ArmNN
 24.08
DepthwiseConvolution2dLayer.cpp
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1 //
2 // Copyright © 2017-2024 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
7 #include "LayerCloneBase.hpp"
8 
9 #include <armnn/TypesUtils.hpp>
10 
12 
15 
16 #include <string>
17 
18 using namespace armnnUtils;
19 
20 namespace armnn
21 {
22 
24  const char* name)
26 {
27 }
28 
30 {
31  const std::vector<TensorShape>& inputShapes =
32  {
35  };
36  const TensorShape filterShape = inputShapes[1];
37  unsigned int inputChannels = filterShape[1];
38  unsigned int filterWidth = filterShape[3];
39  unsigned int filterHeight = filterShape[2];
40  unsigned int depthMultiplier = filterShape[0];
41 
42  fn("FilterWidth",std::to_string(filterWidth));
43  fn("FilterHeight",std::to_string(filterHeight));
44  fn("DepthMultiplier",std::to_string(depthMultiplier));
45  fn("InputChannels",std::to_string(inputChannels));
46 
48 }
49 
50 std::unique_ptr<IWorkload> DepthwiseConvolution2dLayer::CreateWorkload(const IWorkloadFactory& factory) const
51 {
53  SetAdditionalInfo(descriptor);
54 
55  return factory.CreateWorkload(LayerType::DepthwiseConvolution2d, descriptor, PrepInfoAndDesc(descriptor));
56 }
57 
59 {
60  auto layer = CloneBase<DepthwiseConvolution2dLayer>(graph, m_Param, GetName());
61  return std::move(layer);
62 }
63 
64 std::vector<TensorShape>
65 DepthwiseConvolution2dLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
66 {
67  if (inputShapes.size() != 2)
68  {
69  throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
70  "\" - should be \"2\".");
71  }
72 
73  const TensorShape& inputShape = inputShapes[0];
74  const TensorShape& filterShape = inputShapes[1];
75 
76  if (inputShape.GetNumDimensions() != 4)
77  {
78  throw armnn::Exception("Convolutions will always have 4D input.");
79  }
80 
81  if (m_Param.m_StrideX == 0)
82  {
83  throw armnn::Exception("m_StrideX cannot be 0.");
84  }
85 
86  if (m_Param.m_StrideY == 0)
87  {
88  throw armnn::Exception("m_StrideY cannot be 0.");
89  }
90 
91 
92  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
93 
94  unsigned int inputBatchSize = inputShape[0];
95  unsigned int inputHeight = inputShape[dataLayoutIndex.GetHeightIndex()];
96  unsigned int inputWidth = inputShape[dataLayoutIndex.GetWidthIndex()];
97 
98  // Expected filter shape: [ 1, H, W, O ] - This shape does NOT depend on the data layout
99  // Namely: [ 1, filter height, filter width, output channels ]
100 
101  unsigned int filterHeight = filterShape[1];
102  unsigned int dilatedFilterHeight = filterHeight + (m_Param.m_DilationY - 1) * (filterHeight - 1);
103  unsigned int readHeight = (inputHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - dilatedFilterHeight;
104  unsigned int outputHeight = 1 + (readHeight / m_Param.m_StrideY);
105 
106  unsigned int filterWidth = filterShape[2];
107  unsigned int dilatedFilterWidth = filterWidth + (m_Param.m_DilationX - 1) * (filterWidth - 1);
108  unsigned int readWidth = (inputWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - dilatedFilterWidth;
109  unsigned int outputWidth = 1 + (readWidth / m_Param.m_StrideX);
110 
111  unsigned int outputChannels = filterShape[3];
112  unsigned int outputBatchSize = inputBatchSize;
113 
115  TensorShape{ outputBatchSize, outputHeight, outputWidth, outputChannels } :
116  TensorShape{ outputBatchSize, outputChannels, outputHeight, outputWidth };
117 
118  return std::vector<TensorShape>{ tensorShape };
119 }
120 
122 {
124 
125  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
126 
128 
129  if (!GetInputSlot(1).GetConnection())
130  {
131  throw armnn::LayerValidationException("DepthwiseConvolution2dLayer: Weights data should not be null.");
132  }
133 
134  auto inferredShapes = InferOutputShapes({
137  });
138 
139  if (inferredShapes.size() != 1)
140  {
141  throw armnn::LayerValidationException("inferredShapes has "
142  + std::to_string(inferredShapes.size()) +
143  " elements - should only have 1.");
144  }
145 
146  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "DepthwiseConvolution2dLayer");
147 }
148 
150 {
152  return tensors;
153 }
154 
156 {
157  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
158 }
159 
160 } // namespace armnn
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:100
armnn::DataLayout::NHWC
@ NHWC
armnn::LayerWithParameters::SerializeLayerParameters
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string (currently used in DotSerializer and company).
