IVGCVSW-6174 Add Cl Pooling3d Workload
* Add IsSupported for Pooling3d
* Add CreateWorkload case for Pooling3d
* Create new ClPooling3dWorkload header and source files
* Add Pooling3d workload to ClWorkloads.hpp
* Add tests for Pooling3d workload
* Add Pooling3d build function to ArmComputeTensorUtils
Change-Id: Ia270b0fe809a171ed73af14376de8708b346d500
Signed-off-by: Ryan OShea <ryan.oshea3@arm.com>
diff --git a/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.cpp
index a708afa..a241aea 100644
--- a/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.cpp
+++ b/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.cpp
@@ -29,6 +29,15 @@
using namespace armnnUtils;
+template<typename T>
+void PermuteNCDHWToNDHWC(std::vector<T> &src, armnn::TensorInfo &srcInfo)
+{
+ const armnn::PermutationVector NCDHWToNDHWC = { 0, 4, 1, 2, 3 };
+ std::vector<T> tmp(src.size());
+ armnnUtils::Permute(srcInfo.GetShape(), NCDHWToNDHWC, src.data(), tmp.data(), sizeof(T));
+ src = tmp;
+}
+
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 5> SimplePooling3dTestImpl(
armnn::IWorkloadFactory& workloadFactory,
@@ -137,6 +146,7 @@
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout,
float qScale = 1.0f,
int32_t qOffset = 0)
{
@@ -153,6 +163,7 @@
descriptor.m_PadFront = descriptor.m_PadBack = 0;
descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude;
+ descriptor.m_DataLayout = dataLayout;
unsigned int inputWidth = 3;
unsigned int inputHeight = 3;
@@ -169,8 +180,10 @@
unsigned int channels = 2;
unsigned int batchSize = 2;
- armnn::TensorInfo inputTensorInfo({ batchSize, channels, inputDepth, inputHeight, inputWidth }, ArmnnType);
- armnn::TensorInfo outputTensorInfo({ batchSize, channels, outputDepth, outputHeight, outputWidth }, ArmnnType);
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( batchSize, channels, inputDepth, inputHeight,
+ inputWidth, dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( batchSize, channels, outputDepth, outputHeight,
+ outputWidth, dataLayout, ArmnnType);
// Set quantization parameters if the requested type is a quantized type.
if(armnn::IsQuantizedType<T>())
@@ -239,6 +252,12 @@
},
qScale, qOffset);
+ if (dataLayout == armnn::DataLayout::NDHWC)
+ {
+ PermuteNCDHWToNDHWC(input, inputTensorInfo);
+ PermuteNCDHWToNDHWC(outputExpected, outputTensorInfo);
+ }
+
return SimplePooling3dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset,
input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape());
@@ -249,7 +268,7 @@
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::ITensorHandleFactory& tensorHandleFactory,
- const armnn::DataLayout dataLayout = armnn::DataLayout::NCDHW,
+ const armnn::DataLayout dataLayout,
float qScale = 1.0f,
int32_t qOffset = 0)
{
@@ -306,16 +325,10 @@
},
qScale, qOffset));
- const armnn::PermutationVector NCDHWToNDHWC = { 0, 4, 1, 2, 3 };
if (dataLayout == armnn::DataLayout::NDHWC)
{
- std::vector<T> tmp(inputData.size());
- armnnUtils::Permute(inputTensorInfo.GetShape(), NCDHWToNDHWC, inputData.data(), tmp.data(), sizeof(T));
- inputData = tmp;
-
- std::vector<T> tmp1(outputData.size());
- armnnUtils::Permute(outputTensorInfo.GetShape(), NCDHWToNDHWC, outputData.data(), tmp1.data(), sizeof(T));
- outputData = tmp1;
+ PermuteNCDHWToNDHWC(inputData, inputTensorInfo);
+ PermuteNCDHWToNDHWC(outputData, outputTensorInfo);
}
return SimplePooling3dTestImpl<ArmnnType>(
@@ -328,6 +341,7 @@
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout,
float qScale = 1.0f,
int32_t qOffset = 0)
{
@@ -342,9 +356,10 @@
descriptor.m_PadFront = 1;
descriptor.m_PadBack = 1;
descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue;
+ descriptor.m_DataLayout = dataLayout;
- armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4, 4 }, ArmnnType);
- armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3, 3 }, ArmnnType);
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 4, 4, 4 , dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 3, 3, 3 , dataLayout, ArmnnType);
// Set quantization parameters if the requested type is a quantized type.
