From 8efb48a6847c5cd166c561127ae6611150963ce3 Mon Sep 17 00:00:00 2001 From: Nikhil Raj Date: Fri, 19 May 2023 11:14:28 +0100 Subject: Update Doxygen docu for 23.05 Signed-off-by: Nikhil Raj Change-Id: I0a992286f14fa68fcc6e5eba31ac39fed003cbbe --- .../classarmnn_utils_1_1_data_layout_indexed.xhtml | 455 +++++++++++++++++++++ 1 file changed, 455 insertions(+) create mode 100644 23.05/classarmnn_utils_1_1_data_layout_indexed.xhtml (limited to '23.05/classarmnn_utils_1_1_data_layout_indexed.xhtml') diff --git a/23.05/classarmnn_utils_1_1_data_layout_indexed.xhtml b/23.05/classarmnn_utils_1_1_data_layout_indexed.xhtml new file mode 100644 index 0000000000..7eff05f824 --- /dev/null +++ b/23.05/classarmnn_utils_1_1_data_layout_indexed.xhtml @@ -0,0 +1,455 @@ + + + + + + + + + + + + + +ArmNN: DataLayoutIndexed Class Reference + + + + + + + + + + + + + + + + +
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+  23.05 +
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+Public Member Functions | +List of all members
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DataLayoutIndexed Class Reference
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Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout. + More...

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#include <DataLayoutIndexed.hpp>

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+Public Member Functions

 DataLayoutIndexed (armnn::DataLayout dataLayout)
 
armnn::DataLayout GetDataLayout () const
 
unsigned int GetChannelsIndex () const
 
unsigned int GetHeightIndex () const
 
unsigned int GetWidthIndex () const
 
unsigned int GetDepthIndex () const
 
unsigned int GetIndex (const armnn::TensorShape &shape, unsigned int batchIndex, unsigned int channelIndex, unsigned int heightIndex, unsigned int widthIndex) const
 
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Detailed Description

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Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout.

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Definition at line 17 of file DataLayoutIndexed.hpp.

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Constructor & Destructor Documentation

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◆ DataLayoutIndexed()

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DataLayoutIndexed (armnn::DataLayout dataLayout)
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Definition at line 13 of file DataLayoutIndexed.cpp.

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14  : m_DataLayout(dataLayout)
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15 {
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16  switch (dataLayout)
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17  {
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18  case armnn::DataLayout::NHWC:
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19  m_ChannelsIndex = 3;
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20  m_HeightIndex = 1;
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21  m_WidthIndex = 2;
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22  break;
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23  case armnn::DataLayout::NCHW:
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24  m_ChannelsIndex = 1;
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25  m_HeightIndex = 2;
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26  m_WidthIndex = 3;
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27  break;
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28  case armnn::DataLayout::NDHWC:
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29  m_DepthIndex = 1;
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30  m_HeightIndex = 2;
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31  m_WidthIndex = 3;
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32  m_ChannelsIndex = 4;
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33  break;
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34  case armnn::DataLayout::NCDHW:
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35  m_ChannelsIndex = 1;
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36  m_DepthIndex = 2;
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37  m_HeightIndex = 3;
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38  m_WidthIndex = 4;
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39  break;
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40  default:
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41  throw armnn::InvalidArgumentException("Unknown DataLayout value: " +
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42  std::to_string(static_cast<int>(dataLayout)));
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43  }
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44 }
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References armnn::NCDHW, armnn::NCHW, armnn::NDHWC, and armnn::NHWC.

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Member Function Documentation

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◆ GetChannelsIndex()

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unsigned int GetChannelsIndex () const
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Definition at line 23 of file DataLayoutIndexed.hpp.

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23 { return m_ChannelsIndex; }
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Referenced by armnn::BatchNormImpl(), armnn::BatchToSpaceNd(), armnn::Convert1HWOtoMIHW(), armnn::Convolve(), armnn::Convolve3d(), armnn::DepthToSpace(), armnn::GetOffset(), DepthToSpaceLayer::InferOutputShapes(), ResizeLayer::InferOutputShapes(), Pooling2dLayer::InferOutputShapes(), Pooling3dLayer::InferOutputShapes(), armnn::InstanceNorm(), armnn::Offset(), armnn::Pooling2d(), armnn::Pooling3d(), armnn::Resize(), FuseBatchNorm< ConvLayer, ArmnnType, T >::Run(), armnn::SpaceToBatchNd(), armnn::SpaceToDepth(), armnn::TransposeConvolution2dImpl(), armnn::optimizations::pad_fold::TryFoldPadIntoLayer2d(), ResizeQueueDescriptor::Validate(), SpaceToBatchNdQueueDescriptor::Validate(), SpaceToDepthQueueDescriptor::Validate(), and DepthToSpaceQueueDescriptor::Validate().

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◆ GetDataLayout()

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armnn::DataLayout GetDataLayout () const
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Definition at line 22 of file DataLayoutIndexed.hpp.

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22 { return m_DataLayout; }
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Referenced by armnn::Convolve(), armnn::Convolve3d(), armnn::GetOffset(), armnn::Offset(), armnnUtils::operator==(), and armnn::Pooling2d().

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◆ GetDepthIndex()

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unsigned int GetDepthIndex () const
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Definition at line 26 of file DataLayoutIndexed.hpp.

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26 { return m_DepthIndex; }
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Referenced by armnn::Convolve3d(), Pooling3dLayer::InferOutputShapes(), Convolution3dLayer::InferOutputShapes(), and armnn::Pooling3d().

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◆ GetHeightIndex()

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unsigned int GetHeightIndex () const
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Definition at line 24 of file DataLayoutIndexed.hpp.