Definition: LayerWithParameters.hpp:23
armnn::DepthwiseConvolution2dLayer
This layer represents a depthwise convolution 2d operation.
Definition: DepthwiseConvolution2dLayer.hpp:15
TypesUtils.hpp
armnn::DepthwiseConvolution2dDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NCHW, NHWC).
Definition: Descriptors.hpp:710
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
armnn::DepthwiseConvolution2dLayer::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the DepthwiseConvolution2d type.
Definition: DepthwiseConvolution2dLayer.cpp:50
armnnUtils::DataLayoutIndexed
Provides access to the appropriate indexes for Channels, Height and Width based on DataLayout.
Definition: DataLayoutIndexed.hpp:17
armnn::Layer::ValidateAndCopyShape
void ValidateAndCopyShape(const TensorShape &outputShape, const TensorShape &inferredShape, const ShapeInferenceMethod shapeInferenceMethod, const std::string &layerName, const unsigned int outputSlotIndex=0)
Definition: Layer.cpp:457
armnn::DepthwiseConvolution2dDescriptor::m_PadLeft
uint32_t m_PadLeft
Padding left value in the width dimension.
Definition: Descriptors.hpp:692
armnn::Layer::GetOutputSlot
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:339
armnn::IStrategy
Definition: IStrategy.hpp:16
armnn::DepthwiseConvolution2dDescriptor::m_StrideY
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
Definition: Descriptors.hpp:702
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::LayerWithParameters< DepthwiseConvolution2dDescriptor >::GetParameters
const DepthwiseConvolution2dDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
WorkloadFactory.hpp
armnn::LayerWithParameters
Definition: LayerWithParameters.hpp:14
armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
armnnUtils::DataLayoutIndexed::GetHeightIndex
unsigned int GetHeightIndex() const
Definition: DataLayoutIndexed.hpp:24
armnn::IConnectableLayer::ImmutableConstantTensors
std::vector< std::reference_wrapper< const std::shared_ptr< ConstTensorHandle > >> ImmutableConstantTensors
Definition: INetwork.hpp:141
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:614
armnn::LayerWithParameters< DepthwiseConvolution2dDescriptor >::GetConnectedConstantAsInputTensors
Layer::ImmutableConstantTensors GetConnectedConstantAsInputTensors() const
Definition: LayerWithParameters.hpp:59
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::LayerWithParameters< DepthwiseConvolution2dDescriptor >::m_Param
DepthwiseConvolution2dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::TensorShape::GetNumDimensions
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174
armnn::DepthwiseConvolution2dDescriptor::m_DilationY
uint32_t m_DilationY
Dilation factor value for height dimension.
Definition: Descriptors.hpp:706
armnn::LayerWithParameters< DepthwiseConvolution2dDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::DepthwiseConvolution2dLayer::Clone
DepthwiseConvolution2dLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: DepthwiseConvolution2dLayer.cpp:58
armnn::LayerValidationException
Definition: Exceptions.hpp:105
armnn::IWorkloadFactory
Definition: WorkloadFactory.hpp:22
armnnUtils
Definition: CompatibleTypes.hpp:10
armnn::DepthwiseConvolution2dLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of DepthwiseConvolution2dLayer.