if(armnn::IsQuantizedType<T>())
@@ -395,6 +410,12 @@
},
qScale, qOffset);
+ if (dataLayout == armnn::DataLayout::NDHWC)
+ {
+ PermuteNCDHWToNDHWC(input, inputTensorInfo);
+ PermuteNCDHWToNDHWC(outputExpected, outputTensorInfo);
+ }
+
return SimplePooling3dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset,
input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape());
@@ -462,16 +483,10 @@
},
qScale, qOffset));
- const armnn::PermutationVector NCDHWToNDHWC = { 0, 4, 1, 2, 3 };
if (dataLayout == armnn::DataLayout::NDHWC)
{
- std::vector<T> tmp(inputData.size());
- armnnUtils::Permute(inputTensorInfo.GetShape(), NCDHWToNDHWC, inputData.data(), tmp.data(), sizeof(T));
- inputData = tmp;
-
- std::vector<T> tmp1(outputData.size());
- armnnUtils::Permute(outputTensorInfo.GetShape(), NCDHWToNDHWC, outputData.data(), tmp1.data(), sizeof(T));
- outputData = tmp1;
+ PermuteNCDHWToNDHWC(inputData, inputTensorInfo);
+ PermuteNCDHWToNDHWC(outputData, outputTensorInfo);
}
return SimplePooling3dTestImpl<ArmnnType>(
@@ -484,6 +499,7 @@
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout,
float qScale = 1.0f,
int32_t qOffset = 0)
{
@@ -498,11 +514,12 @@
descriptor.m_PadFront = 50;
descriptor.m_PadBack = 50;
descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude;
+ descriptor.m_DataLayout = dataLayout;
- armnn::TensorInfo inputTensorInfo({ 5, 3, 52, 60, 68 }, ArmnnType);
- armnn::TensorInfo outputTensorInfo({ 5, 3, 11, 13, 15 }, ArmnnType);
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 5, 3, 52, 60, 68, dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 5, 3, 11, 13, 14, dataLayout, ArmnnType);
- // Set quantization parameters if the requested type is a quantized type.
+ // Set quantization parameters if the requested type is a quantized type.armnnUtils::GetTensorInfo(
if(armnn::IsQuantizedType<T>())
{
inputTensorInfo.SetQuantizationScale(qScale);
@@ -535,6 +552,7 @@
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout,
float qScale = 1.0f,
int32_t qOffset = 0)
{
@@ -549,9 +567,11 @@
descriptor.m_PadFront = 1;
descriptor.m_PadBack = 1;
descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue;
+ descriptor.m_DataLayout = dataLayout;
- armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4, 4 }, ArmnnType);
- armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3, 3 }, ArmnnType);
+
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo ( 1, 1, 4, 4, 4, dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 3, 3, 3, dataLayout, ArmnnType);
// Set quantization parameters if the requested type is a quantized type.
if(armnn::IsQuantizedType<T>())
@@ -602,6 +622,12 @@
},
qScale, qOffset);
+ if (dataLayout == armnn::DataLayout::NDHWC)
+ {
+ PermuteNCDHWToNDHWC(input, inputTensorInfo);
+ PermuteNCDHWToNDHWC(outputExpected, outputTensorInfo);
+ }
+
return SimplePooling3dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset,
input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape());
@@ -612,7 +638,7 @@
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::ITensorHandleFactory& tensorHandleFactory,
- armnn::DataLayout dataLayout = armnn::DataLayout::NCDHW,
+ const armnn::DataLayout dataLayout,
float qScale = 1.0f,
int32_t qOffset = 0)
{
@@ -669,16 +695,10 @@
},
qScale, qOffset));
- const armnn::PermutationVector NCDHWToNDHWC = { 0, 4, 1, 2, 3 };
if (dataLayout == armnn::DataLayout::NDHWC)
{
- std::vector<T> tmp(inputData.size());
- armnnUtils::Permute(inputTensorInfo.GetShape(), NCDHWToNDHWC, inputData.data(), tmp.data(), sizeof(T));
- inputData = tmp;
-
- std::vector<T> tmp1(outputData.size());
- armnnUtils::Permute(outputTensorInfo.GetShape(), NCDHWToNDHWC, outputData.data(), tmp1.data(), sizeof(T));
- outputData = tmp1;
+ PermuteNCDHWToNDHWC(inputData, inputTensorInfo);
+ PermuteNCDHWToNDHWC(outputData, outputTensorInfo);
}
return SimplePooling3dTestImpl<ArmnnType>(
@@ -691,6 +711,7 @@
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout,
float qScale = 1.0f,
int32_t qOffset = 0)
{
@@ -705,9 +726,10 @@
descriptor.m_PadFront = 1;
descriptor.m_PadBack = 1;
descriptor.m_PaddingMethod = armnn::PaddingMethod::IgnoreValue;
+ descriptor.m_DataLayout = dataLayout;
- armnn::TensorInfo inputTensorInfo({ 1, 1, 4, 4, 4 }, ArmnnType);
- armnn::TensorInfo outputTensorInfo({ 1, 1, 3, 3, 3 }, ArmnnType);
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 4, 4, 4, dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 3, 3, 3, dataLayout,ArmnnType);
// Set quantization parameters if the requested type is a quantized type.
