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-rwxr-xr-xsrc/backends/backendsCommon/test/Conv2dTestImpl.hpp41
-rwxr-xr-xsrc/backends/backendsCommon/test/LayerTests.cpp86
-rw-r--r--src/backends/backendsCommon/test/LayerTests.hpp54
-rw-r--r--src/backends/backendsCommon/test/Pooling2dTestImpl.hpp21
4 files changed, 102 insertions, 100 deletions
diff --git a/src/backends/backendsCommon/test/Conv2dTestImpl.hpp b/src/backends/backendsCommon/test/Conv2dTestImpl.hpp
index d99b7f7fa3..6685a8edd2 100755
--- a/src/backends/backendsCommon/test/Conv2dTestImpl.hpp
+++ b/src/backends/backendsCommon/test/Conv2dTestImpl.hpp
@@ -14,6 +14,7 @@
#include <test/TensorHelpers.hpp>
#include "QuantizeHelper.hpp"
+#include <backendsCommon/DataLayoutIndexed.hpp>
#include <backendsCommon/CpuTensorHandle.hpp>
#include <backendsCommon/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
@@ -75,7 +76,7 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl(
const boost::multi_array<T, 4>& originalOutputExpected,
float qScale,
int32_t qOffset,
- const armnn::DataLayoutIndexed& layout = armnn::DataLayout::NCHW,
+ const armnn::DataLayout layout = armnn::DataLayout::NCHW,
uint32_t padLeft = 0,
uint32_t padTop = 0,
uint32_t padRight = 0,
@@ -137,7 +138,7 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl(
// at this point if we require it permute the input data
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
std::vector<T> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
@@ -166,7 +167,7 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl(
outputData.insert(outputData.end(), outputImage.begin(), outputImage.end());
// at this point if we require it permute the expected output
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
std::vector<T> tmp(outputData.size());
armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp.data());
@@ -187,7 +188,7 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl(
armnn::ScopedCpuTensorHandle biasTensor(biasDesc);
// Permute the kernel if necessary
boost::multi_array<T, 4> kernel = boost::multi_array<T, 4>(originalKernel);
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
armnnUtils::Permute(kernelDesc.GetShape(), NCHWToNHWC, originalKernel.data(), kernel.data());
}
@@ -210,7 +211,7 @@ LayerTestResult<T, 4> SimpleConvolution2dTestImpl(
data.m_Parameters.m_PadTop = padTop;
data.m_Parameters.m_PadBottom = padBottom;
data.m_Parameters.m_BiasEnabled = biasEnabled;
- data.m_Parameters.m_DataLayout = layout.GetDataLayout();
+ data.m_Parameters.m_DataLayout = layout;
std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConvolution2d(data, info);
inputHandle->Allocate();
@@ -327,7 +328,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl(
const boost::multi_array<T, 4>& outputExpected,
float qScale,
int32_t qOffset,
- const armnn::DataLayoutIndexed& layout,
+ const armnn::DataLayout layout,
uint32_t padLeft = 0,
uint32_t padTop = 0,
uint32_t padRight = 0,
@@ -377,7 +378,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl(
// At this point if we require it permute the input data
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
std::vector<T> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
@@ -401,7 +402,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl(
LayerTestResult<T, 4> ret(outputTensorInfo);
// At this point if we require it permute the expected output
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
std::vector<T> tmp(outputData.size());
armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputData.data(), tmp.data());
@@ -417,7 +418,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl(
// Permute the kernel if necessary
boost::multi_array<T, 4> kernel = boost::multi_array<T, 4>(originalKernel);
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
armnnUtils::Permute(kernelDesc.GetShape(), NCHWToNHWC, originalKernel.data(), kernel.data());
}
@@ -440,7 +441,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestImpl(
data.m_Parameters.m_PadTop = padTop;
data.m_Parameters.m_PadBottom = padBottom;
