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| author | Matteo Martincigh <matteo.martincigh@arm.com> | 2018-11-28 16:22:36 +0000 |
|---|---|---|
| committer | Matteo Martincigh <matteo.martincigh@arm.com> | 2018-12-05 13:48:43 +0000 |
| commit | 4631582a4c8b92917633d0af4ebcc8fff2abd04a (patch) | |
| tree | 15f237e78af14394486699dedb834531af207067 /src/backends/reference/workloads/ConvImpl.hpp | |
| parent | c2130a070e6a9196d193c93a02b5f118810dd59a (diff) | |
| download | armnn-4631582a4c8b92917633d0af4ebcc8fff2abd04a.tar.gz | |
IVGCVSW-2264 Remove input swizzling from ParseConv2D in the TF parser
* Removed the input swizzling when the data layout is NHWC
* Permuting weights depending on the data layout used
* Added getter methods to ParsedConstTfOperation to get the tensor
info and the storage memory area, needed for swizzling the weights
* Added unit tests for both NHWC and NCHW data layouts
Change-Id: I6543900c594417df630b2663d8551158b93b7836
Diffstat (limited to 'src/backends/reference/workloads/ConvImpl.hpp')
| -rw-r--r-- | src/backends/reference/workloads/ConvImpl.hpp | 11 |
1 files changed, 7 insertions, 4 deletions
diff --git a/src/backends/reference/workloads/ConvImpl.hpp b/src/backends/reference/workloads/ConvImpl.hpp index b8e2deaa9c..704bc368d2 100644 --- a/src/backends/reference/workloads/ConvImpl.hpp +++ b/src/backends/reference/workloads/ConvImpl.hpp @@ -15,6 +15,8 @@ #include <boost/assert.hpp> #include <boost/numeric/conversion/cast.hpp> +#include <DataLayoutIndexed.hpp> + #include <cmath> #include <limits> @@ -74,6 +76,7 @@ static void ConvImpl(ConvData data, data.m_Parameters.m_DataLayout); const armnnUtils::DataLayoutIndexed dataLayoutIndexed(data.m_Parameters.m_DataLayout); + const unsigned int channelsIndex = dataLayoutIndexed.GetChannelsIndex(); const unsigned int heightIndex = dataLayoutIndexed.GetHeightIndex(); const unsigned int widthIndex = dataLayoutIndexed.GetWidthIndex(); @@ -91,10 +94,10 @@ static void ConvImpl(ConvData data, unsigned int heightFilter = filterInfo.GetShape()[heightIndex]; unsigned int widthFilter = filterInfo.GetShape()[widthIndex]; - unsigned int paddingTop = data.m_Parameters.m_PadTop; + unsigned int paddingTop = data.m_Parameters.m_PadTop; unsigned int paddingLeft = data.m_Parameters.m_PadLeft; - unsigned int hStride = data.m_Parameters.m_StrideY; - unsigned int xStride = data.m_Parameters.m_StrideX; + unsigned int xStride = data.m_Parameters.m_StrideX; + unsigned int yStride = data.m_Parameters.m_StrideY; // The world's least efficient convolution. for (unsigned int batchIdx = 0; batchIdx < batchSize; batchIdx++) @@ -168,7 +171,7 @@ static void ConvImpl(ConvData data, AccumulatorType filterValue = filterData[filterIndex] - boost::numeric_cast<AccumulatorType>(filterOffset); - unsigned int yInput = yOutput * hStride + yFilter; + unsigned int yInput = yOutput * yStride + yFilter; unsigned int xInput = xOutput * xStride + xFilter; AccumulatorType inputValue; |