSoftmaxUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    float beta);
-
-LayerTestResult<uint8_t,3> Simple3dSoftmaxUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        float beta);
-
-LayerTestResult<uint8_t,4> Simple4dSoftmaxUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        float beta);
-
-LayerTestResult<int16_t,2> SimpleSoftmaxUint16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        float beta);
-
-LayerTestResult<int16_t,3> Simple3dSoftmaxUint16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        float beta);
-
-LayerTestResult<int16_t,4> Simple4dSoftmaxUint16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        float beta);
-
-LayerTestResult<float, 4> SimpleSigmoidTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> SimpleReshapeTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 5> Reshape5dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SimpleFloorTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 1> Concatenation1dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> Concatenation2dDim0Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> Concatenation2dDim1Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> Concatenation2dDim0DiffInputDimsTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> Concatenation2dDim1DiffInputDimsTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> Concatenation3dDim0Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> Concatenation3dDim1Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> Concatenation3dDim2Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool useSubtensor);
-
-LayerTestResult<float, 3> Concatenation3dDim0DiffInputDimsTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> Concatenation3dDim1DiffInputDimsTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> Concatenation3dDim2DiffInputDimsTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool useSubtensor);
-
-LayerTestResult<float, 4> Concatenation4dDim0Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> Concatenation4dDim1Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> Concatenation4dDim2Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> Concatenation4dDim3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool useSubtensor);
-
-LayerTestResult<float, 4> Concatenation4dDiffShapeDim0Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> Concatenation4dDiffShapeDim1Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> Concatenation4dDiffShapeDim2Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> Concatenation4dDiffShapeDim3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool useSubtensor);
-
-LayerTestResult<uint8_t, 4> Concatenation4dDim0Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> Concatenation4dDim1Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> Concatenation4dDim2Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> Concatenation4dDim3Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool useSubtensor);
-
-LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim0Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim1Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim2Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> Concatenation4dDiffShapeDim3Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool useSubtensor);
-
-LayerTestResult<uint8_t, 4> SimpleSigmoidUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SimpleSigmoidInt16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> CompareConvolution2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory);
-
-template<typename T>
-LayerTestResult<T, 4> CompareDepthwiseConvolution2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> CompareNormalizationTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    armnn::NormalizationAlgorithmChannel normChannel,
-    armnn::NormalizationAlgorithmMethod normMethod);
-
-LayerTestResult<float, 2> CompareSoftmaxTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    float beta);
-
-LayerTestResult<float, 2> FullyConnectedFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    bool transposeWeights);
-
-std::vector<LayerTestResult<float, 3>> SplitterTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> CopyViaSplitterTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> ConcatTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> CompareActivationTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    armnn::ActivationFunction f,
-    unsigned int batchSize);
-
-LayerTestResult<float, 4> BatchNormTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> BatchNormNhwcTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> CompareBatchNormTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory);
-
-LayerTestResult<float, 4> BoundedReLuUpperAndLowerBoundTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperAndLowerBoundTest(
-    armnn::IWorkloadFactory& workloadFactor,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManagery);
-
-LayerTestResult<float, 4> BoundedReLuUpperBoundOnlyTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BoundedReLuUint8UpperBoundOnlyTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> CompareBoundedReLuTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    float upperBound,
-    float lowerBound);
-
-LayerTestResult<float, 4> ReLuTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> ReLuUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> ReLuInt16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> BoundedReLuInt16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SoftReLuTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SoftReLuUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SoftReLuInt16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> LeakyReLuTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> LeakyReLuUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> LeakyReLuInt16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> AbsTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> AbsUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> AbsInt16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SqrtTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SqrtUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SqrtInt16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SquareTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SquareUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SquareInt16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> TanhTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> TanhUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> TanhInt16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-
-// Tests that the output should be identical to the input when the output dimensions match the input ones.
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> ResizeBilinearNopTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout);
-
-// Tests the behaviour of the resize bilinear operation when rescaling a 2x2 image into a 1x1 image.
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> SimpleResizeBilinearTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout);
-
-// Tests the resize bilinear for minification of a square input matrix (also: input dimensions are a
-// multiple of output dimensions).
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> ResizeBilinearSqMinTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout);
-
-// Tests the resize bilinear for minification (output dimensions smaller than input dimensions).
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> ResizeBilinearMinTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout);
-
-// Tests the resize bilinear for magnification (output dimensions bigger than input dimensions).
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> ResizeBilinearMagTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout  dataLayout);
-
-// Tests that the output should be identical to the input when the output dimensions match the input ones.
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> ResizeNearestNeighborNopTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout);
-
-// Tests the behaviour of the resize NearestNeighbor operation when rescaling a 2x2 image into a 1x1 image.
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> SimpleResizeNearestNeighborTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout);
-
-// Tests the resize NearestNeighbor for minification of a square input matrix (also: input dimensions are a
-// multiple of output dimensions).
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> ResizeNearestNeighborSqMinTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout);
-
-// Tests the resize NearestNeighbor for minification (output dimensions smaller than input dimensions).
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> ResizeNearestNeighborMinTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout);
-
-// Tests the resize NearestNeighbor for magnification (output dimensions bigger than input dimensions).
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> ResizeNearestNeighborMagTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout  dataLayout,
-        float inQuantScale,
-        int32_t inQuantOffset,
-        float outQuantScale,
-        int32_t outQuantOffset);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 2> Rsqrt2dTestCommon(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::TensorInfo inputTensorInfo,
-        const armnn::TensorInfo outputTensorInfo,
-        const std::vector<float>& inputValues,
-        const std::vector<float>& expectedOutputValues);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 2> Rsqrt2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 3> Rsqrt3dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 2> RsqrtZeroTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 2> RsqrtNegativeTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> BatchNormTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> BatchNormNhwcTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> FakeQuantizationTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> L2NormalizationDefaultEpsilonTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> L2NormalizationNonDefaultEpsilonTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> L2Normalization1dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout layout);
-
-LayerTestResult<int16_t, 4> L2Normalization1dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout layout);
-
-LayerTestResult<uint8_t, 4> L2Normalization1dUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> L2Normalization2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout layout);
-
-LayerTestResult<int16_t, 4> L2Normalization2dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout layout);
-
-LayerTestResult<uint8_t, 4> L2Normalization2dUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout layout);
-
-LayerTestResult<float, 2> L2Normalization2dShapeTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> L2Normalization3dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout layout);
-
-LayerTestResult<int16_t, 4> L2Normalization3dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout layout);
-
-LayerTestResult<uint8_t, 4> L2Normalization3dUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> L2Normalization4dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout layout);
-
-LayerTestResult<int16_t, 4> L2Normalization4dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    const armnn::DataLayout layout);
-
-LayerTestResult<uint8_t, 4> L2Normalization4dUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout layout);
-
-LayerTestResult<float, 4> ConstantTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> ConstantUint8SimpleQuantizationScaleNoOffsetTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> ConstantInt16SimpleQuantizationScaleNoOffsetTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BoundedReLuUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    float upperBound);
-
-LayerTestResult<uint8_t, 4> BoundedReLuUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    float upperBound,
-    float lowerBound);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 2> FullyConnectedTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled);
-
-std::vector<LayerTestResult<uint8_t, 3>> SplitterUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-std::vector<LayerTestResult<int16_t, 3>> SplitterInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> CopyViaSplitterUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 3> CopyViaSplitterInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> ConcatUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint16_t, 3> ConcatUint16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> ConcatUint8DifferentQParamsTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> CompareActivationUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    armnn::ActivationFunction f);
-
-LayerTestResult<int16_t, 4> CompareActivationInt16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        armnn::IWorkloadFactory& refWorkloadFactory,
-        armnn::ActivationFunction f);
-
-LayerTestResult<uint8_t, 2> CompareSoftmaxUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::IWorkloadFactory& refWorkloadFactory,
-    float beta);
-
-LayerTestResult<uint8_t, 4> SimpleConvolution2d3x5Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<uint8_t, 4> SimpleConvolution2d3x3Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<int16_t, 4> SimpleConvolution2d3x5QSymm16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        bool biasEnabled,
-        const armnn::DataLayout layout);
-
-LayerTestResult<int16_t, 4> SimpleConvolution2d3x3QSymm16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        bool biasEnabled,
-        const armnn::DataLayout layout);
-
-LayerTestResult<uint8_t, 4> DepthwiseConvolution2dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<uint8_t, 4> DepthwiseConvolution2dDepthMul1Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<int16_t, 4> DepthwiseConvolution2dInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<int16_t, 4> DepthwiseConvolution2dDepthMul1Int16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool biasEnabled,
-    const armnn::DataLayout layout);
-
-LayerTestResult<uint8_t, 4> ConstantLinearActivationUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> ConstantLinearActivationInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BatchNormUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BatchNormUint8NhwcTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> BatchNormInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> BatchNormInt16NhwcTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> ConstantUint8CustomQuantizationScaleAndOffsetTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> ConstantInt16CustomQuantizationScaleAndOffsetTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 1> Concatenation1dUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 2> Concatenation2dDim0Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 2> Concatenation2dDim1Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 2> Concatenation2dDim0DiffInputDimsUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 2> Concatenation2dDim1DiffInputDimsUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> Concatenation3dDim0Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> Concatenation3dDim1Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> Concatenation3dDim2Uint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool useSubtensor);
-
-LayerTestResult<uint8_t, 3> Concatenation3dDim0DiffInputDimsUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> Concatenation3dDim1DiffInputDimsUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> Concatenation3dDim2DiffInputDimsUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool useSubtensor);
-
-LayerTestResult<float, 2> FullyConnectedLargeTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    bool transposeWeights);