data.m_Parameters.m_BiasEnabled = biasEnabled;
- data.m_Parameters.m_DataLayout = layout.GetDataLayout();
+ data.m_Parameters.m_DataLayout = layout;
armnn::WorkloadInfo info;
AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
@@ -466,7 +467,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dDepthMul1TestImpl(
float qScale,
int32_t qOffset,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
unsigned int inputHeight = 3;
unsigned int inputWidth = 3;
@@ -511,7 +512,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dDepthMul1TestImpl(
}));
// at this point if we require it permute the input data
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
std::vector<T> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
@@ -533,7 +534,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dDepthMul1TestImpl(
0.f, 0.f, 0.f,
-1.f, 0.f, -1.f,
}));
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
std::vector<T> tmp(kernelData.size());
armnnUtils::Permute(kernelDesc.GetShape(), NCHWToNHWC, kernelData.data(), tmp.data());
@@ -557,7 +558,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dDepthMul1TestImpl(
}
LayerTestResult<T, 4> ret(outputTensorInfo);
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
std::vector<T> tmp(outputImage.size());
armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, outputImage.data(), tmp.data());
@@ -589,7 +590,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dDepthMul1TestImpl(
data.m_Parameters.m_PadTop = 0;
data.m_Parameters.m_PadBottom = 0;
data.m_Parameters.m_BiasEnabled = biasEnabled;
- data.m_Parameters.m_DataLayout = layout.GetDataLayout();
+ data.m_Parameters.m_DataLayout = layout;
std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateDepthwiseConvolution2d(data, info);
inputHandle->Allocate();
@@ -611,7 +612,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
float qScale,
int32_t qOffset,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
unsigned int depthMultiplier = 2;
@@ -672,7 +673,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
std::vector<T> inputData = originalInputData;
// at this point if we require it permute the input data
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, originalInputData.data(), inputData.data());
}
@@ -709,7 +710,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
0, 0, 0
}));
std::vector<T> kernelData = originalKernelData;
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
armnnUtils::Permute(kernelDesc.GetShape(), NCHWToNHWC, originalKernelData.data(), kernelData.data());
}
@@ -762,7 +763,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
LayerTestResult<T, 4> ret(outputTensorInfo);
std::vector<T> outputImage = originalOutputImage;
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
armnnUtils::Permute(outputTensorInfo.GetShape(), NCHWToNHWC, originalOutputImage.data(), outputImage.data());
}
@@ -792,7 +793,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dTestImpl(
data.m_Parameters.m_PadTop = 1;
data.m_Parameters.m_PadBottom = 1;
data.m_Parameters.m_BiasEnabled = biasEnabled;
- data.m_Parameters.m_DataLayout = layout.GetDataLayout();
+ data.m_Parameters.m_DataLayout = layout;
std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateDepthwiseConvolution2d(data, info);
inputHandle->Allocate();
diff --git a/src/backends/backendsCommon/test/LayerTests.cpp b/src/backends/backendsCommon/test/LayerTests.cpp
index caa4f4065d..ecd09ca024 100755
--- a/src/backends/backendsCommon/test/LayerTests.cpp
+++ b/src/backends/backendsCommon/test/LayerTests.cpp
@@ -109,7 +109,7 @@ LayerTestResult<T, 4> SimpleConvolution2d3x5TestCommon(
float qScale,
int32_t qOffset,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
// Use common single-batch 3-channel 16x8 image.
armnn::TensorInfo inputDesc({1, 3, 8, 16}, armnn::GetDataType<T>());
@@ -192,7 +192,7 @@ LayerTestResult<T, 4> SimpleConvolution2d3x3TestCommon(
float qScale,
int32_t qOffset,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
// Use a 3x3 kernel, which exercises ArmCompute's direct convolution path.
