From 6940dd720ebb6b3d1df8ca203ab696daefe58189 Mon Sep 17 00:00:00 2001 From: Jim Flynn Date: Fri, 20 Mar 2020 12:25:56 +0000 Subject: renamed Documentation folder 20.02 and added .nojekyll file Signed-off-by: Jim Flynn --- ...orkloads_2_space_to_batch_n_d_8cpp_source.xhtml | 136 +++++++++++++++++++++ 1 file changed, 136 insertions(+) create mode 100644 20.02/backends_2reference_2workloads_2_space_to_batch_n_d_8cpp_source.xhtml (limited to '20.02/backends_2reference_2workloads_2_space_to_batch_n_d_8cpp_source.xhtml') diff --git a/20.02/backends_2reference_2workloads_2_space_to_batch_n_d_8cpp_source.xhtml b/20.02/backends_2reference_2workloads_2_space_to_batch_n_d_8cpp_source.xhtml new file mode 100644 index 0000000000..b9c618d3c9 --- /dev/null +++ b/20.02/backends_2reference_2workloads_2_space_to_batch_n_d_8cpp_source.xhtml @@ -0,0 +1,136 @@ + + + + + + + + + + + + + +ArmNN: src/backends/reference/workloads/SpaceToBatchNd.cpp Source File + + + + + + + + + + + + + + + + +
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SpaceToBatchNd.cpp
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1 //
2 // Copyright © 2017 Arm Ltd. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "SpaceToBatchNd.hpp"
7 
8 #include <armnnUtils/DataLayoutIndexed.hpp>
9 
10 using namespace armnnUtils;
11 
12 namespace armnn
13 {
14 
15 unsigned int GetOffset(const TensorShape& shape,
16  unsigned int b,
17  unsigned int h,
18  unsigned int w,
19  unsigned int c,
20  const DataLayoutIndexed& dataLayout)
21 {
22  if (dataLayout.GetDataLayout() == DataLayout::NHWC)
23  {
24  return ((b * shape[dataLayout.GetHeightIndex()] + h) * shape[dataLayout.GetWidthIndex()] + w) *
25  shape[dataLayout.GetChannelsIndex()] + c;
26  }
27  else
28  {
29  return ((b * shape[dataLayout.GetChannelsIndex()] + c) * shape[dataLayout.GetHeightIndex()] + h) *
30  shape[dataLayout.GetWidthIndex()] + w;
31  }
32 }
33 
34 void SpaceToBatchNd(const TensorInfo& inputInfo,
35  const TensorInfo& outputInfo,
36  const SpaceToBatchNdDescriptor& params,
37  Decoder<float>& inputData,
38  Encoder<float>& outputData)
39 {
40  DataLayoutIndexed dataLayout = params.m_DataLayout;
41 
42  const TensorShape& inputShape = inputInfo.GetShape();
43  const TensorShape& outputShape = outputInfo.GetShape();
44 
45  const unsigned int channels = inputShape[dataLayout.GetChannelsIndex()];
46 
47  const unsigned int inputBatchSize = inputShape[0];
48  const unsigned int inputHeight = inputShape[dataLayout.GetHeightIndex()];
49  const unsigned int inputWidth = inputShape[dataLayout.GetWidthIndex()];
50 
51  const unsigned int outputBatchSize = outputShape[0];
52  const unsigned int outputHeight = outputShape[dataLayout.GetHeightIndex()];
53  const unsigned int outputWidth = outputShape[dataLayout.GetWidthIndex()];
54 
55  const unsigned int blockHeight = params.m_BlockShape[0];
56  const unsigned int blockWidth = params.m_BlockShape[1];
57 
58  const unsigned int paddingTop = params.m_PadList[0].first;
59  const unsigned int paddingLeft = params.m_PadList[1].first;
60 
61  for (unsigned int outB = 0; outB < outputBatchSize; outB++)
62  {
63  unsigned int inB = outB % inputBatchSize;
64 
65  unsigned int shiftW = (outB / inputBatchSize) % blockWidth;
66  unsigned int shiftH = (outB / inputBatchSize) / blockWidth;
67 
68  for (unsigned int outH = 0; outH < outputHeight; outH++)