-
-LayerTestResult<uint8_t, 2> PadUint82dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 2> PadUint82dCustomPaddingTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> PadUint83dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> PadUint84dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> PadFloat322dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> PadFloat322dCustomPaddingTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> PadFloat323dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> PadFloat324dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 2> Pad2dTestCommon(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    float qScale,
-    int32_t qOffset,
-    const float customPaddingValue = 0.0f);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 3> Pad3dTestCommon(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    float qScale,
-    int32_t qOffset);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> Pad4dTestCommon(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    float qScale,
-    int32_t qOffset);
-
-void LstmUtilsZeroVectorTest();
-void LstmUtilsMeanStddevNormalizationNoneZeroInputTest();
-void LstmUtilsMeanStddevNormalizationAllZeroInputTest();
-void LstmUtilsMeanStddevNormalizationMixedZeroInputTest();
-void LstmUtilsVectorBatchVectorCwiseProductTest();
-void LstmUtilsVectorBatchVectorAddTest();
-
-LayerTestResult<float, 2> LstmLayerFloat32WithCifgWithPeepholeNoProjectionTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> LstmLayerFloat32NoCifgNoPeepholeNoProjectionTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> LstmLayerFloat32NoCifgWithPeepholeWithProjectionTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> LstmLayerFloat32NoCifgWithPeepholeWithProjectionWithLayerNormTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 2> LstmLayerInt16NoCifgNoPeepholeNoProjectionTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 2> LstmLayerInt16WithCifgWithPeepholeNoProjectionTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 2> LstmLayerInt16NoCifgWithPeepholeWithProjectionTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 2> LstmLayerInt16NoCifgNoPeepholeNoProjectionInt16ConstantTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-// QuantizedLstm
-LayerTestResult<uint8_t, 2> QuantizedLstmTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SimpleConvertFp16ToFp32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<armnn::Half, 4> SimpleConvertFp32ToFp16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> MaximumSimpleTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> MaximumBroadcast1ElementTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> MaximumBroadcast1DVectorTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t , 4> MaximumUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> MaximumBroadcast1ElementUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> MaximumBroadcast1DVectorUint8Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t , 4> MaximumInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> MaximumBroadcast1ElementInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> MaximumBroadcast1DVectorInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 1> MeanSimpleTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 3> MeanSimpleAxisTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> MeanKeepDimsTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> MeanMultipleDimsTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 1> MeanVts1Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 3> MeanVts2Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 3> MeanVts3Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToBatchNdSimpleFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToBatchNdMultiChannelsFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToBatchNdMultiBlockFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToBatchNdPaddingFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SpaceToBatchNdSimpleUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiChannelsUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiBlockUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SpaceToBatchNdPaddingUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToBatchNdSimpleNHWCFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToBatchNdMultiChannelsNHWCFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToBatchNdMultiBlockNHWCFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToBatchNdPaddingNHWCFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SpaceToBatchNdSimpleNHWCUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiChannelsNHWCUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SpaceToBatchNdMultiBlockNHWCUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SpaceToBatchNdPaddingNHWCUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SpaceToBatchNdSimpleUint16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SpaceToBatchNdMultiChannelsUint16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SpaceToBatchNdMultiBlockUint16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SpaceToBatchNdPaddingUint16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SpaceToBatchNdSimpleNHWCUint16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SpaceToBatchNdMultiChannelsNHWCUint16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SpaceToBatchNdMultiBlockNHWCUint16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SpaceToBatchNdPaddingNHWCUint16Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> BatchToSpaceNdNhwcTest1(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> BatchToSpaceNdNhwcTest2(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> BatchToSpaceNdNhwcTest3(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> BatchToSpaceNdNhwcTest4(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> BatchToSpaceNdNchwTest1(
-    armnn::IWorkloadFactory &workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> BatchToSpaceNdNchwTest2(
-    armnn::IWorkloadFactory &workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> BatchToSpaceNdNchwTest3(
-    armnn::IWorkloadFactory &workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BatchToSpaceNdNhwcTest5(
-    armnn::IWorkloadFactory &workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BatchToSpaceNdNhwcTest6(
-    armnn::IWorkloadFactory &workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BatchToSpaceNdNhwcTest7(
-    armnn::IWorkloadFactory &workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BatchToSpaceNdNchwTest4(
-    armnn::IWorkloadFactory &workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BatchToSpaceNdNchwTest5(
-    armnn::IWorkloadFactory &workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BatchToSpaceNdNchwTest6(
-    armnn::IWorkloadFactory &workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> BatchToSpaceNdNchwTest7(
-    armnn::IWorkloadFactory &workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> StridedSlice4DFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> StridedSlice4DReverseFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> StridedSliceSimpleStrideFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> StridedSliceSimpleRangeMaskFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> StridedSliceShrinkAxisMaskFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> StridedSlice3DFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> StridedSlice3DReverseFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> StridedSlice2DFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> StridedSlice2DReverseFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> StridedSlice4DUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> StridedSlice4DReverseUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> StridedSliceSimpleStrideUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> StridedSliceSimpleRangeMaskUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 2> StridedSliceShrinkAxisMaskUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> StridedSlice3DUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> StridedSlice3DReverseUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 2> StridedSlice2DUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 2> StridedSlice2DReverseUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> StridedSlice4DInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> StridedSlice4DReverseInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> StridedSliceSimpleStrideInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> StridedSliceSimpleRangeMaskInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 2> StridedSliceShrinkAxisMaskInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 3> StridedSlice3DInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 3> StridedSlice3DReverseInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 2> StridedSlice2DInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 2> StridedSlice2DReverseInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> Debug4DFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> Debug3DFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> Debug2DFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 1> Debug1DFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> Debug4DUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> Debug3DUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 2> Debug2DUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 1> Debug1DUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> PreCompiledConvolution2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> PreCompiledConvolution2dStride2x2Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> PreCompiledDepthwiseConvolution2dTest(
-    armnn::IWorkloadFactory & workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager);
-
-LayerTestResult<uint8_t, 4> PreCompiledDepthwiseConvolution2dStride2x2Test(
-    armnn::IWorkloadFactory & workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager);
-
-LayerTestResult<uint8_t, 4> PreCompiledMaxPooling2dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> Debug4DFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 3> Debug3DFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> Debug2DFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 1> Debug1DFloat32Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> Debug4DUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 3> Debug3DUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 2> Debug2DUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 1> Debug1DUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 1> Gather1DParamsFloatTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 1> Gather1DParamsUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 1> Gather1DParamsInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 2> GatherMultiDimParamsFloatTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 2> GatherMultiDimParamsUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 2> GatherMultiDimParamsInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> GatherMultiDimParamsMultiDimIndicesFloatTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> GatherMultiDimParamsMultiDimIndicesUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> GatherMultiDimParamsMultiDimIndicesInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> DequantizeSimpleUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> DequantizeOffsetUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> DequantizeSimpleInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SpaceToDepthNCHWAsymmQ8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> SpaceToDepthNHWCAsymmQ8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToDepthNHWCFloat32Test1(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToDepthNCHWFloat32Test1(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToDepthNHWCFloat32Test2(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<float, 4> SpaceToDepthNCHWFloat32Test2(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SpaceToDepthNHWCQSymm16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> SpaceToDepthNCHWQSymm16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> QuantizeSimpleUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<uint8_t, 4> QuantizeClampUint8Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-LayerTestResult<int16_t, 4> QuantizeClampInt16Test(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template <armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-std::vector<T> ConvertToDataType(const std::vector<float>& input,
-                                 const armnn::TensorInfo& inputTensorInfo)
-{
-    std::vector<T> output(input.size());
-    auto outputTensorInfo = inputTensorInfo;
-    outputTensorInfo.SetDataType(ArmnnType);
-
-    std::unique_ptr<armnn::Encoder<float>> pOutputEncoder = armnn::MakeEncoder<float>(outputTensorInfo, output.data());
-    armnn::Encoder<float>& rOutputEncoder = *pOutputEncoder;
-
-    for (auto it = input.begin(); it != input.end(); ++it)
-    {
-        rOutputEncoder.Set(*it);
-        ++rOutputEncoder;
-    }
-    return output;
-}
-
-// Utility method to convert a single value to the correct type
-template <typename T>
-T ConvertToDataType(const float& value,
-                    const armnn::TensorInfo& tensorInfo)
-{
-    std::vector<T> output(1);
-    std::unique_ptr<armnn::Encoder<float>> pEncoder = armnn::MakeEncoder<float>(tensorInfo, output.data());
-    armnn::Encoder<float>& rEncoder = *pEncoder;
-    rEncoder.Set(value);
-    return output[0];
-}
-
-template<typename T, typename B>
-LayerTestResult<T, 2> SimpleFullyConnectedTestImpl(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        armnn::TensorInfo inputTensorInfo,
-        armnn::TensorInfo outputTensorInfo,
-        armnn::TensorInfo weightsDesc,
-        armnn::TensorInfo biasesDesc,
-        boost::multi_array<T, 2>& weights,
-        boost::multi_array<B, 1>& bias,
-        boost::multi_array<T, 4>& input,
-        bool biasEnabled,
-        bool transposeWeights)
-{
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::FullyConnectedQueueDescriptor data;
-    armnn::WorkloadInfo info;
-    armnn::ScopedCpuTensorHandle weightsTensor(weightsDesc);
-    armnn::ScopedCpuTensorHandle biasTensor(biasesDesc);
-
-    AllocateAndCopyDataToITensorHandle(&weightsTensor, &weights[0][0]);
-    AllocateAndCopyDataToITensorHandle(&biasTensor, &bias[0]);
-
-    AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
-    data.m_Weight = &weightsTensor;
-    data.m_Bias = &biasTensor;
-    data.m_Parameters.m_BiasEnabled = biasEnabled;
-    data.m_Parameters.m_TransposeWeightMatrix = transposeWeights;
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateFullyConnected(data, info);
-    LayerTestResult<T, 2> result(outputTensorInfo);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    ExecuteWorkload(*workload, memoryManager);
-
-    CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
-
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 2> FullyConnectedTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        bool biasEnabled)
-{
-    constexpr static unsigned int inputWidth = 3u;
-    constexpr static unsigned int inputHeight = 2u;
-    constexpr static unsigned int inputChannels = 1u;
-
-    constexpr static unsigned int inputSize = inputWidth * inputHeight * inputChannels;
-
-    constexpr static unsigned int outputChannels = 2u;
-
-    armnn::TensorInfo inputTensorInfo({ 1, inputChannels, inputHeight, inputWidth }, ArmnnType);
-    inputTensorInfo.SetQuantizationScale(0.1f);
-    inputTensorInfo.SetQuantizationOffset(63);
-
-    armnn::TensorInfo outputTensorInfo({ 1, outputChannels }, ArmnnType);
-    outputTensorInfo.SetQuantizationScale(5.f);
-    outputTensorInfo.SetQuantizationOffset(biasEnabled ? -50 : 10);
-
-    armnn::TensorInfo weightsDesc({ outputChannels, inputSize }, ArmnnType);
-    weightsDesc.SetQuantizationScale(0.2f);
