ArmNN
 24.02
AvgPool2DIgnoreValueOperator.cpp File Reference
Include dependency graph for AvgPool2DIgnoreValueOperator.cpp:

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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)
 

Function Documentation

◆ ConvertAvgPool2DIgnoreValueToTosaOperator()

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

Definition at line 8 of file AvgPool2DIgnoreValueOperator.cpp.

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

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.

Referenced by GetTosaMapping().

armnn::Pooling2dDescriptor::m_PoolHeight
uint32_t m_PoolHeight
Pooling height value.
Definition: Descriptors.hpp:417
armnn::Pooling2dDescriptor::m_StrideY
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
Definition: Descriptors.hpp:421
armnn::Pooling2dDescriptor::m_PadTop
uint32_t m_PadTop
Padding top value in the height dimension.
Definition: Descriptors.hpp:411
armnn::Pooling2dDescriptor::m_PoolWidth
uint32_t m_PoolWidth
Pooling width value.
Definition: Descriptors.hpp:415
armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
armnn::Layer
Definition: Layer.hpp:230
mainName
const std::string mainName
Definition: TosaOperatorUtils.hpp:19
armnn::OutputSlot::GetOwningLayer
Layer & GetOwningLayer() const
Definition: Layer.hpp:132
armnn::Pooling2dDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:427
ArmNNToDType
DType ArmNNToDType(const DataType &type)
Definition: TosaOperatorUtils.hpp:22
armnn::Pooling2dDescriptor::m_PadBottom
uint32_t m_PadBottom
Padding bottom value in the height dimension.
Definition: Descriptors.hpp:413
armnn::Pooling2dDescriptor::m_PadRight
uint32_t m_PadRight
Padding right value in the width dimension.
Definition: Descriptors.hpp:409
GenerateUniqueOutputName
std::string GenerateUniqueOutputName(const Layer &layer, uint32_t layerSlot)
Definition: TosaOperatorUtils.hpp:82
armnn::Pooling2dDescriptor::m_PadLeft
uint32_t m_PadLeft
Padding left value in the width dimension.
Definition: Descriptors.hpp:407
armnn::Pooling2dDescriptor::m_StrideX
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
Definition: Descriptors.hpp:419
GenerateUniqueName
std::string GenerateUniqueName(const Layer &layer, uint32_t layerSlot)
Definition: TosaOperatorUtils.hpp:63
GetTosaTensorShape
std::vector< int32_t > GetTosaTensorShape(const TensorShape &shape)
Definition: TosaOperatorUtils.hpp:52
armnn::InputSlot::GetConnectedOutputSlot
const OutputSlot * GetConnectedOutputSlot() const
Definition: Layer.hpp:56
GetUniqueTosaMappingID
std::string GetUniqueTosaMappingID()
Definition: TosaOperatorUtils.hpp:100