69  {
70  for (unsigned int outW = 0; outW < outputWidth; outW++)
71  {
72  if (outH * blockHeight + shiftH < paddingTop ||
73  outH * blockHeight + shiftH >= paddingTop + inputHeight ||
74  outW * blockWidth + shiftW < paddingLeft ||
75  outW * blockWidth + shiftW >= paddingLeft + inputWidth)
76  {
77  for (unsigned int c = 0; c < channels; c++)
78  {
79  unsigned int outOffset = GetOffset(outputShape,
80  outB,
81  outH,
82  outW,
83  c,
84  dataLayout);
85  outputData += outOffset;
86  outputData.Set(0);
87  outputData -= outOffset;
88  }
89  }
90  else
91  {
92  for (unsigned int c = 0; c < channels; c++)
93  {
94  unsigned int inOffset = GetOffset(inputShape,
95  inB,
96  (outH * blockHeight + shiftH) - paddingTop,
97  (outW * blockWidth + shiftW) - paddingLeft,
98  c,
99  dataLayout);
100 
101  unsigned int outOffset = GetOffset(outputShape,
102  outB,
103  outH,
104  outW,
105  c,
106  dataLayout);
107 
108  outputData += outOffset;
109  inputData += inOffset;
110  outputData.Set(inputData.Get());
111  inputData -= inOffset;
112  outputData -= outOffset;
113  }
114  }
115  }
116  }
117  }
118 }
119 
120 void SpaceToBatchNd(const TensorInfo& inputInfo,
121  const TensorInfo& outputInfo,
122  const SpaceToBatchNdDescriptor& params,
123  Decoder<float>& inputData,
124  Encoder<float>& outData);
125 
126 } //namespace armnn
DataLayoutIndexed.hpp
+
armnnUtils::DataLayoutIndexed::GetWidthIndex
unsigned int GetWidthIndex() const
Definition: DataLayoutIndexed.hpp:25
+
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:88
+ +
armnn::Encoder::Set
virtual void Set(IType right)=0
+ +
armnn
Copyright (c) 2020 ARM Limited.
Definition: 00_introduction.dox:25
+ +
armnn::SpaceToBatchNdDescriptor::m_PadList
std::vector< std::pair< unsigned int, unsigned int > > m_PadList
Specifies the padding values for the input dimension: heightPad{top, bottom} widthPad{left, right}.
Definition: Descriptors.hpp:804
+
armnnUtils::DataLayoutIndexed::GetHeightIndex
unsigned int GetHeightIndex() const
Definition: DataLayoutIndexed.hpp:24
+
armnn::SpaceToBatchNdDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:806
+
armnn::Decoder::Get
virtual IType Get() const =0
+
armnn::GetOffset
unsigned int GetOffset(const TensorShape &shape, unsigned int b, unsigned int h, unsigned int w, unsigned int c, const DataLayoutIndexed &dataLayout)
Definition: SpaceToBatchNd.cpp:15
+
SpaceToBatchNd.hpp
+
armnnUtils::DataLayoutIndexed
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout...
Definition: DataLayoutIndexed.hpp:17
+
armnnUtils::DataLayoutIndexed::GetDataLayout
armnn::DataLayout GetDataLayout() const
Definition: DataLayoutIndexed.hpp:22
+
armnn::SpaceToBatchNdDescriptor::m_BlockShape
std::vector< unsigned int > m_BlockShape
Block shape value.
Definition: Descriptors.hpp:801
+
armnn::SpaceToBatchNd
void SpaceToBatchNd(const TensorInfo &inputInfo, const TensorInfo &outputInfo, const SpaceToBatchNdDescriptor &params, Decoder< float > &inputData, Encoder< float > &outputData)
Definition: SpaceToBatchNd.cpp:34
+
armnn::SpaceToBatchNdDescriptor
A SpaceToBatchNdDescriptor for the SpaceToBatchNdLayer.
Definition: Descriptors.hpp:778
+ +
armnnUtils::DataLayoutIndexed::GetChannelsIndex
unsigned int GetChannelsIndex() const
Definition: DataLayoutIndexed.hpp:23
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