-    weightsDesc.SetQuantizationOffset(93);
-
-    armnn::TensorInfo biasesDesc({ outputChannels }, GetBiasTypeFromWeightsType(weightsDesc.GetDataType()).value());
-    biasesDesc.SetQuantizationScale(inputTensorInfo.GetQuantizationScale() * weightsDesc.GetQuantizationScale());
-    biasesDesc.SetQuantizationOffset(0);
-
-    LayerTestResult<T, 2> result(outputTensorInfo);
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, ConvertToDataType<ArmnnType>(
-        {
-            -1.2f, 6.1f, -3.5f,
-            18.8f, -5.5f, 2.9f
-        },
-        inputTensorInfo));
-
-    auto weights = MakeTensor<T, 2>(weightsDesc, ConvertToDataType<ArmnnType>(
-        {
-            -8.4f, 20.0f, -10.4f, -8, 16.4f, -11.8f,
-            23.4f, 10.4f, -14.0f, -3.8f, -11.8f, 11.4f
-        },
-        weightsDesc));
-
-    auto bias = MakeTensor<int32_t, 1>(biasesDesc, std::vector<int32_t>{9250, 67500});
-
-    result = SimpleFullyConnectedTestImpl<T>(
-            workloadFactory,
-            memoryManager,
-            inputTensorInfo, outputTensorInfo,
-            weightsDesc, biasesDesc,
-            weights, bias, input,
-            biasEnabled, true
-    );
-
-    if (biasEnabled)
-    {
-        result.outputExpected = MakeTensor<T, 2>(outputTensorInfo,
-                                                 ConvertToDataType<ArmnnType>({80.f, 1460.f}, outputTensorInfo));
-    }
-    else
-    {
-        result.outputExpected = MakeTensor<T, 2>(outputTensorInfo,
-                                                 ConvertToDataType<ArmnnType>({-107.04f, 110.f}, outputTensorInfo));
-    }
-
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 2> Rsqrt2dTestCommon(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::TensorInfo inputTensorInfo,
-        const armnn::TensorInfo outputTensorInfo,
-        const std::vector<float>& inputValues,
-        const std::vector<float>& expectedOutputValues)
-{
-    auto inputTensor = MakeTensor<T, 2>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputValues,inputTensorInfo));
-
-    LayerTestResult<T, 2> result(outputTensorInfo);
-
-    result.outputExpected = MakeTensor<T, 2>(outputTensorInfo,
-                                             ConvertToDataType<ArmnnType>(expectedOutputValues,outputTensorInfo));
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::RsqrtQueueDescriptor descriptor;
-
-    armnn::WorkloadInfo info;
-
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateRsqrt(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-
-    CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get());
-
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 2> Rsqrt2dTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const armnn::TensorShape inputShape{ 2, 2 };
-    const armnn::TensorShape outputShape{ 2, 2 };
-
-    armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
-    inputTensorInfo.SetQuantizationScale(0.1f);
-    inputTensorInfo.SetQuantizationOffset(0);
-
-    armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType);
-    outputTensorInfo.SetQuantizationScale(0.1f);
-    outputTensorInfo.SetQuantizationOffset(0);
-
-    std::vector<float> inputValues
-    {
-        1.f, 4.f,
-        16.f, 25.f
-    };
-
-    std::vector<float> expectedOutputValues
-    {
-        1.f, 0.5f,
-        0.25f, 0.2f
-    };
-
-    return Rsqrt2dTestCommon<ArmnnType>(workloadFactory, memoryManager,
-                                inputTensorInfo, outputTensorInfo,
-                                inputValues, expectedOutputValues);
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 3> Rsqrt3dTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const armnn::TensorShape inputShape{ 3, 1, 2 };
-    const armnn::TensorShape outputShape{ 3, 1, 2 };
-
-    armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
-    inputTensorInfo.SetQuantizationScale(0.1f);
-    inputTensorInfo.SetQuantizationOffset(0);
-
-    armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType);
-    outputTensorInfo.SetQuantizationScale(0.1f);
-    outputTensorInfo.SetQuantizationOffset(0);
-
-    std::vector<float> inputValues
-    {
-        1.f, 4.f, 16.f,
-        25.f, 64.f, 100.f
-    };
-
-    std::vector<float> expectedOutputValues
-    {
-        1.f, 0.5f, 0.25f,
-        0.2f, 0.125f, 0.1f
-    };
-
-    auto inputTensor = MakeTensor<T, 3>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputValues,inputTensorInfo));
-
-    LayerTestResult<T, 3> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, 3>(outputTensorInfo,
-                                             ConvertToDataType<ArmnnType>(expectedOutputValues,outputTensorInfo));
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::RsqrtQueueDescriptor descriptor;
-
-    armnn::WorkloadInfo info;
-
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateRsqrt(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-
-    CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0], outputHandle.get());
-
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 2> RsqrtZeroTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const armnn::TensorShape inputShape{ 1, 2 };
-    const armnn::TensorShape outputShape{ 1, 2 };
-
-    armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
-    inputTensorInfo.SetQuantizationScale(0.1f);
-
-    armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType);
-    outputTensorInfo.SetQuantizationScale(0.1f);
-
-    std::vector<float> inputValues
-    {
-        0.f, -0.f
-    };
-
-    std::vector<float> expectedOutputValues
-    {
-        INFINITY, -INFINITY
-    };
-
-    return Rsqrt2dTestCommon<ArmnnType>(workloadFactory, memoryManager,
-                                inputTensorInfo, outputTensorInfo,
-                                inputValues, expectedOutputValues);
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 2> RsqrtNegativeTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const armnn::TensorShape inputShape{ 1, 2 };
-    const armnn::TensorShape outputShape{ 1, 2 };
-
-    armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType);
-    inputTensorInfo.SetQuantizationScale(0.1f);
-    inputTensorInfo.SetQuantizationOffset(0);
-
-    armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType);
-    outputTensorInfo.SetQuantizationScale(0.1f);
-    outputTensorInfo.SetQuantizationOffset(0);
-
-    std::vector<float> inputValues
-    {
-        -25.f, -16.f
-    };
-
-    std::vector<float> expectedOutputValues
-    {
-        -NAN, -NAN
-    };
-
-    return Rsqrt2dTestCommon<ArmnnType>(workloadFactory, memoryManager,
-                                inputTensorInfo, outputTensorInfo,
-                                inputValues, expectedOutputValues);
-}
-
-template<typename T, size_t NumDims>
-LayerTestResult<T, NumDims> SimpleReshapeTestImpl(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-    armnn::TensorInfo inputTensorInfo,
-    armnn::TensorInfo outputTensorInfo,
-    const std::vector<T>& inputData,
-    const std::vector<T>& outputExpectedData)
-{
-    auto input = MakeTensor<T, NumDims>(inputTensorInfo, inputData);
-
-    LayerTestResult<T, NumDims> ret(outputTensorInfo);
-    ret.outputExpected = MakeTensor<T, NumDims>(outputTensorInfo, outputExpectedData);
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::ReshapeQueueDescriptor data;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateReshape(data, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-
-    CopyDataToITensorHandle(inputHandle.get(), input.origin());
-
-    workload->Execute();
-
-    CopyDataFromITensorHandle(ret.output.origin(), outputHandle.get());
-
-    return ret;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> SimpleReshapeTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo;
-    armnn::TensorInfo outputTensorInfo;
-
-    unsigned int inputShape[] = { 2, 2, 3, 3 };
-    unsigned int outputShape[] = { 2, 2, 9, 1 };
-
-    inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
-    inputTensorInfo.SetQuantizationScale(1.0f);
-    outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
-    outputTensorInfo.SetQuantizationScale(1.0f);
-
-    auto input = ConvertToDataType<ArmnnType>(
-        {
-            0.0f, 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, 28.0f, 29.0f,
-            30.0f, 31.0f, 32.0f,
-            33.0f, 34.0f, 35.0f,
-        },
-        inputTensorInfo);
-
-    auto outputExpected = ConvertToDataType<ArmnnType>(
-        {
-            0.0f, 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, 28.0f, 29.0f, 30.0f, 31.0f, 32.0f, 33.0f, 34.0f, 35.0f,
-        },
-        outputTensorInfo);
-
-    return SimpleReshapeTestImpl<T, 4>(
-        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected);
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 5> Reshape5dTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo;
-    armnn::TensorInfo outputTensorInfo;
-
-    unsigned int inputShape[] = { 2, 2, 8, 1, 1 };
-    unsigned int outputShape[] = { 2, 2, 2, 2, 2 };
-
-    inputTensorInfo = armnn::TensorInfo(5, inputShape, ArmnnType);
-    inputTensorInfo.SetQuantizationScale(1.0f);
-    outputTensorInfo = armnn::TensorInfo(5, outputShape, ArmnnType);
-    outputTensorInfo.SetQuantizationScale(1.0f);
-
-    auto input = ConvertToDataType<ArmnnType>(
-        {
-            0.0f, 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, 28.0f, 29.0f, 30.0f, 31.0f,
-        },
-        inputTensorInfo);
-
-    auto outputExpected = ConvertToDataType<ArmnnType>(
-        {
-            0.0f, 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,
-
-            28.0f, 29.0f,
-            30.0f, 31.0f,
-        },
-        outputTensorInfo);
-
-    return SimpleReshapeTestImpl<T, 5>(
-        workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> SimpleFloorTest(
-    armnn::IWorkloadFactory& workloadFactory,
-    const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo({1, 3, 2, 3}, ArmnnType);
-    inputTensorInfo.SetQuantizationScale(0.1f);
-
-    armnn::TensorInfo outputTensorInfo(inputTensorInfo);
-    outputTensorInfo.SetQuantizationScale(0.1f);
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, ConvertToDataType<ArmnnType>(
-        { -37.5f, -15.2f, -8.76f, -2.0f, -1.5f, -1.3f, -0.5f, -0.4f, 0.0f,
-        1.0f, 0.4f, 0.5f, 1.3f, 1.5f, 2.0f, 8.76f, 15.2f, 37.5f },
-        inputTensorInfo));
-
-    LayerTestResult<T, 4> ret(outputTensorInfo);
-    ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, ConvertToDataType<ArmnnType>(
-        { -38.0f, -16.0f, -9.0f, -2.0f, -2.0f, -2.0f, -1.0f, -1.0f, 0.0f,
-        1.0f, 0.0f, 0.0f, 1.0f, 1.0f, 2.0f, 8.0f, 15.0f, 37.0f },
-        outputTensorInfo));
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::FloorQueueDescriptor data;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateFloor(data, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get());
-
-    return ret;
-}
-
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> ResizeBilinearNopTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout)
-{
-    armnn::TensorInfo inputTensorInfo = armnn::IsQuantizedType<T>()
-                                        ?  armnnUtils::GetTensorInfo(1, 1, 4, 4, dataLayout, ArmnnType)
-                                        :  armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType);
-    armnn::TensorInfo outputTensorInfo = armnn::IsQuantizedType<T>()
-                                         ?  armnnUtils::GetTensorInfo(1, 1, 4, 4, dataLayout, ArmnnType)
-                                         :  armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType);
-    if (armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(1.5f);
-        inputTensorInfo.SetQuantizationOffset(-3);
-        outputTensorInfo.SetQuantizationScale(1.5f);
-        outputTensorInfo.SetQuantizationOffset(-3);
-    }
-
-    std::vector<float> inputData = armnn::IsQuantizedType<T>()
-                                   ? std::initializer_list<float>
-                                     {
-                                             1, 2, 3, 4,
-                                             2, 3, 4, 5,
-                                             3, 4, 5, 6,
-                                             4, 5, 6, 7
-                                     }
-                                   : std::initializer_list<float>
-                                     {
-                                             1.0f, 2.0f, 3.0f, 4.0f,
-                                             2.0f, 3.0f, 4.0f, 5.0f,
-                                             3.0f, 4.0f, 5.0f, 6.0f,
-                                             4.0f, 5.0f, 6.0f, 7.0f,
-
-                                             1.0f, 2.0f, 3.0f, 4.0f,
-                                             2.0f, 3.0f, 4.0f, 5.0f,
-                                             3.0f, 4.0f, 5.0f, 6.0f,
-                                             4.0f, 5.0f, 6.0f, 7.0f
-                                     };
-
-    const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
-    if (dataLayout == armnn::DataLayout::NHWC)
-    {
-        std::vector<float> tmp(inputData.size());
-        armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float));
-        inputData = tmp;
-    }
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(),
-                                                                      inputTensorInfo.GetQuantizationOffset(),
-                                                                      inputData));
-
-    LayerTestResult<T, 4> result(outputTensorInfo);
-    result.outputExpected = input;
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::ResizeQueueDescriptor descriptor;
-    descriptor.m_Parameters.m_Method     = armnn::ResizeMethod::Bilinear;
-    descriptor.m_Parameters.m_DataLayout = dataLayout;
-
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResize(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> SimpleResizeBilinearTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout)
-{
-    armnn::TensorInfo inputTensorInfo = armnn::IsQuantizedType<T>()
-                                        ?  armnnUtils::GetTensorInfo(1, 1, 2, 2, dataLayout, ArmnnType)
-                                        :  armnnUtils::GetTensorInfo(1, 2, 2, 2, dataLayout, ArmnnType);
-    armnn::TensorInfo outputTensorInfo = armnn::IsQuantizedType<T>()
-                                         ?  armnnUtils::GetTensorInfo(1, 1, 1, 1, dataLayout, ArmnnType)
-                                         :  armnnUtils::GetTensorInfo(1, 2, 1, 1, dataLayout, ArmnnType);
-
-    if (armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(0.1567f);
-        inputTensorInfo.SetQuantizationOffset(1);
-        outputTensorInfo.SetQuantizationScale(0.1567f);
-        outputTensorInfo.SetQuantizationOffset(1);
-    }
-
-    std::vector<float> inputData = armnn::IsQuantizedType<T>()
-                                   ? std::initializer_list<float>
-                                     {
-                                             1, 255,
-                                             200, 250
-                                     }
-                                   : std::initializer_list<float>
-                                     {
-                                             1.0f, 255.0f,
-                                             200.0f, 250.0f,
-
-                                             250.0f, 200.0f,
-                                             250.0f,   1.0f
-                                     };
-
-    // The 'resize bilinear' operation projects the top-left corner of output texels into the input image,
-    // then figures out the interpolants and weights. Note this is different to projecting the centre of the
-    // output texel. Thus, for a input matrix of 2x2, we'll expect the output 1x1 matrix to contain, as
-    // its single element, the value that was at position (0,0) of the input matrix (rather than an average,
-    // which we would expect if projecting the centre).
