ArmNN
 24.02
MeanLayer.cpp
Go to the documentation of this file.
1 //
2 // Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "MeanLayer.hpp"
7 #include "LayerCloneBase.hpp"
8 
10 
14 
15 #include <cstring>
16 
17 namespace armnn
18 {
19 
20 MeanLayer::MeanLayer(const armnn::MeanDescriptor& param, const char* name)
21  : LayerWithParameters(1, 1, LayerType::Mean, param, name)
22 {}
23 
24 std::unique_ptr<IWorkload> MeanLayer::CreateWorkload(const armnn::IWorkloadFactory& factory) const
25 {
26  MeanQueueDescriptor descriptor;
27  descriptor.m_Parameters.m_Axis = m_Param.m_Axis;
29  SetAdditionalInfo(descriptor);
30 
31  return factory.CreateWorkload(LayerType::Mean, descriptor, PrepInfoAndDesc(descriptor));
32 }
33 
35 {
36  auto layer = CloneBase<MeanLayer>(graph, m_Param, GetName());
37 
38  layer->m_Param.m_Axis = m_Param.m_Axis;
39  layer->m_Param.m_KeepDims = m_Param.m_KeepDims;
40 
41  return std::move(layer);
42 }
43 
45 {
47 
48  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
49 
51 
52  std::vector<TensorShape> inferredShapes = InferOutputShapes(
54 
55  ARMNN_ASSERT(inferredShapes.size() == 1);
56  ARMNN_ASSERT(inferredShapes[0].GetDimensionality() == Dimensionality::Specified);
57 
58  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "MeanLayer");
59 }
60 
61 std::vector<TensorShape> MeanLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
62 {
63  ARMNN_ASSERT(inputShapes.size() == 1);
64  const TensorShape& input = inputShapes[0];
65 
66  ARMNN_ASSERT_MSG(input.GetNumDimensions() > 0 && input.GetNumDimensions() <= 4,
67  "MeanLayer: Mean supports up to 4D input.");
68 
69  unsigned int rank = input.GetNumDimensions();
70  unsigned int outputRank = 0;
71 
72  // Calculate output dimension
73  if (m_Param.m_KeepDims)
74  {
75  outputRank = rank;
76  }
77  else if (m_Param.m_Axis.empty())
78  {
79  outputRank = 1;
80  }
81  else if (m_Param.m_Axis.size() > input.GetNumDimensions())
82  {
83  throw LayerValidationException("MeanLayer: Dimensions to reduce can not be bigger than input dimensions");
84  }
85  else
86  {
87  outputRank = input.GetNumDimensions() - armnn::numeric_cast<unsigned int>(m_Param.m_Axis.size());
88  if (outputRank == 0)
89  {
90  outputRank = 1;
91  }
92  }
93 
94  std::vector<unsigned int> dimSizes(outputRank, 1);
95  if (!m_Param.m_Axis.empty())
96  {
97  // Skip the dimension that has been reduced unless keepDims is true.
98  unsigned int outputIndex = 0;
99  for (unsigned int i = 0; i < input.GetNumDimensions(); ++i)
100  {
101  if (std::find(m_Param.m_Axis.begin(), m_Param.m_Axis.end(), i) == m_Param.m_Axis.end())
102  {
103  dimSizes[outputIndex] = armnn::numeric_cast<unsigned int>(input[i]);
104  ++outputIndex;
105  }
106  else if (m_Param.m_KeepDims)
107  {
108  dimSizes[outputIndex] = 1;
109  ++outputIndex;
110  }
111  }
112  }
113  return std::vector<TensorShape>({ TensorShape(outputRank, dimSizes.data()) });
114 }
115 
117 {
118  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
119 }
120 
121 } // namespace armnn
ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92
WorkloadData.hpp
armnn::MeanLayer::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: MeanLayer.cpp:61
armnn::MeanLayer
This layer represents a mean operation.
Definition: MeanLayer.hpp:14
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:435
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_ASSERT_MSG
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15
armnn::ReduceOperation::Mean
@ Mean
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< MeanDescriptor >::GetParameters
const MeanDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
WorkloadFactory.hpp
NumericCast.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::MeanDescriptor::m_KeepDims
bool m_KeepDims
Enable/disable keep dimensions. If true, then the reduced dimensions that are of length 1 are kept.
Definition: Descriptors.hpp:1192
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:592
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::LayerWithParameters< MeanDescriptor >::m_Param
MeanDescriptor 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::LayerWithParameters< MeanDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44
armnn::MeanLayer::MeanLayer
MeanLayer(const MeanDescriptor &param, const char *name)
Constructor to create a MeanLayer.
Definition: MeanLayer.cpp:20
armnn::LayerValidationException
Definition: Exceptions.hpp:105
armnn::IWorkloadFactory
Definition: WorkloadFactory.hpp:22
armnn::MeanLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of MeanLayer.
Definition: MeanLayer.cpp:44
armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:504
armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:287
armnn::MeanLayer::Clone
MeanLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: MeanLayer.cpp:34
armnn::MeanLayer::ExecuteStrategy
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Definition: MeanLayer.cpp:116
armnn::Dimensionality::Specified
@ Specified
TensorHandle.hpp
armnn::MeanDescriptor::m_Axis
std::vector< unsigned int > m_Axis
Values for the dimensions to reduce.
Definition: Descriptors.hpp:1190
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
MeanLayer.hpp
armnn::LayerType::Mean
@ Mean
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:391
armnn::MeanQueueDescriptor
Definition: WorkloadData.hpp:288
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::MeanDescriptor
A MeanDescriptor for the MeanLayer.
Definition: Descriptors.hpp:1172
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
armnn::MeanLayer::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the Mean type.
Definition: MeanLayer.cpp:24