@@ -315,7 +315,7 @@ LayerTestResult<float, 4> SimpleConvolution2d3x5Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return SimpleConvolution2d3x5TestCommon<float>(workloadFactory, memoryManager, 0.f, 0, biasEnabled, layout);
}
@@ -324,7 +324,7 @@ LayerTestResult<uint8_t, 4> SimpleConvolution2d3x5Uint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return SimpleConvolution2d3x5TestCommon<uint8_t>(workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);
}
@@ -333,7 +333,7 @@ LayerTestResult<float, 4> SimpleConvolution2d3x3Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return SimpleConvolution2d3x3TestCommon<float>(workloadFactory, memoryManager, 0.f, 0, biasEnabled, layout);
}
@@ -355,7 +355,7 @@ LayerTestResult<uint8_t, 4> SimpleConvolution2d3x3Uint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return SimpleConvolution2d3x3TestCommon<uint8_t>(workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);
}
@@ -364,7 +364,7 @@ template<typename T>
LayerTestResult<T, 4> Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout,
+ const armnn::DataLayout layout,
float qScale,
int32_t qOffset)
{
@@ -426,7 +426,7 @@ template<typename T>
LayerTestResult<T, 4> SimpleConvolution2dAsymmetricPaddingTestCommon(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout,
+ const armnn::DataLayout layout,
float qScale,
int32_t qOffset)
{
@@ -485,7 +485,7 @@ LayerTestResult<T, 4> DepthwiseConvolution2dAsymmetricTestCommon(
float qScale,
int32_t qOffset,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
// Use a single-batch 2-channel 5x5 image as input.
armnn::TensorInfo inputTensorInfo({ 1, 2, 5, 5 }, armnn::GetDataType<T>());
@@ -673,7 +673,7 @@ LayerTestResult<float, 4>
Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTestCommon<float>(
workloadFactory, memoryManager, layout, 0.0f, 0);
@@ -682,7 +682,7 @@ Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest(
LayerTestResult<float, 4> Convolution2dAsymmetricPaddingTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return SimpleConvolution2dAsymmetricPaddingTestCommon<float>(
workloadFactory, memoryManager, layout, 0.0f, 0);
@@ -692,7 +692,7 @@ LayerTestResult<float, 4> DepthwiseConvolution2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return DepthwiseConvolution2dTestImpl<float, float>(
workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout);
@@ -710,7 +710,7 @@ LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul1Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return DepthwiseConvolution2dDepthMul1TestImpl<float, float>(
workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout);
@@ -720,7 +720,7 @@ LayerTestResult<float, 4> DepthwiseConvolution2dAsymmetricTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return DepthwiseConvolution2dAsymmetricTestCommon<float>(
workloadFactory, memoryManager, 0.0f, 0, biasEnabled, layout);
@@ -730,7 +730,7 @@ LayerTestResult<uint8_t, 4> DepthwiseConvolution2dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return DepthwiseConvolution2dTestImpl<uint8_t, int32_t>(
workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);
@@ -740,7 +740,7 @@ LayerTestResult<uint8_t, 4> DepthwiseConvolution2dDepthMul1Uint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return DepthwiseConvolution2dDepthMul1TestImpl<uint8_t, int32_t>(
workloadFactory, memoryManager, 0.5f, 50, biasEnabled, layout);
@@ -775,7 +775,7 @@ LayerTestResult<T,4> CompareDepthwiseConvolution2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
armnn::IWorkloadFactory& refWorkloadFactory,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
return CompareDepthwiseConvolution2dTestImpl<T>(workloadFactory, memoryManager, refWorkloadFactory, layout);
}
@@ -784,13 +784,13 @@ template LayerTestResult<float, 4> CompareDepthwiseConvolution2dTest<float>(
armnn::IWorkloadFactory&,
const armnn::IBackendInternal::IMemoryManagerSharedPtr&,
armnn::IWorkloadFactory&,
