ArmNN
 24.08
Convolution3dLayer.cpp
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1 //
2 // Copyright © 2021-2024 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "Convolution3dLayer.hpp"
7 #include "LayerCloneBase.hpp"
8 
10 
12 
13 using namespace armnnUtils;
14 
15 namespace armnn
16 {
17 
19  : LayerWithParameters(param.GetNumInputs(), 1, LayerType::Convolution3d, param, name)
20 {
21 }
22 
24 {
25  const std::vector<TensorShape>& inputShapes =
26  {
29  };
30 
31  // Conv3d Filter Layout: [D,H,W,I,O]
32  const TensorShape filterShape = inputShapes[1];
33  unsigned int filterDepth = filterShape[0];
34  unsigned int filterHeight = filterShape[1];
35  unsigned int filterWidth = filterShape[2];
36  unsigned int inChannels = filterShape[3];
37  unsigned int outChannels = filterShape[4];
38 
39  fn("FilterDepth",std::to_string(filterDepth));
40  fn("FilterHeight",std::to_string(filterHeight));
41  fn("FilterWidth",std::to_string(filterWidth));
42  fn("InputChannels",std::to_string(inChannels));
43  fn("OutputChannels",std::to_string(outChannels));
44 
46 }
47 
48 std::unique_ptr<IWorkload> Convolution3dLayer::CreateWorkload(const IWorkloadFactory& factory) const
49 {
51  SetAdditionalInfo(descriptor);
52 
53  return factory.CreateWorkload(LayerType::Convolution3d, descriptor, PrepInfoAndDesc(descriptor));
54 }
55 
57 {
58  auto layer = CloneBase<Convolution3dLayer>(graph, m_Param, GetName());
59  return std::move(layer);
60 }
61 
62 std::vector<TensorShape> Convolution3dLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
63 {
64  if (inputShapes.size() != 2)
65  {
66  throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
67  "\" - should be \"2\".");
68  }
69 
70  const TensorShape& inputShape = inputShapes[0];
71  const TensorShape& filterShape = inputShapes[1];
72 
73  if (inputShape.GetNumDimensions() != 5)
74  {
75  throw armnn::Exception("Convolutions will always have 5D input.");
76  }
77 
78  if (m_Param.m_StrideX == 0)
79  {
80  throw armnn::Exception("m_StrideX cannot be 0.");
81  }
82 
83  if (m_Param.m_StrideY == 0)
84  {
85  throw armnn::Exception("m_StrideY cannot be 0.");
86  }
87 
88  if (m_Param.m_StrideZ == 0)
89  {
90  throw armnn::Exception("m_StrideZ cannot be 0.");
91  }
92 
93  DataLayoutIndexed dataLayoutIndex(m_Param.m_DataLayout);
94 
95  unsigned int inWidth = inputShape[dataLayoutIndex.GetWidthIndex()];
96  unsigned int inHeight = inputShape[dataLayoutIndex.GetHeightIndex()];
97  unsigned int inDepth = inputShape[dataLayoutIndex.GetDepthIndex()];
98  unsigned int inBatchSize = inputShape[0];
99 
100  // Conv3d Filter Layout: [D,H,W,I,O]
101  unsigned int filterDepth = filterShape[0];
102  unsigned int dilatedFilterDepth = filterDepth + (m_Param.m_DilationZ - 1) * (filterDepth - 1);
103  unsigned int readDepth = (inDepth + m_Param.m_PadFront + m_Param.m_PadBack) - dilatedFilterDepth;
104  unsigned int outDepth = 1 + (readDepth / m_Param.m_StrideZ);
105 
106  unsigned int filterHeight = filterShape[1];
107  unsigned int dilatedFilterHeight = filterHeight + (m_Param.m_DilationY - 1) * (filterHeight - 1);
108  unsigned int readHeight = (inHeight + m_Param.m_PadTop + m_Param.m_PadBottom) - dilatedFilterHeight;
109  unsigned int outHeight = 1 + (readHeight / m_Param.m_StrideY);
110 
111  unsigned int filterWidth = filterShape[2];
112  unsigned int dilatedFilterWidth = filterWidth + (m_Param.m_DilationX - 1) * (filterWidth - 1);
113  unsigned int readWidth = (inWidth + m_Param.m_PadLeft + m_Param.m_PadRight) - dilatedFilterWidth;
114  unsigned int outWidth = 1 + (readWidth / m_Param.m_StrideX);
115 
116  unsigned int outChannels = filterShape[4];
117  unsigned int outBatchSize = inBatchSize;
118 
120  TensorShape( { outBatchSize, outDepth, outHeight, outWidth, outChannels } ) :
121  TensorShape( { outBatchSize, outChannels, outDepth, outHeight, outWidth });
122 
123  return std::vector<TensorShape>({ tensorShape });
124 }
125 
127 {
129 
130  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
131 
133 
134  if (!GetInputSlot(1).GetConnection())
135  {
136  throw armnn::LayerValidationException("Convolution3dLayer: Weights should be connected to input slot 1.");
137  }
138 
139  auto inferredShapes = InferOutputShapes({
142 
143  if (inferredShapes.size() != 1)
144  {
145  throw armnn::LayerValidationException("inferredShapes has "
146  + std::to_string(inferredShapes.size()) +
147  " elements - should only have 1.");
148  }
149 
150  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "Convolution3dLayer");
151 }
152 
154 {
155  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
156 }
157 
158 } // namespace armnn
armnn::Convolution3dLayer::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: Convolution3dLayer.cpp:62
armnn::Convolution3dDescriptor::GetNumInputs
uint32_t GetNumInputs() const
Get the number of views/inputs.