-
-    std::vector<float> outputData = armnn::IsQuantizedType<T>()
-                                    ? std::initializer_list<float>
-                                      {
-                                              1
-                                      }
-                                    : std::initializer_list<float>
-                                      {
-                                              1.0f,
-
-                                              250.0f
-                                      };
-
-    const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
-    if (dataLayout == armnn::DataLayout::NHWC)
-    {
-        std::vector<float> tmp(inputData.size());
-        armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float));
-        inputData = tmp;
-
-        std::vector<float> tmp1(outputData.size());
-        armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float));
-        outputData = tmp1;
-    }
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(),
-                                                                      inputTensorInfo.GetQuantizationOffset(),
-                                                                      inputData));
-
-    LayerTestResult<T, 4> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, 4>(outputTensorInfo,
-                                             QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(),
-                                                                outputTensorInfo.GetQuantizationOffset(),
-                                                                outputData));
-
-    std::unique_ptr <armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr <armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::ResizeQueueDescriptor descriptor;
-    descriptor.m_Parameters.m_Method     = armnn::ResizeMethod::Bilinear;
-    descriptor.m_Parameters.m_DataLayout = dataLayout;
-
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResize(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> ResizeBilinearSqMinTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout)
-{
-    armnn::TensorInfo inputTensorInfo = armnn::IsQuantizedType<T>()
-                                        ?  armnnUtils::GetTensorInfo(1, 1, 4, 4, dataLayout, ArmnnType)
-                                        :  armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType);
-    armnn::TensorInfo outputTensorInfo = armnn::IsQuantizedType<T>()
-                                         ?  armnnUtils::GetTensorInfo(1, 1, 2, 2, dataLayout, ArmnnType)
-                                         :  armnnUtils::GetTensorInfo(1, 2, 2, 2, dataLayout, ArmnnType);
-
-    if (armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(3.141592f);
-        inputTensorInfo.SetQuantizationOffset(3);
-        outputTensorInfo.SetQuantizationScale(3.141592f);
-        outputTensorInfo.SetQuantizationOffset(3);
-    }
-
-        std::vector<float> inputData = armnn::IsQuantizedType<T>()
-                                       ? std::initializer_list<float>
-                                         {
-                                                1, 2, 3, 4,
-                                                2, 3, 4, 5,
-                                                3, 4, 5, 6,
-                                                4, 5, 6, 7
-                                         }
-                                       : std::initializer_list<float>
-                                         {
-                                                1.0f, 2.0f, 3.0f, 4.0f,
-                                                2.0f, 3.0f, 4.0f, 5.0f,
-                                                3.0f, 4.0f, 5.0f, 6.0f,
-                                                4.0f, 5.0f, 6.0f, 7.0f,
-
-                                                7.0f, 6.0f, 5.0f, 4.0f,
-                                                6.0f, 5.0f, 4.0f, 3.0f,
-                                                5.0f, 4.0f, 3.0f, 2.0f,
-                                                4.0f, 3.0f, 2.0f, 1.0f
-                                         };
-
-    std::vector<float> outputData = armnn::IsQuantizedType<T>()
-                                    ? std::initializer_list<float>
-                                      {
-                                              1, 3,
-                                              3, 5
-                                      }
-                                    : std::initializer_list<float>
-                                      {
-                                              1.0f, 3.0f,
-                                              3.0f, 5.0f,
-
-                                              7.0f, 5.0f,
-                                              5.0f, 3.0f
-                                      };
-
-    const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
-    if (dataLayout == armnn::DataLayout::NHWC)
-    {
-        std::vector<float> tmp(inputData.size());
-        armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float));
-        inputData = tmp;
-
-        std::vector<float> tmp1(outputData.size());
-        armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float));
-        outputData = tmp1;
-    }
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(),
-                                                                      inputTensorInfo.GetQuantizationOffset(),
-                                                                      inputData));
-
-    LayerTestResult<T, 4> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, 4>(outputTensorInfo,
-                                             QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(),
-                                                                outputTensorInfo.GetQuantizationOffset(),
-                                                                outputData));
-
-    std::unique_ptr <armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr <armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::ResizeQueueDescriptor descriptor;
-    descriptor.m_Parameters.m_Method     = armnn::ResizeMethod::Bilinear;
-    descriptor.m_Parameters.m_DataLayout = dataLayout;
-
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResize(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> ResizeBilinearMinTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout)
-{
-    armnn::TensorInfo inputTensorInfo = armnn::IsQuantizedType<T>()
-                                        ?  armnnUtils::GetTensorInfo(1, 1, 2, 3, dataLayout, ArmnnType)
-                                        :  armnnUtils::GetTensorInfo(1, 2, 3, 5, dataLayout, ArmnnType);
-    armnn::TensorInfo outputTensorInfo = armnn::IsQuantizedType<T>()
-                                         ?  armnnUtils::GetTensorInfo(1, 1, 1, 2, dataLayout, ArmnnType)
-                                         :  armnnUtils::GetTensorInfo(1, 2, 2, 3, dataLayout, ArmnnType);
-
-    if (armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(1.5f);
-        inputTensorInfo.SetQuantizationOffset(-1);
-        outputTensorInfo.SetQuantizationScale(1.5f);
-        outputTensorInfo.SetQuantizationOffset(-1);
-    }
-
-    std::vector<float> inputData = armnn::IsQuantizedType<T>()
-                                   ? std::initializer_list<float>
-                                     {
-                                             3.0f, 4.5f, 6.0f, // 1,  2,  3, : Expected quantised values
-                                             9.0f, 13.5f, 21.0f // 5,  8, 13
-                                     }
-                                   : std::initializer_list<float>
-                                     {
-                                             1.0f, 2.0f, 3.0f, 5.0f, 8.0f,
-                                             13.0f, 21.0f, 34.0f, 55.0f, 89.0f,
-                                             144.0f, 233.0f, 377.0f, 610.0f, 987.0f,
-
-                                             987.0f, 610.0f, 377.0f, 233.0f, 144.0f,
-                                             89.0f, 55.0f, 34.0f, 21.0f, 13.0f,
-                                             8.0f, 5.0f, 3.0f, 2.0f, 1.0f
-                                     };
-
-    std::vector<float> outputData = armnn::IsQuantizedType<T>()
-                                    ? std::initializer_list<float>
-                                      {
-                                              3.0f, 5.25f // 1, 3
-                                      }
-                                    : std::initializer_list<float>
-                                      {
-                                              1.0f,   2.6666f,   6.00f,
-                                              78.5f, 179.3333f, 401.00f,
-
-                                              987.0f, 454.6670f, 203.33f,
-                                              48.5f,  22.3333f,  10.00f
-                                      };
-
-    const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
-    if (dataLayout == armnn::DataLayout::NHWC)
-    {
-        std::vector<float> tmp(inputData.size());
-        armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float));
-        inputData = tmp;
-
-        std::vector<float> tmp1(outputData.size());
-        armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float));
-        outputData = tmp1;
-    }
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(),
-                                                                      inputTensorInfo.GetQuantizationOffset(),
-                                                                      inputData));
-
-    LayerTestResult<T, 4> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, 4>(outputTensorInfo,
-                                             QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(),
-                                                                outputTensorInfo.GetQuantizationOffset(),
-                                                                outputData));
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::ResizeQueueDescriptor descriptor;
-    descriptor.m_Parameters.m_Method     = armnn::ResizeMethod::Bilinear;
-    descriptor.m_Parameters.m_DataLayout = dataLayout;
-
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResize(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> ResizeBilinearMagTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout)
-{
-    armnn::TensorInfo inputTensorInfo = armnn::IsQuantizedType<T>()
-                                        ?  armnnUtils::GetTensorInfo(1, 1, 3, 2, dataLayout, ArmnnType)
-                                        :  armnnUtils::GetTensorInfo(1, 2, 3, 2, dataLayout, ArmnnType);
-    armnn::TensorInfo outputTensorInfo = armnn::IsQuantizedType<T>()
-                                         ?  armnnUtils::GetTensorInfo(1, 1, 3, 5, dataLayout, ArmnnType)
-                                         :  armnnUtils::GetTensorInfo(1, 2, 3, 5, dataLayout, ArmnnType);
-
-    if (armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(0.010765f);
-        inputTensorInfo.SetQuantizationOffset(7);
-        outputTensorInfo.SetQuantizationScale(0.010132f);
-        outputTensorInfo.SetQuantizationOffset(-18);
-    }
-
-    std::vector<float> inputData = armnn::IsQuantizedType<T>()
-                                   ? std::initializer_list<float>
-                                     {
-                                             0.183005f, 2.379065f, // 24, 228, : Expected quantised values
-                                             1.05497f, 1.302565f, // 105, 128,
-                                             2.400595f, 0.68896f // 230, 71
-                                     }
-                                   : std::initializer_list<float>
-                                     {
-                                             1.0f,   2.0f,
-                                             13.0f,  21.0f,
-                                             144.0f, 233.0f,
-
-                                             233.0f, 144.0f,
-                                             21.0f,  13.0f,
-                                             2.0f,   1.0f
-                                     };
-    std::vector<float> outputData = armnn::IsQuantizedType<T>()
-                                    ? std::initializer_list<float>
-                                      {
-                                              0.18300501f, 1.06142902f, 1.93985295f, 2.37906504f, 2.37906504f,
-                                              1.05497003f, 1.15400803f, 1.25304604f, 1.30256498f, 1.30256498f,
-                                              2.40059495f, 1.71594095f, 1.03128707f, 0.68896002f, 0.68896002f
-                                              // 0, 87, 173, 217, 217, : Expected quantised values
-                                              // 86, 96, 106, 111, 111,
-                                              // 219, 151, 84, 50, 50
-                                      }
-                                    : std::initializer_list<float>
-                                      {
-                                              1.0f,   1.4f,   1.8f,   2.0f,   2.0f,
-                                              13.0f,  16.2f,  19.4f,  21.0f,  21.0f,
-                                              144.0f, 179.6f, 215.2f, 233.0f, 233.0f,
-
-                                              233.0f, 197.4f, 161.8f, 144.0f, 144.0f,
-                                              21.0f,  17.8f,  14.6f,  13.0f,  13.0f,
-                                              2.0f,   1.6f,   1.2f,   1.0f,   1.0f
-                                      };
-
-    const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
-    if (dataLayout == armnn::DataLayout::NHWC)
-    {
-        std::vector<float> tmp(inputData.size());
-        armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float));
-        inputData = tmp;
-
-        std::vector<float> tmp1(outputData.size());
-        armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float));
-        outputData = tmp1;
-    }
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(),
-                                                                      inputTensorInfo.GetQuantizationOffset(),
-                                                                      inputData));
-
-    LayerTestResult<T, 4> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, 4>(outputTensorInfo,
-                                             QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(),
-                                                                outputTensorInfo.GetQuantizationOffset(),
-                                                                outputData));
-
-    std::unique_ptr <armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr <armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::ResizeQueueDescriptor descriptor;
-    descriptor.m_Parameters.m_Method     = armnn::ResizeMethod::Bilinear;
-    descriptor.m_Parameters.m_DataLayout = dataLayout;
-
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResize(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-    return result;
-}
-
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> ResizeNearestNeighborNopTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout)
-{
-    armnn::TensorInfo inputTensorInfo = armnn::IsQuantizedType<T>()
-                                        ?  armnnUtils::GetTensorInfo(1, 1, 4, 4, dataLayout, ArmnnType)
-                                        :  armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType);
-    armnn::TensorInfo outputTensorInfo = armnn::IsQuantizedType<T>()
-                                         ?  armnnUtils::GetTensorInfo(1, 1, 4, 4, dataLayout, ArmnnType)
-                                         :  armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType);
-    if (armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(1.5f);
-        inputTensorInfo.SetQuantizationOffset(-3);
-        outputTensorInfo.SetQuantizationScale(1.5f);
-        outputTensorInfo.SetQuantizationOffset(-3);
-    }
-
-    std::vector<float> inputData = armnn::IsQuantizedType<T>()
-                                   ? std::initializer_list<float>
-                                           {
-                                                   1, 2, 3, 4,
-                                                   2, 3, 4, 5,
-                                                   3, 4, 5, 6,
-                                                   4, 5, 6, 7
-                                           }
-                                   : std::initializer_list<float>
-                                           {
-                                                   1.0f, 2.0f, 3.0f, 4.0f,
-                                                   2.0f, 3.0f, 4.0f, 5.0f,
-                                                   3.0f, 4.0f, 5.0f, 6.0f,
-                                                   4.0f, 5.0f, 6.0f, 7.0f,
-
-                                                   1.0f, 2.0f, 3.0f, 4.0f,
-                                                   2.0f, 3.0f, 4.0f, 5.0f,
-                                                   3.0f, 4.0f, 5.0f, 6.0f,
-                                                   4.0f, 5.0f, 6.0f, 7.0f
-                                           };
-
-    const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
-    if (dataLayout == armnn::DataLayout::NHWC)
-    {
-        std::vector<float> tmp(inputData.size());
-        armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float));
-        inputData = tmp;
-    }
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(),
-                                                                      inputTensorInfo.GetQuantizationOffset(),
-                                                                      inputData));
-
-    LayerTestResult<T, 4> result(outputTensorInfo);
-    result.outputExpected = input;
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::ResizeQueueDescriptor descriptor;
-    descriptor.m_Parameters.m_Method = armnn::ResizeMethod::NearestNeighbor;
-    descriptor.m_Parameters.m_DataLayout = dataLayout;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResize(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> SimpleResizeNearestNeighborTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout)
-{
-    armnn::TensorInfo inputTensorInfo = armnn::IsQuantizedType<T>()
-                                        ?  armnnUtils::GetTensorInfo(1, 1, 2, 2, dataLayout, ArmnnType)
-                                        :  armnnUtils::GetTensorInfo(1, 2, 2, 2, dataLayout, ArmnnType);
-    armnn::TensorInfo outputTensorInfo = armnn::IsQuantizedType<T>()
-                                         ?  armnnUtils::GetTensorInfo(1, 1, 1, 1, dataLayout, ArmnnType)
-                                         :  armnnUtils::GetTensorInfo(1, 2, 1, 1, dataLayout, ArmnnType);
-
-    if (armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(0.1567f);
-        inputTensorInfo.SetQuantizationOffset(1);
-        outputTensorInfo.SetQuantizationScale(0.1567f);
-        outputTensorInfo.SetQuantizationOffset(1);
-    }
-
-    std::vector<float> inputData = armnn::IsQuantizedType<T>()
-                                   ? std::initializer_list<float>
-                                           {
-                                                   1, 255,
-                                                   200, 250
-                                           }
-                                   : std::initializer_list<float>
-                                           {
-                                                   1.0f, 255.0f,
-                                                   200.0f, 250.0f,
-
-                                                   250.0f, 200.0f,
-                                                   250.0f,   1.0f
-                                           };
-
-    // The 'resize' operation projects the top-left corner of output texels into the input image,
-    // then figures out the interpolants and weights. Note this is different to projecting the centre of the
-    // output texel. Thus, for a input matrix of 2x2, we'll expect the output 1x1 matrix to contain, as
-    // its single element, the value that was at position (0,0) of the input matrix (rather than an average,
-    // which we would expect if projecting the centre).