- const armnn::DataLayoutIndexed&);
+ const armnn::DataLayout);
template LayerTestResult<uint8_t, 4> CompareDepthwiseConvolution2dTest<uint8_t>(
armnn::IWorkloadFactory&,
const armnn::IBackendInternal::IMemoryManagerSharedPtr&,
armnn::IWorkloadFactory&,
- const armnn::DataLayoutIndexed&);
+ const armnn::DataLayout);
LayerTestResult<float,4> SimpleNormalizationAcrossTest(
armnn::IWorkloadFactory& workloadFactory,
@@ -3857,7 +3857,7 @@ LayerTestResult<float, 4> Concatenation4dDiffShapeDim3Test(
LayerTestResult<float, 4> ResizeBilinearNopTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout)
+ const armnn::DataLayout dataLayout)
{
const armnn::TensorInfo inputTensorInfo = GetTensorInfo<float>(1, 2, 4, 4, dataLayout);
const armnn::TensorInfo outputTensorInfo = GetTensorInfo<float>(1, 2, 4, 4, dataLayout);
@@ -3875,7 +3875,7 @@ LayerTestResult<float, 4> ResizeBilinearNopTest(
});
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (dataLayout == armnn::DataLayout::NHWC)
{
std::vector<float> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
@@ -3911,7 +3911,7 @@ LayerTestResult<float, 4> ResizeBilinearNopTest(
LayerTestResult<float, 4> SimpleResizeBilinearTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout)
+ const armnn::DataLayout dataLayout)
{
const armnn::TensorInfo inputTensorInfo = GetTensorInfo<float>(1, 2, 2, 2, dataLayout);
const armnn::TensorInfo outputTensorInfo = GetTensorInfo<float>(1, 2, 1, 1, dataLayout);
@@ -3937,7 +3937,7 @@ LayerTestResult<float, 4> SimpleResizeBilinearTest(
});
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (dataLayout == armnn::DataLayout::NHWC)
{
std::vector<float> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
@@ -3977,7 +3977,7 @@ LayerTestResult<float, 4> SimpleResizeBilinearTest(
LayerTestResult<float, 4> ResizeBilinearSqMinTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout)
+ const armnn::DataLayout dataLayout)
{
const armnn::TensorInfo inputTensorInfo = GetTensorInfo<float>(1, 2, 4, 4, dataLayout);
const armnn::TensorInfo outputTensorInfo = GetTensorInfo<float>(1, 2, 2, 2, dataLayout);
@@ -4003,7 +4003,7 @@ LayerTestResult<float, 4> ResizeBilinearSqMinTest(
});
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (dataLayout == armnn::DataLayout::NHWC)
{
std::vector<float> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
@@ -4043,7 +4043,7 @@ LayerTestResult<float, 4> ResizeBilinearSqMinTest(
LayerTestResult<float, 4> ResizeBilinearMinTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout)
+ const armnn::DataLayout dataLayout)
{
const armnn::TensorInfo inputTensorInfo = GetTensorInfo<float>(1, 2, 3, 5, dataLayout);
const armnn::TensorInfo outputTensorInfo = GetTensorInfo<float>(1, 2, 2, 3, dataLayout);
@@ -4067,7 +4067,7 @@ LayerTestResult<float, 4> ResizeBilinearMinTest(
});
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (dataLayout == armnn::DataLayout::NHWC)
{
std::vector<float> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
@@ -4107,7 +4107,7 @@ LayerTestResult<float, 4> ResizeBilinearMinTest(
LayerTestResult<float, 4> ResizeBilinearMagTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout)
+ const armnn::DataLayout dataLayout)
{
const armnn::TensorInfo inputTensorInfo = GetTensorInfo<float>(1, 2, 3, 2, dataLayout);
const armnn::TensorInfo outputTensorInfo = GetTensorInfo<float>(1, 2, 3, 5, dataLayout);
@@ -4133,7 +4133,7 @@ LayerTestResult<float, 4> ResizeBilinearMagTest(
});
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (dataLayout == armnn::DataLayout::NHWC)
{
std::vector<float> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
@@ -4235,7 +4235,7 @@ LayerTestResult<float, 4> L2NormalizationTestImpl(
const armnn::TensorShape& inputOutputTensorShape,
const std::vector<float>& inputValues,
const std::vector<float>& expectedOutputValues,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
const armnn::TensorInfo inputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32);