if(armnn::IsQuantizedType<T>())
@@ -794,28 +816,129 @@
},
qScale, qOffset);
+ if (dataLayout == armnn::DataLayout::NDHWC)
+ {
+ PermuteNCDHWToNDHWC(input, inputTensorInfo);
+ PermuteNCDHWToNDHWC(outputExpected, outputTensorInfo);
+ }
+
return SimplePooling3dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset,
input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape());
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 5> AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolTestCommon(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout,
+ float qScale = 1.0f,
+ int32_t qOffset = 0)
+{
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType);
+
+ armnn::Pooling3dDescriptor descriptor;
+ descriptor.m_PoolType = armnn::PoolingAlgorithm::Max;
+ descriptor.m_PoolWidth = 1;
+ descriptor.m_PoolHeight = 2;
+ descriptor.m_PoolDepth = 3;
+ descriptor.m_StrideX = 1;
+ descriptor.m_StrideY = 2;
+ descriptor.m_StrideZ = 1;
+ descriptor.m_PadLeft = 0;
+ descriptor.m_PadRight = 0;
+ descriptor.m_PadTop = 2;
+ descriptor.m_PadBottom = 0;
+ descriptor.m_PadFront = 1;
+ descriptor.m_PadBack = 2;
+ descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
+ descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude;
+ descriptor.m_DataLayout = dataLayout;
+
+ // Construct input data.
+ auto input = QuantizedVector<T>( { 1.0f, 3.0f, 4.0f, }, qScale, qOffset);
+
+ // These were calculated manually.
+ auto outputExpected = QuantizedVector<T>( { 0.0f, 3.0f, 0.0f, 3.0f, }, qScale, qOffset);
+
+ if (dataLayout == armnn::DataLayout::NDHWC)
+ {
+ PermuteNCDHWToNDHWC<T>(input, inputTensorInfo);
+ PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo);
+ }
+
+ return SimplePooling3dTestImpl<ArmnnType>(
+ workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset,
+ input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape());
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 5> AsymmetricNonSquareMaxPooling3dTestCommon(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout,
float qScale = 1.0f,
int32_t qOffset = 0)
{
- armnn::TensorInfo inputTensorInfo({ 1, 1, 1, 3, 1 }, ArmnnType);
- armnn::TensorInfo outputTensorInfo({ 1, 1, 2, 2, 1 }, ArmnnType);
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType);
armnn::Pooling3dDescriptor descriptor;
descriptor.m_PoolType = armnn::PoolingAlgorithm::Max;
descriptor.m_PoolWidth = 1;
descriptor.m_PoolHeight = 2;
descriptor.m_PoolDepth = 3;
- descriptor.m_StrideX = 0;
+ descriptor.m_StrideX = 1;
+ descriptor.m_StrideY = 2;
+ descriptor.m_StrideZ = 1;
+ descriptor.m_PadLeft = 0;
+ descriptor.m_PadRight = 0;
+ descriptor.m_PadTop = 1;
+ descriptor.m_PadBottom = 0;
+ descriptor.m_PadFront = 1;
+ descriptor.m_PadBack = 2;
+ descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
+ descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude;
+ descriptor.m_DataLayout = dataLayout;
+
+ // Construct input data.
+ auto input = QuantizedVector<T>( { 1.0f, 3.0f, 4.0f, }, qScale, qOffset);
+
+ // These were calculated manually.
+ auto outputExpected = QuantizedVector<T>( { 1.0f, 4.0f, 1.0f, 4.0f, }, qScale, qOffset);
+
+ if (dataLayout == armnn::DataLayout::NDHWC)
+ {
+ PermuteNCDHWToNDHWC<T>(input, inputTensorInfo);
+ PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo);
+ }
+
+ return SimplePooling3dTestImpl<ArmnnType>(
+ workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset,
+ input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape());
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 5> AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolTestCommon(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout,
+ float qScale = 1.0f,
+ int32_t qOffset = 0)
+{
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType);
+
+ armnn::Pooling3dDescriptor descriptor;
+ descriptor.m_PoolType = armnn::PoolingAlgorithm::Average;
+ descriptor.m_PoolWidth = 1;
+ descriptor.m_PoolHeight = 2;
+ descriptor.m_PoolDepth = 3;
+ descriptor.m_StrideX = 1;
descriptor.m_StrideY = 2;
descriptor.m_StrideZ = 1;
descriptor.m_PadLeft = 0;
@@ -826,21 +949,19 @@
descriptor.m_PadBack = 2;
descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude;
+ descriptor.m_DataLayout = dataLayout;
// Construct input data.