-
-    std::vector<float> outputData = armnn::IsQuantizedType<T>()
-                                    ? std::initializer_list<float>
-                                            {
-                                                    1
-                                            }
-                                    : std::initializer_list<float>
-                                            {
-                                                    1.0f,
-
-                                                    250.0f
-                                            };
-
-    const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
-    if (dataLayout == armnn::DataLayout::NHWC)
-    {
-        std::vector<float> tmp(inputData.size());
-        armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float));
-        inputData = tmp;
-
-        std::vector<float> tmp1(outputData.size());
-        armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float));
-        outputData = tmp1;
-    }
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(),
-                                                                      inputTensorInfo.GetQuantizationOffset(),
-                                                                      inputData));
-
-    LayerTestResult<T, 4> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, 4>(outputTensorInfo,
-                                             QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(),
-                                                                outputTensorInfo.GetQuantizationOffset(),
-                                                                outputData));
-
-    std::unique_ptr <armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr <armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::ResizeQueueDescriptor descriptor;
-    descriptor.m_Parameters.m_DataLayout = dataLayout;
-    descriptor.m_Parameters.m_Method = armnn::ResizeMethod::NearestNeighbor;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResize(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> ResizeNearestNeighborSqMinTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout)
-{
-    armnn::TensorInfo inputTensorInfo = armnn::IsQuantizedType<T>()
-                                        ?  armnnUtils::GetTensorInfo(1, 1, 4, 4, dataLayout, ArmnnType)
-                                        :  armnnUtils::GetTensorInfo(1, 2, 4, 4, dataLayout, ArmnnType);
-    armnn::TensorInfo outputTensorInfo = armnn::IsQuantizedType<T>()
-                                         ?  armnnUtils::GetTensorInfo(1, 1, 2, 2, dataLayout, ArmnnType)
-                                         :  armnnUtils::GetTensorInfo(1, 2, 2, 2, dataLayout, ArmnnType);
-
-    if (armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(3.141592f);
-        inputTensorInfo.SetQuantizationOffset(3);
-        outputTensorInfo.SetQuantizationScale(3.141592f);
-        outputTensorInfo.SetQuantizationOffset(3);
-    }
-
-    std::vector<float> inputData = armnn::IsQuantizedType<T>()
-                                   ? std::initializer_list<float>
-                                           {
-                                                  1, 2, 3, 4,
-                                                  2, 3, 4, 5,
-                                                  3, 4, 5, 6,
-                                                  4, 5, 6, 7
-                                           }
-                                   : std::initializer_list<float>
-                                           {
-                                                   1.0f, 2.0f, 3.0f, 4.0f,
-                                                   2.0f, 3.0f, 4.0f, 5.0f,
-                                                   3.0f, 4.0f, 5.0f, 6.0f,
-                                                   4.0f, 5.0f, 6.0f, 7.0f,
-
-                                                   7.0f, 6.0f, 5.0f, 4.0f,
-                                                   6.0f, 5.0f, 4.0f, 3.0f,
-                                                   5.0f, 4.0f, 3.0f, 2.0f,
-                                                   4.0f, 3.0f, 2.0f, 1.0f
-                                           };
-
-    std::vector<float> outputData = armnn::IsQuantizedType<T>()
-                                    ? std::initializer_list<float>
-                                            {
-                                                    1, 3,
-                                                    3, 5
-                                            }
-                                    : std::initializer_list<float>
-                                            {
-                                                    1.0f, 3.0f,
-                                                    3.0f, 5.0f,
-
-                                                    7.0f, 5.0f,
-                                                    5.0f, 3.0f
-                                            };
-
-    const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
-    if (dataLayout == armnn::DataLayout::NHWC)
-    {
-        std::vector<float> tmp(inputData.size());
-        armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float));
-        inputData = tmp;
-
-        std::vector<float> tmp1(outputData.size());
-        armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float));
-        outputData = tmp1;
-    }
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(),
-                                                                      inputTensorInfo.GetQuantizationOffset(),
-                                                                      inputData));
-
-    LayerTestResult<T, 4> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, 4>(outputTensorInfo,
-                                             QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(),
-                                                                outputTensorInfo.GetQuantizationOffset(),
-                                                                outputData));
-
-    std::unique_ptr <armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr <armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::ResizeQueueDescriptor descriptor;
-    descriptor.m_Parameters.m_DataLayout = dataLayout;
-    descriptor.m_Parameters.m_Method = armnn::ResizeMethod::NearestNeighbor;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResize(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> ResizeNearestNeighborMinTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout)
-{
-    armnn::TensorInfo inputTensorInfo = armnn::IsQuantizedType<T>()
-                                        ?  armnnUtils::GetTensorInfo(1, 1, 2, 3, dataLayout, ArmnnType)
-                                        :  armnnUtils::GetTensorInfo(1, 2, 3, 5, dataLayout, ArmnnType);
-    armnn::TensorInfo outputTensorInfo = armnn::IsQuantizedType<T>()
-                                         ?  armnnUtils::GetTensorInfo(1, 1, 1, 2, dataLayout, ArmnnType)
-                                         :  armnnUtils::GetTensorInfo(1, 2, 2, 3, dataLayout, ArmnnType);
-
-    if (armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(1.5f);
-        inputTensorInfo.SetQuantizationOffset(-1);
-        outputTensorInfo.SetQuantizationScale(1.5f);
-        outputTensorInfo.SetQuantizationOffset(-1);
-    }
-
-    std::vector<float> inputData = armnn::IsQuantizedType<T>()
-                                   ? std::initializer_list<float>
-                                           {
-                                                   3.0f, 4.5f, 6.0f, // 1,  2,  3, : Expected quantised values
-                                                   9.0f, 13.5f, 21.0f // 5,  8, 13
-                                           }
-                                   : std::initializer_list<float>
-                                           {
-                                                   1.0f, 2.0f, 3.0f, 5.0f, 8.0f,
-                                                   13.0f, 21.0f, 34.0f, 55.0f, 89.0f,
-                                                   144.0f, 233.0f, 377.0f, 610.0f, 987.0f,
-
-                                                   987.0f, 610.0f, 377.0f, 233.0f, 144.0f,
-                                                   89.0f, 55.0f, 34.0f, 21.0f, 13.0f,
-                                                   8.0f, 5.0f, 3.0f, 2.0f, 1.0f
-                                           };
-
-    std::vector<float> outputData = armnn::IsQuantizedType<T>()
-                                    ? std::initializer_list<float>
-                                            {
-                                                    3.0f, 4.5f // 1, 3
-                                            }
-                                    : std::initializer_list<float>
-                                            {
-                                                    1.f,   2.f,   5.f,
-                                                   13.f,  21.f,  55.f,
-
-                                                  987.f, 610.f, 233.f,
-                                                   89.f,  55.f,  21.f
-                                            };
-
-    const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
-    if (dataLayout == armnn::DataLayout::NHWC)
-    {
-        std::vector<float> tmp(inputData.size());
-        armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float));
-        inputData = tmp;
-
-        std::vector<float> tmp1(outputData.size());
-        armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float));
-        outputData = tmp1;
-    }
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(),
-                                                                      inputTensorInfo.GetQuantizationOffset(),
-                                                                      inputData));
-
-    LayerTestResult<T, 4> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, 4>(outputTensorInfo,
-                                             QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(),
-                                                                outputTensorInfo.GetQuantizationOffset(),
-                                                                outputData));
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::ResizeQueueDescriptor descriptor;
-    descriptor.m_Parameters.m_DataLayout = dataLayout;
-    descriptor.m_Parameters.m_Method = armnn::ResizeMethod::NearestNeighbor;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResize(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> ResizeNearestNeighborMagTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout dataLayout,
-        float inQuantScale,
-        int32_t inQuantOffset,
-        float outQuantScale,
-        int32_t outQuantOffset)
-{
-    armnn::TensorInfo inputTensorInfo = armnn::IsQuantizedType<T>()
-                                        ?  armnnUtils::GetTensorInfo(1, 1, 3, 2, dataLayout, ArmnnType)
-                                        :  armnnUtils::GetTensorInfo(1, 2, 3, 2, dataLayout, ArmnnType);
-    armnn::TensorInfo outputTensorInfo = armnn::IsQuantizedType<T>()
-                                         ?  armnnUtils::GetTensorInfo(1, 1, 3, 5, dataLayout, ArmnnType)
-                                         :  armnnUtils::GetTensorInfo(1, 2, 3, 5, dataLayout, ArmnnType);
-
-    if (armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(inQuantScale);
-        inputTensorInfo.SetQuantizationOffset(inQuantOffset);
-        outputTensorInfo.SetQuantizationScale(outQuantScale);
-        outputTensorInfo.SetQuantizationOffset(outQuantOffset);
-    }
-
-    std::vector<float> inputData = armnn::IsQuantizedType<T>()
