From 6f92c8e9f8bb38dcf5dccf8deeff5112ecd8e37c Mon Sep 17 00:00:00 2001 From: Nikhil Raj Date: Wed, 22 Nov 2023 11:41:15 +0000 Subject: Update Doxygen for 23.11 Signed-off-by: Nikhil Raj Change-Id: I47cd933f5002cb94a73aa97689d7b3d9c93cb849 --- 23.11/_avg_pool2_d_ignore_value_operator_8cpp.html | 302 +++++++++++++++++++++ 1 file changed, 302 insertions(+) create mode 100644 23.11/_avg_pool2_d_ignore_value_operator_8cpp.html (limited to '23.11/_avg_pool2_d_ignore_value_operator_8cpp.html') diff --git a/23.11/_avg_pool2_d_ignore_value_operator_8cpp.html b/23.11/_avg_pool2_d_ignore_value_operator_8cpp.html new file mode 100644 index 0000000000..535fa85ac5 --- /dev/null +++ b/23.11/_avg_pool2_d_ignore_value_operator_8cpp.html @@ -0,0 +1,302 @@ + + + + + + + + +Arm NN: src/backends/tosaCommon/operatorMappings/AvgPool2DIgnoreValueOperator.cpp File Reference + + + + + + + + + + + + + + + + +
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+  23.11 +
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+Functions
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AvgPool2DIgnoreValueOperator.cpp File Reference
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#include "Pooling2DOperator.hpp"
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+Include dependency graph for AvgPool2DIgnoreValueOperator.cpp:
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Go to the source code of this file.

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+Functions

TosaSerializationBasicBlock * ConvertAvgPool2DIgnoreValueToTosaOperator (const Layer *layer, const std::vector< const TensorInfo * > &inputs, const std::vector< const TensorInfo * > &outputs, const Pooling2dDescriptor *poolDescriptor)
 
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Function Documentation

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◆ ConvertAvgPool2DIgnoreValueToTosaOperator()

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TosaSerializationBasicBlock* ConvertAvgPool2DIgnoreValueToTosaOperator (const Layer * layer,
const std::vector< const TensorInfo * > & inputs,
const std::vector< const TensorInfo * > & outputs,
const Pooling2dDescriptor * poolDescriptor 
)
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Definition at line 8 of file AvgPool2DIgnoreValueOperator.cpp.

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12 {
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13  std::string padInputName = std::string("input0_");
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14  std::string padOutputName = std::string("intermediate0_") + GetUniqueTosaMappingID();
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15  std::string poolOutputName = std::string("output0_");
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16  std::string blockName = std::string("Op_AVG_POOL2D_block_") + GetUniqueTosaMappingID();
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17 
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18  // If a layer is present then the block will be used for execution, so input and output names need to be determined
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19  // using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
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20  if(layer != nullptr)
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21  {
+
22  // Get the layers connected to the input slots and determine unique tensors names.
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23  Layer& connectedInputLayer = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
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24  padInputName = GenerateUniqueName(connectedInputLayer, 0);
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25 
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26  // Determine unique output tensor name.
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27  poolOutputName = GenerateUniqueOutputName(*layer, 0);
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28  }
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29 
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30  std::vector<int> paddings;
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31  if (poolDescriptor->m_DataLayout == DataLayout::NHWC)
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32  {
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33  paddings = {0,
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34  0,
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35  static_cast<int>(poolDescriptor->m_PadTop),
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36  static_cast<int>(poolDescriptor->m_PadBottom),
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37  static_cast<int>(poolDescriptor->m_PadLeft),
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38  static_cast<int>(poolDescriptor->m_PadRight),
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39  0,
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40  0
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41  };
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42  }
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43  else
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44  {
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45  paddings = {0,
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46  0,
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47  0,
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48  0,
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49  static_cast<int>(poolDescriptor->m_PadTop),
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50  static_cast<int>(poolDescriptor->m_PadBottom),
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51  static_cast<int>(poolDescriptor->m_PadLeft),
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52  static_cast<int>(poolDescriptor->m_PadRight)
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53  };
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54  }
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55 
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56  TosaPadAttribute padAttribute(paddings, 0, 0.0f);
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57  auto* opPad = new TosaSerializationOperator(Op_PAD,
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58  Attribute_PadAttribute,
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59  &padAttribute,
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60  {padInputName},
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61  {padOutputName});
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62 
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63  std::vector<int> pad = {0, 0, 0, 0};
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64  std::vector<int> kernel = {static_cast<int>(poolDescriptor->m_PoolHeight),
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65  static_cast<int>(poolDescriptor->m_PoolWidth)};
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66  std::vector<int> stride = {static_cast<int>(poolDescriptor->m_StrideY),
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67  static_cast<int>(poolDescriptor->m_StrideX)};
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68  TosaPoolAttribute poolAttribute(pad, kernel, stride, 0, 0, ArmNNToDType(inputs[0]->GetDataType()));
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69 
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70  auto* opPool = new TosaSerializationOperator(Op_AVG_POOL2D,
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71  Attribute_PoolAttribute,
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72  &poolAttribute,
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73  {padOutputName},
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74  {poolOutputName});
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75 
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76  std::vector<TosaSerializationTensor*> tensors;
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77 
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78  std::vector<int32_t> inputShape = GetTosaTensorShape(inputs[0]->GetShape());
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79  DType inputDType = ArmNNToDType(inputs[0]->GetDataType());
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80 
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81  // Only add input tensors if connected layer is an input layer.
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82  // As intermediate or constant tensors will be created separately.
+
83  // There also can't be duplicate tensor.
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84  if(padInputName.find("input0_") != std::string::npos)
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85  {
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86  tensors.push_back(new TosaSerializationTensor(padInputName, inputShape, inputDType, {}));
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87  }
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88 
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89  std::vector<int32_t> outputShape = GetTosaTensorShape(outputs[0]->GetShape());
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90  DType outputDType = ArmNNToDType(outputs[0]->GetDataType());
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91 
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92  std::vector<int32_t> intermediateShape;
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93  if (poolDescriptor->m_DataLayout == DataLayout::NHWC)
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94  {
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95  intermediateShape = {inputShape[0],
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96  inputShape[1] + paddings[2] + paddings[3],
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97  inputShape[2] + paddings[4] + paddings[5],
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98  inputShape[3]};
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99  }
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100  else
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101  {
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102  intermediateShape = {inputShape[0],
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103  inputShape[1],
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104  inputShape[2] + paddings[4] + paddings[5],
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105  inputShape[3] + paddings[6] + paddings[7]};
+
106  }
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107 
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108  tensors.push_back(new TosaSerializationTensor(padOutputName, intermediateShape, inputDType, {}));
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109  tensors.push_back(new TosaSerializationTensor(poolOutputName, outputShape, outputDType, {}));
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110 
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111  // operatorInputNames/operatorOutputNames ends up being the same as
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112  // blockInputNames/blockOutputNames for one-to-one ArmNN to TOSA mappings
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113  return new TosaSerializationBasicBlock(blockName, // name
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114  mainName, // region name
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115  {opPad, opPool}, // operators
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116  tensors, // tensors
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117  {padInputName}, // inputs
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118  {poolOutputName}); // outputs
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119 }
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References ArmNNToDType(), GenerateUniqueName(), GenerateUniqueOutputName(), InputSlot::GetConnectedOutputSlot(), Layer::GetInputSlot(), OutputSlot::GetOwningLayer(), GetTosaTensorShape(), GetUniqueTosaMappingID(), Pooling2dDescriptor::m_DataLayout, Pooling2dDescriptor::m_PadBottom, Pooling2dDescriptor::m_PadLeft, Pooling2dDescriptor::m_PadRight, Pooling2dDescriptor::m_PadTop, Pooling2dDescriptor::m_PoolHeight, Pooling2dDescriptor::m_PoolWidth, Pooling2dDescriptor::m_StrideX, and Pooling2dDescriptor::m_StrideY.