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24 { return m_HeightIndex; }
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Referenced by armnn::BatchNormImpl(), armnn::BatchToSpaceNd(), armnn_driver::ConvertPooling2d(), armnn::Convolve(), armnn::Convolve3d(), armnn::DepthToSpace(), armnn::GetOffset(), SpaceToBatchNdLayer::InferOutputShapes(), DepthToSpaceLayer::InferOutputShapes(), Pooling2dLayer::InferOutputShapes(), Pooling3dLayer::InferOutputShapes(), BatchToSpaceNdLayer::InferOutputShapes(), Convolution2dLayer::InferOutputShapes(), Convolution3dLayer::InferOutputShapes(), DepthwiseConvolution2dLayer::InferOutputShapes(), TransposeConvolution2dLayer::InferOutputShapes(), armnn::InstanceNorm(), armnn::Offset(), armnn::Pooling2d(), armnn::Pooling3d(), armnn::Resize(), FuseBatchNorm< ConvLayer, ArmnnType, T >::Run(), Convolution2dLayer::SerializeLayerParameters(), armnn::SpaceToBatchNd(), armnn::SpaceToDepth(), armnn::TransposeConvolution2dImpl(), armnn::optimizations::pad_fold::TryFoldPadIntoLayer2d(), SpaceToBatchNdQueueDescriptor::Validate(), SpaceToDepthQueueDescriptor::Validate(), and DepthToSpaceQueueDescriptor::Validate().

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◆ GetIndex()

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unsigned int GetIndex (const armnn::TensorShape & shape,
unsigned int batchIndex,
unsigned int channelIndex,
unsigned int heightIndex,
unsigned int widthIndex 
) const
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Offset the given indices appropriately depending on the data layout

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channelIndex stays unchanged

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widthIndex stays unchanged

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Get the value using the correct offset

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Definition at line 28 of file DataLayoutIndexed.hpp.

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31  {
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32  ARMNN_ASSERT( batchIndex < shape[0] || ( shape[0] == 0 && batchIndex == 0 ) );
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33  ARMNN_ASSERT( channelIndex < shape[m_ChannelsIndex] ||
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34  ( shape[m_ChannelsIndex] == 0 && channelIndex == 0) );
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35  ARMNN_ASSERT( heightIndex < shape[m_HeightIndex] ||
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36  ( shape[m_HeightIndex] == 0 && heightIndex == 0) );
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37  ARMNN_ASSERT( widthIndex < shape[m_WidthIndex] ||
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38  ( shape[m_WidthIndex] == 0 && widthIndex == 0) );
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39 
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40  /// Offset the given indices appropriately depending on the data layout
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41  switch (m_DataLayout)
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42  {
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43  case armnn::DataLayout::NHWC:
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44  batchIndex *= shape[1] * shape[2] * shape[3]; // batchIndex *= heightIndex * widthIndex * channelIndex
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45  heightIndex *= shape[m_WidthIndex] * shape[m_ChannelsIndex];
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46  widthIndex *= shape[m_ChannelsIndex];
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47  /// channelIndex stays unchanged
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48  break;
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49  case armnn::DataLayout::NCHW:
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50  default:
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51  batchIndex *= shape[1] * shape[2] * shape[3]; // batchIndex *= heightIndex * widthIndex * channelIndex
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52  channelIndex *= shape[m_HeightIndex] * shape[m_WidthIndex];
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53  heightIndex *= shape[m_WidthIndex];
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54  /// widthIndex stays unchanged
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55  break;
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56  }
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57 
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58  /// Get the value using the correct offset
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59  return batchIndex + channelIndex + heightIndex + widthIndex;
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60  }
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References ARMNN_ASSERT, armnn::NCHW, and armnn::NHWC.

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Referenced by armnn::BatchNormImpl(), TensorBufferArrayView< DataType >::Get(), armnn::InstanceNorm(), armnn::Resize(), and armnn::TransposeConvolution2dImpl().

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◆ GetWidthIndex()

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unsigned int GetWidthIndex () const
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Definition at line 25 of file DataLayoutIndexed.hpp.

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25 { return m_WidthIndex; }
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Referenced by armnn::BatchNormImpl(), armnn::BatchToSpaceNd(), armnn_driver::ConvertPooling2d(), armnn::Convolve(), armnn::Convolve3d(), armnn::DepthToSpace(), armnn::GetOffset(), SpaceToBatchNdLayer::InferOutputShapes(), DepthToSpaceLayer::InferOutputShapes(), Pooling2dLayer::InferOutputShapes(), Pooling3dLayer::InferOutputShapes(), BatchToSpaceNdLayer::InferOutputShapes(), Convolution2dLayer::InferOutputShapes(), Convolution3dLayer::InferOutputShapes(), DepthwiseConvolution2dLayer::InferOutputShapes(), TransposeConvolution2dLayer::InferOutputShapes(), armnn::InstanceNorm(), armnn::Offset(), armnn::Pooling2d(), armnn::Pooling3d(), armnn::Resize(), FuseBatchNorm< ConvLayer, ArmnnType, T >::Run(), Convolution2dLayer::SerializeLayerParameters(), armnn::SpaceToBatchNd(), armnn::SpaceToDepth(), armnn::TransposeConvolution2dImpl(), armnn::optimizations::pad_fold::TryFoldPadIntoLayer2d(), SpaceToBatchNdQueueDescriptor::Validate(), SpaceToDepthQueueDescriptor::Validate(), and DepthToSpaceQueueDescriptor::Validate().

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The documentation for this class was generated from the following files: +
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ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
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