Definition: Descriptors.cpp:465
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:100
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::Convolution3dDescriptor::m_PadFront
uint32_t m_PadFront
Padding front value in the depth dimension.
Definition: Descriptors.hpp:637
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
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::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::Convolution3dDescriptor::m_PadTop
uint32_t m_PadTop
Padding top value in the height dimension.
Definition: Descriptors.hpp:633
armnn::Convolution3dDescriptor::m_DilationX
uint32_t m_DilationX
Dilation along x axis.
Definition: Descriptors.hpp:647
armnn::Convolution3dDescriptor::m_PadBottom
uint32_t m_PadBottom
Padding bottom value in the height dimension.
Definition: Descriptors.hpp:635
Convolution3dLayer.hpp
armnn::IStrategy
Definition: IStrategy.hpp:16
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< Convolution3dDescriptor >::GetParameters
const Convolution3dDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
armnn::LayerWithParameters
Definition: LayerWithParameters.hpp:14
armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
armnn::Convolution3dQueueDescriptor
Definition: WorkloadData.hpp:216
armnnUtils::DataLayoutIndexed::GetHeightIndex
unsigned int GetHeightIndex() const
Definition: DataLayoutIndexed.hpp:24
armnn::Convolution3dLayer::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the Convolution3d type.
Definition: Convolution3dLayer.cpp:48
armnn::DataLayout::NDHWC
@ NDHWC
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:614
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::Convolution3dDescriptor::m_PadRight
uint32_t m_PadRight
Padding right value in the width dimension.
Definition: Descriptors.hpp:631
armnn::Convolution3dLayer::Clone
Convolution3dLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: Convolution3dLayer.cpp:56
armnn::LayerWithParameters< Convolution3dDescriptor >::m_Param
Convolution3dDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::Convolution3dLayer::SerializeLayerParameters
void SerializeLayerParameters(ParameterStringifyFunction &fn) const override
Helper to serialize the layer parameters to string.
Definition: Convolution3dLayer.cpp:23
armnn::TensorShape::GetNumDimensions
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174
armnn::LayerWithParameters< Convolution3dDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::Convolution3dDescriptor::m_DilationZ
uint32_t m_DilationZ
Dilation along z axis.
Definition: Descriptors.hpp:651
armnn::LayerValidationException
Definition: Exceptions.hpp:105
armnn::IWorkloadFactory
Definition: WorkloadFactory.hpp:22
armnnUtils
Definition: CompatibleTypes.hpp:10
armnn::Convolution3dDescriptor::m_PadLeft
uint32_t m_PadLeft
Padding left value in the width dimension.
Definition: Descriptors.hpp:629
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::Convolution3dDescriptor::m_StrideY
uint32_t m_StrideY
Stride value when proceeding through input for the height dimension.
Definition: Descriptors.hpp:643
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:303
armnn::Convolution3dDescriptor::m_StrideX
uint32_t m_StrideX
Stride value when proceeding through input for the width dimension.
Definition: Descriptors.hpp:641
armnn::Convolution3dDescriptor
A Convolution3dDescriptor for the Convolution3dLayer.
Definition: Descriptors.hpp:588
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::GetNumInputs
uint32_t GetNumInputs(bool biasEnabled)
Definition: Descriptors.cpp:455
TensorHandle.hpp
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::Convolution3dDescriptor::m_PadBack
uint32_t m_PadBack
Padding back value in the depth dimension.
Definition: Descriptors.hpp:639
armnn::Convolution3dLayer
This layer represents a convolution 3d operation.
Definition: Convolution3dLayer.hpp:16
armnn::Convolution3dDescriptor::m_DilationY
uint32_t m_DilationY
Dilation along y axis.
Definition: Descriptors.hpp:649
armnn
Copyright (c) 2021 ARM Limited and Contributors.
Definition: 01_00_quick_start.dox:6
armnn::Convolution3dDescriptor::m_StrideZ
uint32_t m_StrideZ
Stride value when proceeding through input for the depth dimension.
Definition: Descriptors.hpp:645
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:410
armnn::Convolution3dDescriptor::m_DataLayout
DataLayout m_DataLayout
The data layout to be used (NDHWC, NCDHW).
Definition: Descriptors.hpp:655
armnn::Convolution3dLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of Convolution3dLayer.
Definition: Convolution3dLayer.cpp:126
armnn::Convolution3dLayer::ExecuteStrategy
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Definition: Convolution3dLayer.cpp:153
armnn::LayerType::Convolution3d
@ Convolution3d
armnn::Convolution3dLayer::Convolution3dLayer
Convolution3dLayer(const Convolution3dDescriptor &param, const char *name)
Constructor to create a Convolution3dLayer.
Definition: Convolution3dLayer.cpp:18
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
armnnUtils::DataLayoutIndexed::GetDepthIndex
unsigned int GetDepthIndex() const
Definition: DataLayoutIndexed.hpp:26