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Referenced by GetTosaMapping().

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armnn::Pooling2dDescriptor::m_PoolHeight
uint32_t m_PoolHeight
Pooling height value.
Definition: Descriptors.hpp:417
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armnn::Pooling2dDescriptor::m_StrideY
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
Definition: Descriptors.hpp:421
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armnn::Pooling2dDescriptor::m_PadTop
uint32_t m_PadTop
Padding top value in the height dimension.
Definition: Descriptors.hpp:411
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armnn::Pooling2dDescriptor::m_PoolWidth
uint32_t m_PoolWidth
Pooling width value.
Definition: Descriptors.hpp:415
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armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
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mainName
const std::string mainName
Definition: TosaOperatorUtils.hpp:19
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armnn::OutputSlot::GetOwningLayer
Layer & GetOwningLayer() const
Definition: Layer.hpp:132
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armnn::Pooling2dDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:427
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ArmNNToDType
DType ArmNNToDType(const DataType &type)
Definition: TosaOperatorUtils.hpp:22
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armnn::Pooling2dDescriptor::m_PadBottom
uint32_t m_PadBottom
Padding bottom value in the height dimension.
Definition: Descriptors.hpp:413
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armnn::Pooling2dDescriptor::m_PadRight
uint32_t m_PadRight
Padding right value in the width dimension.
Definition: Descriptors.hpp:409
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GenerateUniqueOutputName
std::string GenerateUniqueOutputName(const Layer &layer, uint32_t layerSlot)
Definition: TosaOperatorUtils.hpp:82
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armnn::Pooling2dDescriptor::m_PadLeft
uint32_t m_PadLeft
Padding left value in the width dimension.
Definition: Descriptors.hpp:407
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armnn::Pooling2dDescriptor::m_StrideX
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
Definition: Descriptors.hpp:419
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GenerateUniqueName
std::string GenerateUniqueName(const Layer &layer, uint32_t layerSlot)
Definition: TosaOperatorUtils.hpp:63
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GetTosaTensorShape
std::vector< int32_t > GetTosaTensorShape(const TensorShape &shape)
Definition: TosaOperatorUtils.hpp:52
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armnn::InputSlot::GetConnectedOutputSlot
const OutputSlot * GetConnectedOutputSlot() const
Definition: Layer.hpp:56
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GetUniqueTosaMappingID
std::string GetUniqueTosaMappingID()
Definition: TosaOperatorUtils.hpp:100
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