ArmNN
 24.08
ReduceLayer.cpp
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1 //
2 // Copyright © 2020 Samsung Electronics Co Ltd and Contributors. All rights reserved.
3 // Copyright © 2023-2024 Arm Ltd and Contributors. All rights reserved.
4 // SPDX-License-Identifier: MIT
5 //
6 
7 #include "ReduceLayer.hpp"
8 #include "LayerCloneBase.hpp"
9 
10 #include <armnn/TypesUtils.hpp>
11 
14 
15 namespace armnn
16 {
17 
18 ReduceLayer::ReduceLayer(const ReduceDescriptor& param, const char* name)
19  : LayerWithParameters(1, 1, LayerType::Reduce, param, name)
20 {
21 }
22 
23 std::unique_ptr<IWorkload> ReduceLayer::CreateWorkload(const IWorkloadFactory& factory) const
24 {
25  ReduceQueueDescriptor descriptor;
26  descriptor.m_Parameters.m_vAxis = m_Param.m_vAxis;
29  SetAdditionalInfo(descriptor);
30 
31  return factory.CreateWorkload(LayerType::Reduce, descriptor, PrepInfoAndDesc(descriptor));
32 }
33 
35 {
36  auto layer = CloneBase<ReduceLayer>(graph, m_Param, GetName());
37  layer->m_Param.m_vAxis = m_Param.m_vAxis;
38  layer->m_Param.m_KeepDims = m_Param.m_KeepDims;
39  layer->m_Param.m_ReduceOperation = m_Param.m_ReduceOperation;
40 
41  return std::move(layer);
42 }
43 
45 {
47 
48  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
49 
51 
52  const TensorInfo& input = GetInputSlot(0).GetTensorInfo();
53 
54  auto inputDims = input.GetNumDimensions();
55  if (inputDims < 1 || inputDims > 4)
56  {
57  throw armnn::LayerValidationException("ReduceLayer: Reduce supports up to 4D input.");
58  }
59 
60  std::vector<TensorShape> inferredShapes = InferOutputShapes( {input.GetShape() });
61 
62  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "ReduceLayer");
63 }
64 
65 std::vector<TensorShape> ReduceLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
66 {
67  if (inputShapes.size() != 1)
68  {
69  throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
70  "\" - should be \"1\".");
71  }
72 
73  const TensorShape& input = inputShapes[0];
74 
75  auto inputDims = input.GetNumDimensions();
76  if (inputDims < 1 || inputDims > 4)
77  {
78  throw armnn::Exception("ReduceLayer: Reduce supports up to 4D input.");
79  }
80 
81  unsigned int rank = input.GetNumDimensions();
82  unsigned int outputRank = 0;
83 
84  // Calculate output dimension
85  if (m_Param.m_KeepDims)
86  {
87  outputRank = rank;
88  }
89  else if (m_Param.m_vAxis.empty())
90  {
91  outputRank = 1;
92  }
93  else if (m_Param.m_vAxis.size() > input.GetNumDimensions())
94  {
95  throw LayerValidationException("ReduceLayer: Dimensions to reduce can not be bigger than input dimensions");
96  }
97  else
98  {
99  outputRank = input.GetNumDimensions() - armnn::numeric_cast<unsigned int>(m_Param.m_vAxis.size());
100  if (outputRank == 0)
101  {
102  outputRank = 1;
103  }
104  }
105 
106  std::vector<unsigned int> dimSizes(outputRank, 1);
107  if (!m_Param.m_vAxis.empty())
108  {
109  // Skip the dimension that has been reduced unless keepDims is true.
110  unsigned int outputIndex = 0;
111  for (unsigned int i = 0; i < input.GetNumDimensions(); ++i)
112  {
113  if (std::find(m_Param.m_vAxis.begin(), m_Param.m_vAxis.end(), i) == m_Param.m_vAxis.end())
114  {
115  dimSizes[outputIndex] = armnn::numeric_cast<unsigned int>(input[i]);
116  ++outputIndex;
117  }
118  else if (m_Param.m_KeepDims)
119  {
120  dimSizes[outputIndex] = 1;
121  ++outputIndex;
122  }
123  }
124  }
125  return std::vector<TensorShape>({ TensorShape(outputRank, dimSizes.data()) });
126 }
127 
129 {
130  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
131 }
132 
133 } // namespace armnn
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:100
WorkloadData.hpp
TypesUtils.hpp
armnn::TensorInfo
Definition: Tensor.hpp:152
armnn::TensorInfo::GetNumDimensions
unsigned int GetNumDimensions() const
Definition: Tensor.hpp:197
armnn::Reduce
void Reduce(const TensorInfo &inputInfo, const TensorInfo &outputInfo, Decoder< float > &input, Encoder< float > &output, const std::vector< uint32_t > axis, const ReduceOperation reduceOperation)
Definition: Reduce.cpp:70
CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203
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::ReduceLayer::ReduceLayer
ReduceLayer(const ReduceDescriptor &param, const char *name)
Constructor to create a ReduceLayer.
Definition: ReduceLayer.cpp:18
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::LayerType::Reduce
@ Reduce
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< ReduceDescriptor >::GetParameters
const ReduceDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
WorkloadFactory.hpp
ReduceLayer.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
armnn::ReduceDescriptor::m_ReduceOperation
ReduceOperation m_ReduceOperation
Specifies the reduction operation to execute.
Definition: Descriptors.hpp:1558
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:614
armnn::ReduceLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of ReduceLayer.
Definition: ReduceLayer.cpp:44
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::ReduceQueueDescriptor
Definition: WorkloadData.hpp:686
armnn::LayerWithParameters< ReduceDescriptor >::m_Param
ReduceDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::QueueDescriptorWithParameters::m_Parameters
LayerDescriptor m_Parameters
Definition: WorkloadData.hpp:66
armnn::TensorShape::GetNumDimensions
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174
armnn::ReduceLayer
This layer represents a reduction operation.
Definition: ReduceLayer.hpp:14
armnn::LayerWithParameters< ReduceDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::LayerValidationException
Definition: Exceptions.hpp:105
armnn::IWorkloadFactory
Definition: WorkloadFactory.hpp:22
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:526
armnn::ReduceLayer::Clone
ReduceLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: ReduceLayer.cpp:34
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:303
armnn::Exception
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:46
armnn::ReduceDescriptor::m_KeepDims
bool m_KeepDims
if true then output shape has no change.
Definition: Descriptors.hpp:1554
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
armnn::ReduceDescriptor::m_vAxis
std::vector< uint32_t > m_vAxis
The indices of the dimensions to reduce.
Definition: Descriptors.hpp:1556
armnn
Copyright (c) 2021 ARM Limited and Contributors.
Definition: 01_00_quick_start.dox:6
armnn::ReduceLayer::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: ReduceLayer.cpp:65
armnn::ReduceLayer::ExecuteStrategy
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Definition: ReduceLayer.cpp:128
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:410
armnn::ReduceDescriptor
A ReduceDescriptor for the REDUCE operators.
Definition: Descriptors.hpp:1538
armnn::ReduceLayer::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the Reduce type.
Definition: ReduceLayer.cpp:23
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
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