Definition: DepthwiseConvolution2dLayer.cpp:121
armnn::DepthwiseConvolution2dDescriptor::m_PadRight
uint32_t m_PadRight
Padding right value in the width dimension.
Definition: Descriptors.hpp:694
armnn::ParameterStringifyFunction
std::function< void(const std::string &name, const std::string &value)> ParameterStringifyFunction
Definition: SerializeLayerParameters.hpp:14
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:526
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:303
armnn::DepthwiseConvolution2dLayer::GetConstantTensorsByRef
ImmutableConstantTensors GetConstantTensorsByRef() const override
Retrieve the handles to the constant values connected to the layer.
Definition: DepthwiseConvolution2dLayer.cpp:149
armnn::Exception
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:46
armnnUtils::DataLayoutIndexed::GetWidthIndex
unsigned int GetWidthIndex() const
Definition: DataLayoutIndexed.hpp:25
armnn::DepthwiseConvolution2dLayer::ExecuteStrategy
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Definition: DepthwiseConvolution2dLayer.cpp:155
armnn::DepthwiseConvolution2dDescriptor::m_PadBottom
uint32_t m_PadBottom
Padding bottom value in the height dimension.
Definition: Descriptors.hpp:698
armnn::DepthwiseConvolution2dQueueDescriptor
Depthwise Convolution 2D layer workload data.
Definition: WorkloadData.hpp:234
armnn::GetNumInputs
uint32_t GetNumInputs(bool biasEnabled)
Definition: Descriptors.cpp:455
armnn::DepthwiseConvolution2dLayer::InferOutputShapes
std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override
By default returns inputShapes if the number of inputs are equal to number of outputs,...
Definition: DepthwiseConvolution2dLayer.cpp:65
armnn::LayerType::DepthwiseConvolution2d
@ DepthwiseConvolution2d
TensorHandle.hpp
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn
Copyright (c) 2021 ARM Limited and Contributors.
Definition: 01_00_quick_start.dox:6
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:410
armnn::DepthwiseConvolution2dDescriptor
A DepthwiseConvolution2dDescriptor for the DepthwiseConvolution2dLayer.
Definition: Descriptors.hpp:659
armnn::DepthwiseConvolution2dDescriptor::m_DilationX
uint32_t m_DilationX
Dilation factor value for width dimension.
Definition: Descriptors.hpp:704
armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:441
armnn::LayerType
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below.
Definition: Types.hpp:491
DataLayoutIndexed.hpp
armnn::Graph
Definition: Graph.hpp:30
armnn::IWorkloadFactory::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const =0
Backends should implement their own CreateWorkload function with a switch statement.
armnn::IStrategy::ExecuteStrategy
virtual void ExecuteStrategy(const IConnectableLayer *layer, const armnn::BaseDescriptor &descriptor, const std::vector< armnn::ConstTensor > &constants, const char *name, const armnn::LayerBindingId id=0)=0
LayerCloneBase.hpp
DepthwiseConvolution2dLayer.hpp
armnn::DepthwiseConvolution2dLayer::SerializeLayerParameters
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string.
Definition: DepthwiseConvolution2dLayer.cpp:29
armnn::DepthwiseConvolution2dLayer::DepthwiseConvolution2dLayer
DepthwiseConvolution2dLayer(const DepthwiseConvolution2dDescriptor &param, const char *name)
Constructor to create a DepthwiseConvolution2dLayer.
Definition: DepthwiseConvolution2dLayer.cpp:23
armnn::DepthwiseConvolution2dDescriptor::GetNumInputs
uint32_t GetNumInputs() const
Get the number of views/inputs.
Definition: Descriptors.cpp:480
armnn::DepthwiseConvolution2dDescriptor::m_StrideX
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
Definition: Descriptors.hpp:700
armnn::DepthwiseConvolution2dDescriptor::m_PadTop
uint32_t m_PadTop
Padding top value in the height dimension.
Definition: Descriptors.hpp:696