-                                   ? std::initializer_list<float>
-                                        {
-                                            0.183005f, 2.379065f, //  24, 228, : expected quantised values
-                                            1.054970f, 1.302565f, // 105, 128,
-                                            2.400595f, 0.688960f  // 230, 71
-                                        }
-                                   : std::initializer_list<float>
-                                        {
-                                               1.0f,   2.0f,
-                                              13.0f,  21.0f,
-                                            144.0f, 233.0f,
-
-                                            233.0f, 144.0f,
-                                             21.0f,  13.0f,
-                                              2.0f,   1.0f
-                                        };
-    std::vector<float> outputData = armnn::IsQuantizedType<T>()
-                                    ? std::initializer_list<float>
-                                        {
-                                            0.183005f, 0.183005f, 0.183005f, 2.379065f, 2.379065f,
-                                            1.054970f, 1.054970f, 1.054970f, 1.302565f, 1.302565f,
-                                            2.400595f, 2.400595f, 2.400595f, 0.688960f, 0.688960f
-                                        }
-                                    : std::initializer_list<float>
-                                        {
-                                              1.f,   1.f,   1.f,   2.f,   2.f,
-                                             13.f,  13.f,  13.f,  21.f,  21.f,
-                                            144.f, 144.f, 144.f, 233.f, 233.f,
-
-                                            233.f, 233.f, 233.f, 144.f, 144.f,
-                                             21.f,  21.f,  21.f,  13.f,  13.f,
-                                              2.f,   2.f,   2.f,   1.f,   1.f
-                                        };
-
-    const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
-    if (dataLayout == armnn::DataLayout::NHWC)
-    {
-        std::vector<float> tmp(inputData.size());
-        armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data(), sizeof(float));
-        inputData = tmp;
-
-        std::vector<float> tmp1(outputData.size());
-        armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp1.data(), sizeof(float));
-        outputData = tmp1;
-    }
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(),
-                                                                      inputTensorInfo.GetQuantizationOffset(),
-                                                                      inputData));
-
-    LayerTestResult<T, 4> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, 4>(outputTensorInfo,
-                                             QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(),
-                                                                outputTensorInfo.GetQuantizationOffset(),
-                                                                outputData));
-
-    std::unique_ptr <armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr <armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::ResizeQueueDescriptor descriptor;
-    descriptor.m_Parameters.m_DataLayout = dataLayout;
-    descriptor.m_Parameters.m_Method = armnn::ResizeMethod::NearestNeighbor;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateResize(descriptor, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T, std::size_t InputDim, std::size_t OutputDim>
-LayerTestResult<T, OutputDim> MeanTestHelper(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const unsigned int* inputShape,
-        const std::vector<float>& inputData,
-        const std::vector<unsigned int>& axis,
-        bool keepDims,
-        const unsigned int* outputShape,
-        const std::vector<float>& outputData,
-        float scale = 1.0f,
-        int32_t offset = 0)
-{
-    armnn::TensorInfo inputTensorInfo(InputDim, inputShape, ArmnnType);
-    armnn::TensorInfo outputTensorInfo(OutputDim, outputShape, ArmnnType);
-
-    inputTensorInfo.SetQuantizationScale(scale);
-    inputTensorInfo.SetQuantizationOffset(offset);
-
-    outputTensorInfo.SetQuantizationScale(scale);
-    outputTensorInfo.SetQuantizationOffset(offset);
-
-    auto input = MakeTensor<T, InputDim>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputData, inputTensorInfo));
-
-    LayerTestResult<T, OutputDim> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, OutputDim>(
-            outputTensorInfo, ConvertToDataType<ArmnnType>(outputData, outputTensorInfo));
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::MeanQueueDescriptor data;
-    data.m_Parameters.m_Axis = axis;
-    data.m_Parameters.m_KeepDims = keepDims;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(data,  info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateMean(data, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-
-    CopyDataToITensorHandle(inputHandle.get(), input.origin());
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(result.output.origin(), outputHandle.get());
-
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 1> MeanSimpleTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = { 3, 2 };
-    const unsigned int outputShape[] = { 1 };
-
-    std::vector<float> input({ 1.5f, 1.5f, 2.5f, 2.5f, 3.5f, 3.5f });
-    std::vector<float> output({ 2.5f });
-
-    return MeanTestHelper<ArmnnType, T, 2, 1>(
-            workloadFactory, memoryManager, inputShape, input, {}, false, outputShape, output);
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 3> MeanSimpleAxisTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = { 2, 3, 1, 2 };
-    const unsigned int outputShape[] = { 3, 1, 2 };
-
-    std::vector<float> input({ 1.5f, 2.5f, 3.5f, 4.5f, 5.5f, 6.5f, 1.5f, 2.5f, 3.5f, 4.5f, 5.5f, 6.5f });
-    std::vector<float> output({ 1.5f, 2.5f, 3.5f, 4.5f, 5.5f, 6.5f });
-
-    return MeanTestHelper<ArmnnType, T, 4, 3>(
-            workloadFactory, memoryManager, inputShape, input, { 0 }, false, outputShape, output);
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> MeanKeepDimsTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = { 1, 1, 3, 2 };
-    const unsigned int outputShape[] = { 1, 1, 1, 2 };
-
-    std::vector<float> input({ 1.5f, 1.5f, 2.5f, 2.5f, 3.5f, 3.5f });
-    std::vector<float> output({ 2.5f, 2.5f });
-
-    return MeanTestHelper<ArmnnType, T, 4, 4>(
-            workloadFactory, memoryManager, inputShape, input, { 2 }, true, outputShape, output);
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 4> MeanMultipleDimsTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = { 2, 3, 1, 2 };
-    const unsigned int outputShape[] = { 1, 3, 1, 1 };
-
-    std::vector<float> input({ 1.5f, 2.5f, 3.5f, 4.5f, 5.5f, 6.5f, 1.5f, 2.5f, 3.5f, 4.5f, 5.5f, 6.5 });
-    std::vector<float> output({ 2.0f, 4.0f, 6.0f });
-
-    return MeanTestHelper<ArmnnType, T, 4, 4>(
-            workloadFactory, memoryManager, inputShape, input, { 0, 3 }, true, outputShape, output);
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 1> MeanVts1Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = { 4, 3, 2 };
-    const unsigned int outputShape[] = { 2 };
-
-    std::vector<float> input({ 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 });
-    std::vector<float> output({ 12.0f, 13.0f });
-
-    return MeanTestHelper<ArmnnType, T, 3, 1>(
-            workloadFactory, memoryManager, inputShape, input, { 0, 1 }, false, outputShape, output);
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 3> MeanVts2Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = { 4, 3, 2 };
-    const unsigned int outputShape[] = { 1, 3, 1 };
-
-    std::vector<float> input({ 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 });
-    std::vector<float> output({ 10.5f, 12.5f, 14.5f });
-
-    return MeanTestHelper<ArmnnType, T, 3, 3>(
-            workloadFactory, memoryManager, inputShape, input, { 0, 2 }, true, outputShape, output);
-}
-
-template<armnn::DataType ArmnnType, typename T>
-LayerTestResult<T, 3> MeanVts3Test(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = { 1, 2, 2, 1 };
-    const unsigned int outputShape[] = { 1, 2, 1 };
-
-    std::vector<float> input({ 1.0f, 2.0f, 3.0f, 4.0f });
-    std::vector<float> output({ 1.5f, 3.5f });
-
-    return MeanTestHelper<ArmnnType, T, 4, 3>(
-            workloadFactory, memoryManager, inputShape, input, { 2 }, false, outputShape, output);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 3> ConcatDifferentInputOutputQParamTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        bool useSubtensor)
-{
-    // Defines the tensor descriptors.
-    armnn::TensorInfo outputTensorInfo({ 3, 6, 3 }, ArmnnType);
-    armnn::TensorInfo inputTensorInfo1({ 3, 6, 2 }, ArmnnType);
-    armnn::TensorInfo inputTensorInfo2({ 3, 6, 1 }, ArmnnType);
-
-    std::vector<armnn::TensorShape> inputTensorShapes({inputTensorInfo1.GetShape(), inputTensorInfo2.GetShape()});
-
-    // Quantized input1 tensor.
-    const float inputScale1 = 0.5f;
-    const int32_t inputOffset1 = 5;
-
-    auto input1 = MakeTensor<T, 3>(inputTensorInfo1, std::vector<T>(
-    {
-        1, 2, 3,
-        4, 5, 6,
-        7, 8, 9,
-        10, 11, 12,
-        13, 14, 15,
-        16, 17, 18,
-
-        19, 20, 21,
-        22, 23, 24,
-        25, 26, 27,
-        28, 29, 30,
-        31, 32, 33,
-        34, 35, 36
-    }));
-
-    // Quatized input2 tensor.
-    const float inputScale2 = 0.2f;
-    const int32_t inputOffset2 = 10;
-
-    auto input2 = MakeTensor<T, 3>(inputTensorInfo2, std::vector<T>(
-    {
-        37, 38, 39,
-        40, 41, 42,
-        43, 44, 45,
-        46, 47, 48,
-        49, 50, 51,
-        52, 53, 54
-    }));
-
-    // Quantized output tensor.
-    const float outputScale = 0.1f;
-    const int32_t outputOffset = 20;
-
-    LayerTestResult<T, 3> ret(outputTensorInfo);
-
-    ret.outputExpected = MakeTensor<T, 3>(outputTensorInfo, std::vector<T>(
-    {
-        0,   5,  74,
-        10,  15,  76,
-        20,  25,  78,
-        30,  35,  80,
-        40,  45,  82,
-        50,  55,  84,
-
-        60,  65,  86,
-        70,  75,  88,
-        80,  85,  90,
-        90,  95,  92,
-        100, 105,  94,
-        110, 115,  96,
-
-        120, 125,  98,
-        130, 135, 100,
-        140, 145, 102,
-        150, 155, 104,
-        160, 165, 106,
-        170, 175, 108
-    }));
-
-    outputTensorInfo.SetQuantizationScale(outputScale);
-    outputTensorInfo.SetQuantizationOffset(outputOffset);
-    inputTensorInfo1.SetQuantizationScale(inputScale1);
-    inputTensorInfo1.SetQuantizationOffset(inputOffset1);
-    inputTensorInfo2.SetQuantizationScale(inputScale2);
-    inputTensorInfo2.SetQuantizationOffset(inputOffset2);
-
-    std::vector<unsigned int> wOrigin1 = { 0, 0, 0 }; //Extent of the window is defined by size of input[0].
-    armnn::ConcatQueueDescriptor::ViewOrigin window1(wOrigin1);
-
-    std::vector<unsigned int> wOrigin2 = { 0, 0, 2 }; //Extent of the window is defined by size of input[1].
-    armnn::ConcatQueueDescriptor::ViewOrigin window2(wOrigin2);
-
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    bool subTensorsSupported = useSubtensor && workloadFactory.SupportsSubTensors();
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle1 =
-            subTensorsSupported ?
-            workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo1.GetShape(), wOrigin1.data()) :
-            workloadFactory.CreateTensorHandle(inputTensorInfo1);
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle2 =
-            subTensorsSupported ?