- auto input = QuantizedVector<T>(
- {
- 1.0f, 3.0f, 4.0f,
- },
- qScale, qOffset);
+ auto input = QuantizedVector<T>({ 1.0f, 3.0f, 4.0f, }, qScale, qOffset);
// These were calculated manually.
- auto outputExpected = QuantizedVector<T>(
- {
- 0.0f, 3.0f, 0.0f, 3.0f,
- },
- qScale, qOffset);
+ auto outputExpected = QuantizedVector<T>( { 0.0f, 2.0f, 0.0f, 2.0f, }, qScale, qOffset);
+ if (dataLayout == armnn::DataLayout::NDHWC)
+ {
+ PermuteNCDHWToNDHWC<T>(input, inputTensorInfo);
+ PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo);
+ }
return SimplePooling3dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset,
input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape());
@@ -848,61 +969,61 @@
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 5> AsymmetricNonSquareAveragePooling3dTestCommon(
- armnn::IWorkloadFactory& workloadFactory,
- const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory,
- float qScale = 1.0f,
- int32_t qOffset = 0)
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout,
+ float qScale = 1.0f,
+ int32_t qOffset = 0)
{
- armnn::TensorInfo inputTensorInfo({ 1, 1, 1, 3, 1 }, ArmnnType);
- armnn::TensorInfo outputTensorInfo({ 1, 1, 2, 2, 1 }, ArmnnType);
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType);
armnn::Pooling3dDescriptor descriptor;
descriptor.m_PoolType = armnn::PoolingAlgorithm::Average;
descriptor.m_PoolWidth = 1;
descriptor.m_PoolHeight = 2;
descriptor.m_PoolDepth = 3;
- descriptor.m_StrideX = 0;
+ descriptor.m_StrideX = 1;
descriptor.m_StrideY = 2;
descriptor.m_StrideZ = 1;
descriptor.m_PadLeft = 0;
descriptor.m_PadRight = 0;
- descriptor.m_PadTop = 2;
+ descriptor.m_PadTop = 1;
descriptor.m_PadBottom = 0;
descriptor.m_PadFront = 1;
descriptor.m_PadBack = 2;
descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude;
+ descriptor.m_DataLayout = dataLayout;
// Construct input data.
- auto input = QuantizedVector<T>(
- {
- 1.0f, 3.0f, 4.0f,
- },
- qScale, qOffset);
+ auto input = QuantizedVector<T>( { 1.0f, 3.0f, 4.0f, }, qScale, qOffset);
// These were calculated manually.
- auto outputExpected = QuantizedVector<T>(
- {
- 0.0f, 2.0f, 0.0f, 2.0f,
- },
- qScale, qOffset);
+ auto outputExpected = QuantizedVector<T>( { 1.0f, 3.5f, 1.0f, 3.5f, }, qScale, qOffset);
+ if (dataLayout == armnn::DataLayout::NDHWC)
+ {
+ PermuteNCDHWToNDHWC<T>(input, inputTensorInfo);
+ PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo);
+ }
return SimplePooling3dTestImpl<ArmnnType>(
- workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset,
- input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape());
+ workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset,
+ input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape());
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
-LayerTestResult<T, 5> AsymmetricNonSquareL2Pooling3dTestCommon(
+LayerTestResult<T, 5> AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolTestCommon(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout,
float qScale = 1.0f,
int32_t qOffset = 0)
{
- armnn::TensorInfo inputTensorInfo({ 1, 1, 1, 3, 1 }, ArmnnType);
- armnn::TensorInfo outputTensorInfo({ 1, 1, 2, 2, 1 }, ArmnnType);
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType);
armnn::Pooling3dDescriptor descriptor;
descriptor.m_PoolType = armnn::PoolingAlgorithm::L2;
@@ -920,20 +1041,19 @@
descriptor.m_PadBack = 2;
descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude;
+ descriptor.m_DataLayout = dataLayout;
// Construct input data.
- auto input = QuantizedVector<T>(
- {
- 1.0f, 3.0f, 4.0f,
- },
- qScale, qOffset);
+ auto input = QuantizedVector<T>( { 1.0f, 3.0f, 4.0f, }, qScale, qOffset);
// These were calculated manually.