const armnn::TensorInfo outputTensorInfo(inputOutputTensorShape, armnn::DataType::Float32);
@@ -4243,7 +4243,7 @@ LayerTestResult<float, 4> L2NormalizationTestImpl(
// at this point if we require it permute the input data
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
std::vector<float> inputData = inputValues;
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
std::vector<float> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
@@ -4254,7 +4254,7 @@ LayerTestResult<float, 4> L2NormalizationTestImpl(
LayerTestResult<float, 4> result(outputTensorInfo);
std::vector<float> expectedOutputData = expectedOutputValues;
- if (layout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (layout == armnn::DataLayout::NHWC)
{
std::vector<float> tmp(expectedOutputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, expectedOutputData.data(), tmp.data());
@@ -4266,7 +4266,7 @@ LayerTestResult<float, 4> L2NormalizationTestImpl(
std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
armnn::L2NormalizationQueueDescriptor descriptor;
- descriptor.m_Parameters.m_DataLayout = layout.GetDataLayout();
+ descriptor.m_Parameters.m_DataLayout = layout;
armnn::WorkloadInfo info;
AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
@@ -4729,7 +4729,7 @@ LayerTestResult<float, 4> PadFloat324dTest(
LayerTestResult<float, 4> L2Normalization1dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
// Width: 1
// Height: 1
@@ -4799,7 +4799,7 @@ LayerTestResult<float, 4> L2Normalization1dTest(
LayerTestResult<float, 4> L2Normalization2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
// Width: 5
// Height: 1
@@ -4844,7 +4844,7 @@ LayerTestResult<float, 4> L2Normalization2dTest(
LayerTestResult<float, 4> L2Normalization3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
// Width: 3
// Height: 4
@@ -4909,7 +4909,7 @@ LayerTestResult<float, 4> L2Normalization3dTest(
LayerTestResult<float, 4> L2Normalization4dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout)
+ const armnn::DataLayout layout)
{
// Width: 3
// Height: 4
@@ -6357,7 +6357,7 @@ LayerTestResult<uint8_t, 4> SimpleMaxPooling2dSize3x3Stride2x4Uint8Test(
LayerTestResult<float, 4> SimpleMaxPooling2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout)
+ const armnn::DataLayout dataLayout)
{
return SimpleMaxPooling2dTestCommon<float>(workloadFactory, memoryManager, dataLayout);
}
@@ -6365,7 +6365,7 @@ LayerTestResult<float, 4> SimpleMaxPooling2dTest(
LayerTestResult<uint8_t, 4> SimpleMaxPooling2dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout)
+ const armnn::DataLayout dataLayout)
{
return SimpleMaxPooling2dTestCommon<uint8_t>(workloadFactory, memoryManager, dataLayout);
}
@@ -6373,7 +6373,7 @@ LayerTestResult<uint8_t, 4> SimpleMaxPooling2dUint8Test(
LayerTestResult<float, 4> SimpleAveragePooling2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout)
+ const armnn::DataLayout dataLayout)
{
return SimpleAveragePooling2dTestCommon<float>(workloadFactory, memoryManager, dataLayout);
}
@@ -6381,7 +6381,7 @@ LayerTestResult<float, 4> SimpleAveragePooling2dTest(
LayerTestResult<uint8_t, 4> SimpleAveragePooling2dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout)
+ const armnn::DataLayout dataLayout)
{
return SimpleAveragePooling2dTestCommon<uint8_t>(
workloadFactory, memoryManager, dataLayout, 0.5, -1);
@@ -6413,7 +6413,7 @@ LayerTestResult<uint8_t, 4> LargeTensorsAveragePooling2dUint8Test(
LayerTestResult<float, 4> SimpleL2Pooling2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout)
+ const armnn::DataLayout dataLayout)
{
return SimpleL2Pooling2dTestCommon<float>(workloadFactory, memoryManager, dataLayout);
}
@@ -6421,7 +6421,7 @@ LayerTestResult<float, 4> SimpleL2Pooling2dTest(
LayerTestResult<uint8_t, 4> SimpleL2Pooling2dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout)
+ const armnn::DataLayout dataLayout)
{