-            workloadFactory.CreateSubTensorHandle(*outputHandle, inputTensorInfo2.GetShape(), wOrigin2.data()) :
-            workloadFactory.CreateTensorHandle(inputTensorInfo2);
-
-    armnn::ConcatQueueDescriptor data;
-    armnn::OriginsDescriptor desc = armnn::CreateDescriptorForConcatenation(
-            inputTensorShapes.begin(),inputTensorShapes.end(), 2);
-    data.m_Parameters = desc;
-
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get());
-    AddInputToWorkload(data, info, inputTensorInfo2, inputHandle2.get());
-    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
-
-    data.m_ViewOrigins.push_back(window1);
-    data.m_ViewOrigins.push_back(window2);
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConcat(data, info);
-
-    inputHandle1->Allocate();
-    inputHandle2->Allocate();
-    outputHandle->Allocate();
-
-    CopyDataToITensorHandle(inputHandle1.get(), &input1[0][0][0]);
-    CopyDataToITensorHandle(inputHandle2.get(), &input2[0][0][0]);
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&ret.output[0][0][0], outputHandle.get());
-
-    return ret;
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> PreluTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo ({ 1, 2, 2, 3 }, ArmnnType);
-    armnn::TensorInfo alphaTensorInfo ({ 1, 1, 1, 3 }, ArmnnType);
-    armnn::TensorInfo outputTensorInfo({ 1, 2, 2, 3 }, ArmnnType);
-
-    if (armnn::IsQuantizedType<T>())
-    {
-        inputTensorInfo.SetQuantizationScale(0.25f);
-        inputTensorInfo.SetQuantizationOffset(128);
-        alphaTensorInfo.SetQuantizationScale(0.25f);
-        alphaTensorInfo.SetQuantizationOffset(50);
-        outputTensorInfo.SetQuantizationScale(0.5f);
-        outputTensorInfo.SetQuantizationOffset(120);
-    }
-
-    std::vector<float> inputData
-    {
-        // Expected quantized values:
-        // 128, 128, 128, 132, 132, 132, 124, 124, 124, 120, 120, 120
-        0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, -1.0f, -1.0f, -1.0f, -2.0f, -2.0f, -2.0f
-    };
-    std::vector<float> alphaData
-    {
-        // Expected quantized values:
-        // 50, 54, 58
-        0.0f, 1.0f, 2.0f
-    };
-    std::vector<float> outputExpectedData =
-    {
-        // Expected quantized values:
-        // 20, 120, 120, 122, 122, 122, 120, 118, 116, 120, 116, 112
-       0.0f, 0.0f, 0.0f, 1.0f, 1.0f, 1.0f, 0.0f, -1.0f, -2.0f, 0.0f, -2.0f, -4.0f
-    };
-
-    auto input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(inputTensorInfo.GetQuantizationScale(),
-                                                                      inputTensorInfo.GetQuantizationOffset(),
-                                                                      inputData));
-    auto alpha = MakeTensor<T, 4>(alphaTensorInfo, QuantizedVector<T>(alphaTensorInfo.GetQuantizationScale(),
-                                                                      alphaTensorInfo.GetQuantizationOffset(),
-                                                                      alphaData));
-
-    LayerTestResult<T, 4> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, 4>(outputTensorInfo,
-                                             QuantizedVector<T>(outputTensorInfo.GetQuantizationScale(),
-                                                                outputTensorInfo.GetQuantizationOffset(),
-                                                                outputExpectedData));
-
-    std::unique_ptr <armnn::ITensorHandle> inputHandle  = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr <armnn::ITensorHandle> alphaHandle  = workloadFactory.CreateTensorHandle(alphaTensorInfo);
-    std::unique_ptr <armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::PreluQueueDescriptor descriptor;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload (descriptor, info, inputTensorInfo,  inputHandle.get());
-    AddInputToWorkload (descriptor, info, alphaTensorInfo,  alphaHandle.get());
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreatePrelu(descriptor, info);
-
-    inputHandle->Allocate();
-    alphaHandle->Allocate();
-    outputHandle->Allocate();
-
-    CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
-    CopyDataToITensorHandle(alphaHandle.get(), &alpha[0][0][0][0]);
-
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-
-    return result;
-}
-
-template<armnn::DataType ArmnnType,
-        std::size_t InputDim,
-        std::size_t OutputDim,
-        typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, OutputDim> BatchToSpaceNdHelper(
-        armnn::IWorkloadFactory &workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::DataLayout& dataLayout,
-        const unsigned int *inputShape,
-        const std::vector<float> &inputData,
-        const std::vector<unsigned int> &blockShape,
-        const std::vector<std::pair<unsigned int, unsigned int>> &crops,
-        const unsigned int *outputShape,
-        const std::vector<float> &outputData,
-        float scale = 1.0f,
-        int32_t offset = 0)
-{
-    armnn::TensorInfo inputTensorInfo(InputDim, inputShape, ArmnnType);
-    armnn::TensorInfo outputTensorInfo(OutputDim, outputShape, ArmnnType);
-
-    inputTensorInfo.SetQuantizationScale(scale);
-    inputTensorInfo.SetQuantizationOffset(offset);
-
-    outputTensorInfo.SetQuantizationScale(scale);
-    outputTensorInfo.SetQuantizationOffset(offset);
-
-    auto input = MakeTensor<T, InputDim>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputData, inputTensorInfo));
-
-    LayerTestResult<T, OutputDim> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, OutputDim>(outputTensorInfo,
-                                                     ConvertToDataType<ArmnnType>(outputData, outputTensorInfo));
-
-    std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::BatchToSpaceNdQueueDescriptor data;
-    data.m_Parameters.m_DataLayout = dataLayout;
-    data.m_Parameters.m_BlockShape = blockShape;
-    data.m_Parameters.m_Crops = crops;
-    armnn::WorkloadInfo info;
-    AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
-    AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchToSpaceNd(data, info);
-
-    inputHandle->Allocate();
-    outputHandle->Allocate();
-
-    CopyDataToITensorHandle(inputHandle.get(), input.origin());
-
-    workload->PostAllocationConfigure();
-    workload->Execute();
-
-    CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
-
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNhwcTest1(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 2, 2, 1};
-    const unsigned int outputShape[] = {1, 4, 4, 1};
-
-    std::vector<float> input({
-                                     // Batch 0, Height 0, Width (2) x Channel (1)
-                                     1.0f, 3.0f,
-                                     // Batch 0, Height 1, Width (2) x Channel (1)
-                                     9.0f, 11.0f,
-
-
-                                     // Batch 1, Height 0, Width (2) x Channel (1)
-                                     2.0f, 4.0f,
-                                     // Batch 1, Height 1, Width (2) x Channel (1)
-                                     10.0f, 12.0f,
-
-
-                                     // Batch 2, Height 0, Width (2) x Channel (1)
-                                     5.0f, 7.0f,
-                                     // Batch 2, Height 1, Width (2) x Channel (1)
-                                     13.0f, 15.0f,
-
-                                     // Batch 3, Height 0, Width (2) x Channel (3)
-                                     6.0f, 8.0f,
-                                     // Batch 3, Height 1, Width (2) x Channel (1)
-                                     14.0f, 16.0f
-                             });
-
-    std::vector<float> expectedOutput({
-                                              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
-                                      });
-
-    std::vector<unsigned int> blockShape {2, 2};
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                                armnn::DataLayout::NHWC, inputShape, input, blockShape,
-                                                                crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNhwcTest2(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 1, 1, 1};
-    const unsigned int outputShape[] = {1, 2, 2, 1};
-
-    std::vector<float> input({
-                                     // Batch 0, Height 0, Width (2) x Channel (1)
-                                     1.0f, 2.0f, 3.0f, 4.0f
-                             });
-
-    std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f});
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                                armnn::DataLayout::NHWC, inputShape, input, blockShape,
-                                                                crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNhwcTest3(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 1, 1, 3};
-    const unsigned int outputShape[] = {1, 2, 2, 3};
-
-    std::vector<float> input({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f});
-
-    std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f});
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                                armnn::DataLayout::NHWC, inputShape, input, blockShape,
-                                                                crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNhwcTest4(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {8, 1, 3, 1};
-    const unsigned int outputShape[] = {2, 2, 4, 1};
-
-    std::vector<float> input({
-                                     0.0f, 1.0f, 3.0f,
-                                     0.0f, 9.0f, 11.0f,
-                                     0.0f, 2.0f, 4.0f,
-                                     0.0f, 10.0f, 12.0f,
-                                     0.0f, 5.0f, 7.0f,
-                                     0.0f, 13.0f, 15.0f,
-                                     0.0f, 6.0f, 8.0f,
-                                     0.0f, 14.0f, 16.0f
-                             });
-
-    std::vector<float> expectedOutput({
-                                              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
-                                      });
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {2, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                                armnn::DataLayout::NHWC, inputShape, input, blockShape,
-                                                                crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNhwcTest5(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 2, 2, 1};
-    const unsigned int outputShape[] = {1, 4, 4, 1};
-
-    std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16});
-    std::vector<float> expectedOutput({1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16});
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, armnn::DataLayout::NHWC, inputShape,
-                                                 input, blockShape, crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNhwcTest6(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 1, 1, 1};
-    const unsigned int outputShape[] = {1, 2, 2, 1};
-
-    std::vector<float> input({
-                                     // Batch 0, Height 0, Width (2) x Channel (1)
-                                     1, 2, 3, 4
-                             });
-
-    std::vector<float> expectedOutput({1, 2, 3, 4});
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                 armnn::DataLayout::NHWC, inputShape, input, blockShape,
-                                                 crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNhwcTest7(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 1, 1, 3};
-    const unsigned int outputShape[] = {1, 2, 2, 3};
-
-    std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
-
-    std::vector<float> expectedOutput({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                 armnn::DataLayout::NHWC, inputShape, input, blockShape,
-                                                 crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNchwTest1(
-        armnn::IWorkloadFactory &workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 3, 1, 1};
-    const unsigned int outputShape[] = {1, 3, 2, 2};
-
-    std::vector<float> input({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f});
-
-    std::vector<float> expectedOutput({
-                                              // Batch 0, Channel 0, Height (2) x Width (2)
-                                              1.0f,  4.0f,
-                                              7.0f, 10.0f,
-
-                                              // Batch 0, Channel 1, Height (2) x Width (2)
-                                              2.0f,  5.0f,
-                                              8.0f, 11.0f,
-
-                                              // Batch 0, Channel 2, Height (2) x Width (2)
-                                              3.0f,  6.0f,
-                                              9.0f, 12.0f,
-                                      });
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                                armnn::DataLayout::NCHW, inputShape, input, blockShape,
-                                                                crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNchwTest2(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 1, 1, 1};
-    const unsigned int outputShape[] = {1, 1, 2, 2};
-
-    std::vector<float> input({
-                                     // Batch 0, Height 0, Width (2) x Channel (1)
-                                     1.0f, 2.0f, 3.0f, 4.0f
-                             });
-
-    std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f});
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                                armnn::DataLayout::NCHW, inputShape, input, blockShape,
-                                                                crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNchwTest3(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 3, 1, 1};
-    const unsigned int outputShape[] = {1, 3, 2, 2};
-
-    std::vector<float> input({1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f});
-
-    std::vector<float> expectedOutput({
-                                              // Batch 0, Channel 0, Height (2) x Width (2)
-                                              1.0f,  7.0f,
-                                              2.0f,  8.0f,
-