- auto outputExpected = QuantizedVector<T>(
- {
- 0.0f, 2.2360679775f, 0.0f, 2.2360679775f,
- },
- qScale, qOffset);
+ auto outputExpected = QuantizedVector<T>( { 0.0f, 2.2360679775f, 0.0f, 2.2360679775f, }, qScale, qOffset);
+
+ if (dataLayout == armnn::DataLayout::NDHWC)
+ {
+ PermuteNCDHWToNDHWC<T>(input, inputTensorInfo);
+ PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo);
+ }
return SimplePooling3dTestImpl<ArmnnType>(
workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset,
@@ -941,6 +1061,53 @@
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
+LayerTestResult<T, 5> AsymmetricNonSquareL2Pooling3dTestCommon(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout,
+ float qScale = 1.0f,
+ int32_t qOffset = 0)
+{
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 1, 3, 1, dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo( 1, 1, 2, 2, 1, dataLayout, ArmnnType);
+
+ armnn::Pooling3dDescriptor descriptor;
+ descriptor.m_PoolType = armnn::PoolingAlgorithm::L2;
+ descriptor.m_PoolWidth = 1;
+ descriptor.m_PoolHeight = 2;
+ descriptor.m_PoolDepth = 3;
+ descriptor.m_StrideX = 1;
+ descriptor.m_StrideY = 2;
+ descriptor.m_StrideZ = 1;
+ descriptor.m_PadLeft = 0;
+ descriptor.m_PadRight = 0;
+ descriptor.m_PadTop = 1;
+ descriptor.m_PadBottom = 0;
+ descriptor.m_PadFront = 1;
+ descriptor.m_PadBack = 2;
+ descriptor.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
+ descriptor.m_PaddingMethod = armnn::PaddingMethod::Exclude;
+ descriptor.m_DataLayout = dataLayout;
+
+ // Construct input data.
+ auto input = QuantizedVector<T>( { 1.0f, 3.0f, 4.0f, }, qScale, qOffset);
+
+ // These were calculated manually.
+ auto outputExpected = QuantizedVector<T>( { 1.0f, 3.53553390593f, 1.0f, 3.53553390593f, }, qScale, qOffset);
+
+ if (dataLayout == armnn::DataLayout::NDHWC)
+ {
+ PermuteNCDHWToNDHWC<T>(input, inputTensorInfo);
+ PermuteNCDHWToNDHWC<T>(outputExpected, outputTensorInfo);
+ }
+
+ return SimplePooling3dTestImpl<ArmnnType>(
+ workloadFactory, memoryManager, tensorHandleFactory, descriptor, qScale, qOffset,
+ input, outputExpected, inputTensorInfo.GetShape(), outputTensorInfo.GetShape());
+}
+
+template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 5> ComparePooling3dTestCommon(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
@@ -948,6 +1115,7 @@
const armnn::ITensorHandleFactory& tensorHandleFactory,
const armnn::ITensorHandleFactory& refTensorHandleFactory,
armnn::PoolingAlgorithm poolingType,
+ const armnn::DataLayout dataLayout,
float qScale = 1.0f,
int32_t qOffset = 0)
{
@@ -970,14 +1138,10 @@
const unsigned int outputHeight = (inputHeight + 2 * padY + strideY - poolSize) / strideY;
const unsigned int outputDepth = (inputDepth + 2 * padZ + strideZ - poolSize) / strideZ;
- armnn::TensorInfo inputTensorInfo;
- armnn::TensorInfo outputTensorInfo;
-
- unsigned int inputShape[] = { batchSize, channelCount, inputHeight, inputWidth, inputDepth };
- unsigned int outputShape[] = { batchSize, channelCount, outputHeight, outputWidth, outputDepth };
-
- inputTensorInfo = armnn::TensorInfo(5, inputShape, ArmnnType);
- outputTensorInfo = armnn::TensorInfo(5, outputShape, ArmnnType);
+ armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo(batchSize, channelCount, inputDepth, inputHeight,
+ inputWidth, dataLayout, ArmnnType);
+ armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo(batchSize, channelCount, outputDepth, outputHeight,
+ outputWidth, dataLayout, ArmnnType);
// Set quantization parameters if the requested type is a quantized type.
if(armnn::IsQuantizedType<T>())
@@ -991,7 +1155,6 @@
std::vector<T> input = MakeRandomTensor<T>(inputTensorInfo, 81715);
std::vector<T> actualOutput(outputTensorInfo.GetNumElements());
std::vector<T> expectedOutput(outputTensorInfo.GetNumElements());
-
LayerTestResult<T, 5> comparisonResult(outputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
@@ -1015,8 +1178,10 @@
data.m_Parameters.m_PadFront = padZ;
data.m_Parameters.m_PadBack = padZ;
data.m_Parameters.m_OutputShapeRounding = armnn::OutputShapeRounding::Floor;
+ data.m_Parameters.m_DataLayout = dataLayout;
- std::unique_ptr<armnn::ITensorHandle> outputHandleRef = refTensorHandleFactory.CreateTensorHandle(outputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> outputHandleRef =
+ refTensorHandleFactory.CreateTensorHandle(outputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> inputHandleRef = refTensorHandleFactory.CreateTensorHandle(inputTensorInfo);
// Don't execute if Pooling is not supported, as an exception will be raised.
@@ -1062,34 +1227,36 @@
return comparisonResult;
}
-
} // anonymous namespace
LayerTestResult<float, 5> SimpleMaxPooling3dSize2x2x2Stride1x1x1Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return SimpleMaxPooling3dSize2x2x2Stride1x1x1TestCommon<armnn::DataType::Float32>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<uint8_t, 5> SimpleMaxPooling3dSize2x2x2Stride1x1x1Uint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return SimpleMaxPooling3dSize2x2x2Stride1x1x1TestCommon<armnn::DataType::QAsymmU8>(
- workloadFactory, memoryManager, tensorHandleFactory, 0.1f, 128);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout, 0.1f, 128);
}
LayerTestResult<int16_t, 5> SimpleMaxPooling3dSize2x2x2Stride1x1x1Int16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return SimpleMaxPooling3dSize2x2x2Stride1x1x1TestCommon<armnn::DataType::QSymmS16>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<float, 5> SimpleMaxPooling3dTest(
@@ -1125,28 +1292,31 @@
LayerTestResult<float, 5> IgnorePaddingSimpleMaxPooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return IgnorePaddingSimpleMaxPooling3dTestCommon<armnn::DataType::Float32>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<uint8_t, 5> IgnorePaddingSimpleMaxPooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return IgnorePaddingSimpleMaxPooling3dTestCommon<armnn::DataType::QAsymmU8>(
- workloadFactory, memoryManager, tensorHandleFactory, 1.0f, -5);
+ workloadFactory, memoryManager, tensorHandleFactory,dataLayout, 1.0f, -5);
}
LayerTestResult<int16_t, 5> IgnorePaddingSimpleMaxPooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return IgnorePaddingSimpleMaxPooling3dTestCommon<armnn::DataType::QSymmS16>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<float, 5> SimpleAveragePooling3dTest(
@@ -1212,163 +1382,271 @@
LayerTestResult<float, 5> LargeTensorsAveragePooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return LargeTensorsAveragePooling3dTestCommon<armnn::DataType::Float32>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<uint8_t, 5> LargeTensorsAveragePooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return LargeTensorsAveragePooling3dTestCommon<armnn::DataType::QAsymmU8>(
- workloadFactory, memoryManager, tensorHandleFactory, 0.5, -1);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout, 0.5, -1);
}
LayerTestResult<int16_t, 5> LargeTensorsAveragePooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return LargeTensorsAveragePooling3dTestCommon<armnn::DataType::QSymmS16>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<float, 5> IgnorePaddingSimpleAveragePooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return IgnorePaddingSimpleAveragePooling3dTestCommon<armnn::DataType::Float32>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<uint8_t, 5> IgnorePaddingSimpleAveragePooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return IgnorePaddingSimpleAveragePooling3dTestCommon<armnn::DataType::QAsymmU8>(
- workloadFactory, memoryManager, tensorHandleFactory, 1.0f, -5);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout, 1.0f, -5);
}
LayerTestResult<int16_t, 5> IgnorePaddingSimpleAveragePooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return IgnorePaddingSimpleAveragePooling3dTestCommon<armnn::DataType::QSymmS16>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<float, 5> IgnorePaddingSimpleL2Pooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return IgnorePaddingSimpleL2Pooling3dTestCommon<armnn::DataType::Float32>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<uint8_t, 5> IgnorePaddingSimpleL2Pooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return IgnorePaddingSimpleL2Pooling3dTestCommon<armnn::DataType::QAsymmU8>(
- workloadFactory, memoryManager, tensorHandleFactory, 1.0f, -5);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout, 1.0f, -5);
}
LayerTestResult<int16_t, 5> IgnorePaddingSimpleL2Pooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return IgnorePaddingSimpleL2Pooling3dTestCommon<armnn::DataType::QSymmS16>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<float, 5> AsymmetricNonSquareMaxPooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return AsymmetricNonSquareMaxPooling3dTestCommon<armnn::DataType::Float32>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<uint8_t, 5> AsymmetricNonSquareMaxPooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return AsymmetricNonSquareMaxPooling3dTestCommon<armnn::DataType::QAsymmU8>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<int16_t, 5> AsymmetricNonSquareMaxPooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return AsymmetricNonSquareMaxPooling3dTestCommon<armnn::DataType::QSymmS16>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
+}
+
+LayerTestResult<float, 5> AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
+{
+ return AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::Float32>(
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
+}
+
+LayerTestResult<uint8_t, 5> AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolUint8Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
+{
+ return AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QAsymmU8>(
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
+}
+
+LayerTestResult<int16_t, 5> AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolInt16Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
+{
+ return AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QSymmS16>(
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<float, 5> AsymmetricNonSquareAveragePooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return AsymmetricNonSquareAveragePooling3dTestCommon<armnn::DataType::Float32>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<uint8_t, 5> AsymmetricNonSquareAveragePooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return AsymmetricNonSquareAveragePooling3dTestCommon<armnn::DataType::QAsymmU8>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<int16_t, 5> AsymmetricNonSquareAveragePooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return AsymmetricNonSquareAveragePooling3dTestCommon<armnn::DataType::QSymmS16>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
+}
+
+LayerTestResult<float, 5> AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
+{
+ return AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::Float32>(
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
+}
+
+LayerTestResult<uint8_t, 5> AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolUint8Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
+{
+ return AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QAsymmU8>(
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
+}
+
+LayerTestResult<int16_t, 5> AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolInt16Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
+{
+ return AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QSymmS16>(
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<float, 5> AsymmetricNonSquareL2Pooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return AsymmetricNonSquareL2Pooling3dTestCommon<armnn::DataType::Float32>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<uint8_t, 5> AsymmetricNonSquareL2Pooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return AsymmetricNonSquareL2Pooling3dTestCommon<armnn::DataType::QAsymmU8>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<int16_t, 5> AsymmetricNonSquareL2Pooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory)
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
{
return AsymmetricNonSquareL2Pooling3dTestCommon<armnn::DataType::QSymmS16>(
- workloadFactory, memoryManager, tensorHandleFactory);
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
+}
+
+LayerTestResult<float, 5> AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
+{
+ return AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::Float32>(
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
+}
+
+LayerTestResult<uint8_t, 5> AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolUint8Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
+{
+ return AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QAsymmU8>(
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
+}
+
+LayerTestResult<int16_t, 5> AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolInt16Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout)
+{
+ return AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolTestCommon<armnn::DataType::QSymmS16>(
+ workloadFactory, memoryManager, tensorHandleFactory, dataLayout);
}
LayerTestResult<float, 5> ComparePooling3dTest(
@@ -1377,10 +1655,12 @@
armnn::IWorkloadFactory& refWorkloadFactory,
const armnn::ITensorHandleFactory& tensorHandleFactory,
const armnn::ITensorHandleFactory& refTensorHandleFactory,
- armnn::PoolingAlgorithm poolingType)
+ armnn::PoolingAlgorithm poolingType,
+ const armnn::DataLayout dataLayout)
{
return ComparePooling3dTestCommon<armnn::DataType::Float32>(
- workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, poolingType);
+ workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory,
+ poolingType, dataLayout);
}
LayerTestResult<uint8_t, 5> ComparePooling3dUint8Test(
@@ -1389,11 +1669,12 @@
armnn::IWorkloadFactory& refWorkloadFactory,
const armnn::ITensorHandleFactory& tensorHandleFactory,
const armnn::ITensorHandleFactory& refTensorHandleFactory,
- armnn::PoolingAlgorithm poolingType)
+ armnn::PoolingAlgorithm poolingType,
+ const armnn::DataLayout dataLayout)
{
return ComparePooling3dTestCommon<armnn::DataType::QAsymmU8>(
workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory,
- poolingType, 0.1f, 128);
+ poolingType, dataLayout, 0.1f, 128);
}
LayerTestResult<int16_t, 5> ComparePooling3dInt16Test(
@@ -1402,8 +1683,10 @@
armnn::IWorkloadFactory& refWorkloadFactory,
const armnn::ITensorHandleFactory& tensorHandleFactory,
const armnn::ITensorHandleFactory& refTensorHandleFactory,
- armnn::PoolingAlgorithm poolingType)
+ armnn::PoolingAlgorithm poolingType,
+ const armnn::DataLayout dataLayout)
{
return ComparePooling3dTestCommon<armnn::DataType::QSymmS16>(
- workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory, poolingType);
+ workloadFactory, memoryManager, refWorkloadFactory, tensorHandleFactory, refTensorHandleFactory,
+ poolingType, dataLayout);
}
\ No newline at end of file
diff --git a/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.hpp
index 8ad8111..f17b6df 100644
--- a/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.hpp
+++ b/src/backends/backendsCommon/test/layerTests/Pooling3dTestImpl.hpp
@@ -15,17 +15,20 @@
LayerTestResult<float, 5> SimpleMaxPooling3dSize2x2x2Stride1x1x1Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 5>SimpleMaxPooling3dSize2x2x2Stride1x1x1Uint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<int16_t, 5> SimpleMaxPooling3dSize2x2x2Stride1x1x1Int16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 5> SimpleMaxPooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
@@ -48,17 +51,20 @@
LayerTestResult<float, 5> IgnorePaddingSimpleMaxPooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 5> IgnorePaddingSimpleMaxPooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<int16_t, 5> IgnorePaddingSimpleMaxPooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 5> SimpleAveragePooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
@@ -81,32 +87,38 @@
LayerTestResult<float, 5> LargeTensorsAveragePooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 5> LargeTensorsAveragePooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<int16_t, 5> LargeTensorsAveragePooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 5> IgnorePaddingSimpleAveragePooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 5> IgnorePaddingSimpleAveragePooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<int16_t, 5> IgnorePaddingSimpleAveragePooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 5> SimpleL2Pooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
@@ -129,62 +141,128 @@
LayerTestResult<float, 5> IgnorePaddingSimpleL2Pooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 5> IgnorePaddingSimpleL2Pooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<int16_t, 5> IgnorePaddingSimpleL2Pooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 5> AsymmetricNonSquareMaxPooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 5> AsymmetricNonSquareMaxPooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactor,
+ const armnn::DataLayout dataLayout);
LayerTestResult<int16_t, 5> AsymmetricNonSquareMaxPooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
+
+LayerTestResult<float, 5> AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
+
+LayerTestResult<uint8_t, 5> AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolUint8Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactor,
+ const armnn::DataLayout dataLayout);
+
+LayerTestResult<int16_t, 5> AsymmetricNonSquareMaxPooling3dWithPaddingOnlyPoolInt16Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 5> AsymmetricNonSquareAveragePooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 5> AsymmetricNonSquareAveragePooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<int16_t, 5> AsymmetricNonSquareAveragePooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
+
+LayerTestResult<float, 5> AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
+
+LayerTestResult<uint8_t, 5> AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolUint8Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
+
+LayerTestResult<int16_t, 5> AsymmetricNonSquareAveragePooling3dWithPaddingOnlyPoolInt16Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 5> AsymmetricNonSquareL2Pooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 5> AsymmetricNonSquareL2Pooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<int16_t, 5> AsymmetricNonSquareL2Pooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::ITensorHandleFactory& tensorHandleFactory);
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
+
+LayerTestResult<float, 5> AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolTest(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
+
+LayerTestResult<uint8_t, 5> AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolUint8Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
+
+LayerTestResult<int16_t, 5> AsymmetricNonSquareL2Pooling3dWithPaddingOnlyPoolInt16Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory,
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 5> ComparePooling3dTest(
armnn::IWorkloadFactory& workloadFactory,
@@ -192,7 +270,8 @@
armnn::IWorkloadFactory& refWorkloadFactory,
const armnn::ITensorHandleFactory& tensorHandleFactory,
const armnn::ITensorHandleFactory& refTensorHandleFactory,
- armnn::PoolingAlgorithm poolingType);
+ armnn::PoolingAlgorithm poolingType,
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 5> ComparePooling3dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
@@ -200,7 +279,8 @@
armnn::IWorkloadFactory& refWorkloadFactory,
const armnn::ITensorHandleFactory& tensorHandleFactory,
const armnn::ITensorHandleFactory& refTensorHandleFactory,
- armnn::PoolingAlgorithm poolingType);
+ armnn::PoolingAlgorithm poolingType,
+ const armnn::DataLayout dataLayout);
LayerTestResult<int16_t, 5> ComparePooling3dInt16Test(
armnn::IWorkloadFactory& workloadFactory,
@@ -208,6 +288,5 @@
armnn::IWorkloadFactory& refWorkloadFactory,
const armnn::ITensorHandleFactory& tensorHandleFactory,
const armnn::ITensorHandleFactory& refTensorHandleFactory,
- armnn::PoolingAlgorithm poolingType);
-
-
+ armnn::PoolingAlgorithm poolingType,
+ const armnn::DataLayout dataLayout);