return SimpleL2Pooling2dTestCommon<uint8_t>(workloadFactory, memoryManager, dataLayout);
}
diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp
index 15d0853006..498cfb7fe0 100644
--- a/src/backends/backendsCommon/test/LayerTests.hpp
+++ b/src/backends/backendsCommon/test/LayerTests.hpp
@@ -58,13 +58,13 @@ LayerTestResult<float, 4> SimpleConvolution2d3x5Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> SimpleConvolution2d3x3Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> SimpleConvolution2d3x3NhwcTest(
armnn::IWorkloadFactory& workloadFactory,
@@ -75,12 +75,12 @@ LayerTestResult<float, 4>
Convolution2dAsymmetricPaddingLargerThanHalfKernelSizeTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> Convolution2dAsymmetricPaddingTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> Convolution1dTest(
armnn::IWorkloadFactory& workloadFactory,
@@ -96,7 +96,7 @@ LayerTestResult<float, 4> DepthwiseConvolution2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> DepthwiseConvolution2dDepthNhwcTest(
armnn::IWorkloadFactory& workloadFactory,
@@ -107,13 +107,13 @@ LayerTestResult<float, 4> DepthwiseConvolution2dDepthMul1Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> DepthwiseConvolution2dAsymmetricTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> SimpleMaxPooling2dSize2x2Stride2x2Test(
armnn::IWorkloadFactory& workloadFactory,
@@ -154,22 +154,22 @@ LayerTestResult<uint8_t, 4> IgnorePaddingMaxPooling2dSize3Uint8Test(
LayerTestResult<float, 4> SimpleMaxPooling2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout);
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 4> SimpleMaxPooling2dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout);
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 4> SimpleAveragePooling2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout);
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 4> SimpleAveragePooling2dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout);
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 4> IgnorePaddingAveragePooling2dSize3x2Stride2x2Test(
armnn::IWorkloadFactory& workloadFactory,
@@ -203,12 +203,12 @@ LayerTestResult<uint8_t, 4> IgnorePaddingAveragePooling2dSize3Uint8Test(
LayerTestResult<float, 4> SimpleL2Pooling2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout);
+ const armnn::DataLayout dataLayout);
LayerTestResult<uint8_t, 4> SimpleL2Pooling2dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout);
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 4> L2Pooling2dSize3Stride1Test(
armnn::IWorkloadFactory& workloadFactory,
@@ -464,7 +464,7 @@ LayerTestResult<T, 4> CompareDepthwiseConvolution2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
armnn::IWorkloadFactory& refWorkloadFactory,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> CompareNormalizationTest(
armnn::IWorkloadFactory& workloadFactory,
@@ -606,32 +606,32 @@ LayerTestResult<float, 4> CompareBoundedReLuTest(
LayerTestResult<float, 4> ResizeBilinearNopTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout);
+ const armnn::DataLayout dataLayout);
// Tests the behaviour of the resize bilinear operation when rescaling a 2x2 image into a 1x1 image.
LayerTestResult<float, 4> SimpleResizeBilinearTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout);
+ const armnn::DataLayout dataLayout);
// Tests the resize bilinear for minification of a square input matrix (also: input dimensions are a
// multiple of output dimensions).
LayerTestResult<float, 4> ResizeBilinearSqMinTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout);
+ const armnn::DataLayout dataLayout);
// Tests the resize bilinear for minification (output dimensions smaller than input dimensions).
LayerTestResult<float, 4> ResizeBilinearMinTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout);
+ const armnn::DataLayout dataLayout);
// Tests the resize bilinear for magnification (output dimensions bigger than input dimensions).
LayerTestResult<float, 4> ResizeBilinearMagTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout);
+ const armnn::DataLayout dataLayout);
LayerTestResult<float, 4> BatchNormTest(
armnn::IWorkloadFactory& workloadFactory,
@@ -648,22 +648,22 @@ LayerTestResult<float, 2> FakeQuantizationTest(
LayerTestResult<float, 4> L2Normalization1dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> L2Normalization2dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> L2Normalization3dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> L2Normalization4dTest(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<float, 4> ConstantTest(
armnn::IWorkloadFactory& workloadFactory,
@@ -765,25 +765,25 @@ LayerTestResult<uint8_t, 4> SimpleConvolution2d3x5Uint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<uint8_t, 4> SimpleConvolution2d3x3Uint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<uint8_t, 4> DepthwiseConvolution2dUint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<uint8_t, 4> DepthwiseConvolution2dDepthMul1Uint8Test(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
bool biasEnabled,
- const armnn::DataLayoutIndexed& layout);
+ const armnn::DataLayout layout);
LayerTestResult<uint8_t, 4> ConstantLinearActivationUint8Test(
armnn::IWorkloadFactory& workloadFactory,
diff --git a/src/backends/backendsCommon/test/Pooling2dTestImpl.hpp b/src/backends/backendsCommon/test/Pooling2dTestImpl.hpp
index 2e851faaa7..9050fc64a6 100644
--- a/src/backends/backendsCommon/test/Pooling2dTestImpl.hpp
+++ b/src/backends/backendsCommon/test/Pooling2dTestImpl.hpp
@@ -34,10 +34,11 @@ LayerTestResult<T, 4> SimplePooling2dTestImpl(
const boost::multi_array<T, 4>& input,
const boost::multi_array<T, 4>& outputExpected)
{
- const armnn::DataLayoutIndexed dataLayout = descriptor.m_DataLayout;
- auto heightIndex = dataLayout.GetHeightIndex();
- auto widthIndex = dataLayout.GetWidthIndex();
- auto channelsIndex = dataLayout.GetChannelsIndex();
+ const armnn::DataLayout dataLayout = descriptor.m_DataLayout;
+ const armnn::DataLayoutIndexed dimensionIndices = dataLayout;
+ auto heightIndex = dimensionIndices.GetHeightIndex();
+ auto widthIndex = dimensionIndices.GetWidthIndex();
+ auto channelsIndex = dimensionIndices.GetChannelsIndex();
unsigned int inputHeight = boost::numeric_cast<unsigned int>(input.shape()[heightIndex]);
unsigned int inputWidth = boost::numeric_cast<unsigned int>(input.shape()[widthIndex]);
@@ -240,7 +241,7 @@ template<typename T>
LayerTestResult<T, 4> SimpleMaxPooling2dTestCommon(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- const armnn::DataLayoutIndexed& dataLayout = armnn::DataLayout::NCHW,
+ const armnn::DataLayout dataLayout = armnn::DataLayout::NCHW,
float qScale = 1.0f,
int32_t qOffset = 0)
{
@@ -286,7 +287,7 @@ LayerTestResult<T, 4> SimpleMaxPooling2dTestCommon(
}));
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (dataLayout == armnn::DataLayout::NHWC)
{
std::vector<T> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
@@ -309,7 +310,7 @@ template<typename T>
LayerTestResult<T, 4> SimpleAveragePooling2dTestCommon(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- armnn::DataLayoutIndexed dataLayout = armnn::DataLayout::NCHW,
+ armnn::DataLayout dataLayout = armnn::DataLayout::NCHW,
float qScale = 1.0f,
int32_t qOffset = 0)
{
@@ -355,7 +356,7 @@ LayerTestResult<T, 4> SimpleAveragePooling2dTestCommon(
}));
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (dataLayout == armnn::DataLayout::NHWC)
{
std::vector<T> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
@@ -429,7 +430,7 @@ template<typename T>
LayerTestResult<T, 4> SimpleL2Pooling2dTestCommon(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
- armnn::DataLayoutIndexed dataLayout = armnn::DataLayout::NCHW,
+ armnn::DataLayout dataLayout = armnn::DataLayout::NCHW,
float qScale = 1.0f,
int32_t qOffset = 0)
{
@@ -466,7 +467,7 @@ LayerTestResult<T, 4> SimpleL2Pooling2dTestCommon(
}));
const armnn::PermutationVector NCHWToNHWC = { 0, 3, 1, 2 };
- if (dataLayout.GetDataLayout() == armnn::DataLayout::NHWC)
+ if (dataLayout == armnn::DataLayout::NHWC)
{
std::vector<T> tmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NCHWToNHWC, inputData.data(), tmp.data());
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-08 20:19:56 +0000