-                                              // Batch 0, Channel 1, Height (2) x Width (2)
-                                              3.0f,  9.0f,
-                                              4.0f, 10.0f,
-
-                                              // Batch 0, Channel 2, Height (2) x Width (2)
-                                              5.0f, 11.0f,
-                                              6.0f, 12.0f,
-                                      });
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                                armnn::DataLayout::NCHW, inputShape, input, blockShape,
-                                                                crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNchwTest4(
-        armnn::IWorkloadFactory &workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 3, 1, 1};
-    const unsigned int outputShape[] = {1, 3, 2, 2};
-
-    std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
-
-    std::vector<float> expectedOutput({
-                                              // Batch 0, Channel 0, Height (2) x Width (2)
-                                              1,  4,
-                                              7, 10,
-
-                                              // Batch 0, Channel 1, Height (2) x Width (2)
-                                              2,  5,
-                                              8, 11,
-
-                                              // Batch 0, Channel 2, Height (2) x Width (2)
-                                              3,  6,
-                                              9, 12,
-                                      });
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                 armnn::DataLayout::NCHW, inputShape, input, blockShape,
-                                                 crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNchwTest5(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 1, 1, 1};
-    const unsigned int outputShape[] = {1, 1, 2, 2};
-
-    std::vector<float> input({
-                                     // Batch 0, Height 0, Width (2) x Channel (1)
-                                     1, 2, 3, 4
-                             });
-
-    std::vector<float> expectedOutput({1, 2, 3, 4});
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                 armnn::DataLayout::NCHW, inputShape, input, blockShape,
-                                                 crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNchwTest6(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {4, 3, 1, 1};
-    const unsigned int outputShape[] = {1, 3, 2, 2};
-
-    std::vector<float> input({1, 3, 5, 7, 9, 11, 2, 4, 6, 8, 10, 12});
-
-    std::vector<float> expectedOutput({
-                                              // Batch 0, Channel 0, Height (2) x Width (2)
-                                              1,  7,
-                                              2,  8,
-
-                                              // Batch 0, Channel 1, Height (2) x Width (2)
-                                              3,  9,
-                                              4, 10,
-
-                                              // Batch 0, Channel 2, Height (2) x Width (2)
-                                              5, 11,
-                                              6, 12,
-                                      });
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                 armnn::DataLayout::NCHW, inputShape, input, blockShape,
-                                                 crops, outputShape, expectedOutput);
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> BatchToSpaceNdNchwTest7(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    const unsigned int inputShape[] = {8, 1, 1, 3};
-    const unsigned int outputShape[] = {2, 1, 2, 4};
-
-    std::vector<float> input({
-                                     0, 1, 3, 0,  9, 11,
-                                     0, 2, 4, 0, 10, 12,
-                                     0, 5, 7, 0, 13, 15,
-                                     0, 6, 8, 0, 14, 16
-                             });
-
-    std::vector<float> expectedOutput({
-                                              1,  2,  3,  4,
-                                              5,  6,  7,  8,
-                                              9, 10, 11, 12,
-                                              13, 14, 15, 16
-                                      });
-
-    std::vector<unsigned int> blockShape({2, 2});
-    std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {2, 0}};
-
-    return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
-                                                 armnn::DataLayout::NCHW, inputShape, input, blockShape,
-                                                 crops, outputShape, expectedOutput);
-}
-
-template LayerTestResult<typename armnn::ResolveType<armnn::DataType::Float32>, 4>
-PreluTest<armnn::DataType::Float32>(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template LayerTestResult<typename armnn::ResolveType<armnn::DataType::QuantisedAsymm8>, 4>
-PreluTest<armnn::DataType::QuantisedAsymm8>(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template LayerTestResult<typename armnn::ResolveType<armnn::DataType::QuantisedSymm16>, 4>
-PreluTest<armnn::DataType::QuantisedSymm16>(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager);
-
-template<armnn::DataType ArmnnType, typename T, std::size_t outputDimLength>
-LayerTestResult<T, outputDimLength> StackTestHelper(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
-        const armnn::TensorInfo& inputTensorInfo,
-        const armnn::TensorInfo& outputTensorInfo,
-        unsigned int axis,
-        const std::vector<std::vector<T>>& inputData,
-        const std::vector<T>& outputExpectedData)
-{
-    unsigned int numInputs = static_cast<unsigned int>(inputData.size());
-    std::vector<boost::multi_array<T, outputDimLength-1>> inputs;
-    for (unsigned int i = 0; i < numInputs; ++i)
-    {
-        inputs.push_back(MakeTensor<T, outputDimLength-1>(inputTensorInfo, inputData[i]));
-    }
-
-    LayerTestResult<T, outputDimLength> result(outputTensorInfo);
-    result.outputExpected = MakeTensor<T, outputDimLength>(outputTensorInfo, outputExpectedData);
-
-    std::vector<std::unique_ptr<armnn::ITensorHandle>> inputHandles;
-    for (unsigned int i = 0; i < numInputs; ++i)
-    {
-        inputHandles.push_back(workloadFactory.CreateTensorHandle(inputTensorInfo));
-    }
-    std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
-
-    armnn::StackQueueDescriptor descriptor;
-    descriptor.m_Parameters.m_Axis = axis;
-    descriptor.m_Parameters.m_InputShape = inputTensorInfo.GetShape();
-    descriptor.m_Parameters.m_NumInputs = numInputs;
-
-    armnn::WorkloadInfo info;
-    for (unsigned int i = 0; i < numInputs; ++i)
-    {
-        std::unique_ptr<armnn::ITensorHandle>& inputHandle = inputHandles[i];
-        AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
-        inputHandle->Allocate();
-        CopyDataToITensorHandle(inputHandle.get(), inputs[i].origin());
-    }
-
-    AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
-    outputHandle->Allocate();
-
-    std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateStack(descriptor, info);
-
-    workload->Execute();
-
-    CopyDataFromITensorHandle(result.output.origin(), outputHandle.get());
-
-    return result;
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> Stack0AxisTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo ({ 3, 2, 3 }, ArmnnType);
-    armnn::TensorInfo outputTensorInfo({ 2, 3, 2, 3 }, ArmnnType);
-
-    std::vector<std::vector<T>> inputData;
-
-    inputData.push_back(
-    {
-        1, 2, 3,
-        4, 5, 6,
-
-        7, 8, 9,
-        10, 11, 12,
-
-        13, 14, 15,
-        16, 17, 18
-    });
-
-    inputData.push_back(
-    {
-        19, 20, 21,
-        22, 23, 24,
-
-        25, 26, 27,
-        28, 29, 30,
-
-        31, 32, 33,
-        34, 35, 36
-    });
-
-    std::vector<T> outputExpectedData =
-    {
-        1, 2, 3,
-        4, 5, 6,
-
-        7, 8, 9,
-        10, 11, 12,
-
-        13, 14, 15,
-        16, 17, 18,
-
-
-        19, 20, 21,
-        22, 23, 24,
-
-        25, 26, 27,
-        28, 29, 30,
-
-        31, 32, 33,
-        34, 35, 36
-    };
-
-    return StackTestHelper<ArmnnType, T, 4>(
-        workloadFactory,
-        memoryManager,
-        inputTensorInfo,
-        outputTensorInfo,
-        0U,
-        inputData,
-        outputExpectedData
-    );
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> Stack4dOutput1AxisTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo ({ 3, 2, 3 }, ArmnnType);
-    armnn::TensorInfo outputTensorInfo({ 3, 2, 2, 3 }, ArmnnType);
-
-    std::vector<std::vector<T>> inputData;
-
-    inputData.push_back(
-    {
-        1, 2, 3,
-        4, 5, 6,
-
-        7, 8, 9,
-        10, 11, 12,
-
-        13, 14, 15,
-        16, 17, 18
-    });
-
-    inputData.push_back(
-    {
-        19, 20, 21,
-        22, 23, 24,
-
-        25, 26, 27,
-        28, 29, 30,
-
-        31, 32, 33,
-        34, 35, 36
-    });
-
-    std::vector<T> outputExpectedData =
-    {
-        1, 2, 3,
-        4, 5, 6,
-
-        19, 20, 21,
-        22, 23, 24,
-
-
-        7, 8, 9,
-        10, 11, 12,
-
-        25, 26, 27,
-        28, 29, 30,
-
-
-        13, 14, 15,
-        16, 17, 18,
-
-        31, 32, 33,
-        34, 35, 36
-    };
-
-    return StackTestHelper<ArmnnType, T, 4>(
-        workloadFactory,
-        memoryManager,
-        inputTensorInfo,
-        outputTensorInfo,
-        1U,
-        inputData,
-        outputExpectedData
-    );
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> Stack4dOutput2AxisTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo ({ 3, 2, 3 }, ArmnnType);
-    armnn::TensorInfo outputTensorInfo({ 3, 2, 2, 3 }, ArmnnType);
-
-    std::vector<std::vector<T>> inputData;
-
-    inputData.push_back(
-    {
-        1, 2, 3,
-        4, 5, 6,
-
-        7, 8, 9,
-        10, 11, 12,
-
-        13, 14, 15,
-        16, 17, 18
-    });
-
-    inputData.push_back(
-    {
-        19, 20, 21,
-        22, 23, 24,
-
-        25, 26, 27,
-        28, 29, 30,
-
-        31, 32, 33,
-        34, 35, 36
-    });
-
-    std::vector<T> outputExpectedData =
-    {
-        1, 2, 3,
-        19, 20, 21,
-
-        4, 5, 6,
-        22, 23, 24,
-
-
-        7, 8, 9,
-        25, 26, 27,
-
-        10, 11, 12,
-        28, 29, 30,
-
-        13, 14, 15,
-        31, 32, 33,
-
-        16, 17, 18,
-        34, 35, 36
-    };
-
-    return StackTestHelper<ArmnnType, T, 4>(
-        workloadFactory,
-        memoryManager,
-        inputTensorInfo,
-        outputTensorInfo,
-        2U,
-        inputData,
-        outputExpectedData
-    );
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 4> Stack4dOutput3AxisTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo ({ 3, 2, 3 }, ArmnnType);
-    armnn::TensorInfo outputTensorInfo({ 3, 2, 3, 2 }, ArmnnType);
-
-    std::vector<std::vector<T>> inputData;
-
-    inputData.push_back(
-    {
-        1, 2, 3,
-        4, 5, 6,
-
-        7, 8, 9,
-        10, 11, 12,
-
-        13, 14, 15,
-        16, 17, 18
-    });
-
-    inputData.push_back(
-    {
-        19, 20, 21,
-        22, 23, 24,
-
-        25, 26, 27,
-        28, 29, 30,
-
-        31, 32, 33,
-        34, 35, 36
-    });
-
-    std::vector<T> outputExpectedData =
-    {
-        1, 19,
-        2, 20,
-        3, 21,
-
-        4, 22,
-        5, 23,
-        6, 24,
-
-
-        7, 25,
-        8, 26,
-        9, 27,
-
-        10, 28,
-        11, 29,
-        12, 30,
-
-
-        13, 31,
-        14, 32,
-        15, 33,
-
-        16, 34,
-        17, 35,
-        18, 36
-    };
-
-    return StackTestHelper<ArmnnType, T, 4>(
-        workloadFactory,
-        memoryManager,
-        inputTensorInfo,
-        outputTensorInfo,
-        3U,
-        inputData,
-        outputExpectedData
-    );
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 3> Stack3dOutput1Axis3InputTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo ({ 3, 3 }, ArmnnType);
-    armnn::TensorInfo outputTensorInfo({ 3, 3, 3 }, ArmnnType);
-
-    std::vector<std::vector<T>> inputData;
-
-    inputData.push_back(
-    {
-        1, 2, 3,
-        4, 5, 6,
-        7, 8, 9
-    });
-
-    inputData.push_back(
-    {
-        10, 11, 12,
-        13, 14, 15,
-        16, 17, 18
-    });
-
-    inputData.push_back(
-    {
-        19, 20, 21,
-        22, 23, 24,
-        25, 26, 27
-    });
-
-    std::vector<T> outputExpectedData =
-    {
-        1, 2, 3,
-        10, 11, 12,
-        19, 20, 21,
-
-        4, 5, 6,
-        13, 14, 15,
-        22, 23, 24,
-
-        7, 8, 9,
-        16, 17, 18,
-        25, 26, 27
-    };
-
-    return StackTestHelper<ArmnnType, T, 3>(
-        workloadFactory,
-        memoryManager,
-        inputTensorInfo,
-        outputTensorInfo,
-        1U,
-        inputData,
-        outputExpectedData
-    );
-}
-
-template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 5> Stack5dOutputTest(
-        armnn::IWorkloadFactory& workloadFactory,
-        const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
-{
-    armnn::TensorInfo inputTensorInfo ({ 2, 2, 2, 3 }, ArmnnType);
-    armnn::TensorInfo outputTensorInfo({ 2, 2, 2, 2, 3 }, ArmnnType);
-
-    std::vector<std::vector<T>> inputData;
-
-    inputData.push_back(
-    {
-        1, 2, 3,
-        4, 5, 6,
-
-        7, 8, 9,
-        10, 11, 12,
-
-
-        13, 14, 15,
-        16, 17, 18,
-
-        19, 20, 21,
-        22, 23, 24
-    });
-
-    inputData.push_back(
-    {
-        25, 26, 27,
-        28, 29, 30,
-
-        31, 32, 33,
-        34, 35, 36,
-
-
-        37, 38, 39,
-        40, 41, 42,
-
-        43, 44, 45,
-        46, 47, 48
-    });
-
-    std::vector<T> outputExpectedData =
-    {
-        1, 2, 3,
-        4, 5, 6,
-
-        7, 8, 9,
-        10, 11, 12,
-
-
-        25, 26, 27,
-        28, 29, 30,
-
-        31, 32, 33,
-        34, 35, 36,
-
-
-
-        13, 14, 15,
-        16, 17, 18,
-
-        19, 20, 21,
-        22, 23, 24,
-
-
-        37, 38, 39,
-        40, 41, 42,
-
-        43, 44, 45,
-        46, 47, 48
-
-    };
-
-    return StackTestHelper<ArmnnType, T, 5>(
-        workloadFactory,
-        memoryManager,
-        inputTensorInfo,
-        outputTensorInfo,
-        1U,
-        inputData,
-        outputExpectedData
-    );
-}
+#include <backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp>