ArmNN
 24.08
PreluLayer.cpp
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1 //
2 // Copyright © 2017,2019-2024 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "PreluLayer.hpp"
7 
8 #include "LayerCloneBase.hpp"
9 
11 
15 
16 namespace armnn
17 {
18 
19 PreluLayer::PreluLayer(const char* name)
20  : Layer(2, 1, LayerType::Prelu, name)
21 {}
22 
23 std::unique_ptr<IWorkload> PreluLayer::CreateWorkload(const IWorkloadFactory& factory) const
24 {
25  PreluQueueDescriptor descriptor;
26  SetAdditionalInfo(descriptor);
27 
28  return factory.CreateWorkload(LayerType::Prelu, descriptor, PrepInfoAndDesc(descriptor));
29 }
30 
32 {
33  auto layer = CloneBase<PreluLayer>(graph, GetName());
34 
35  return std::move(layer);
36 }
37 
38 std::vector<TensorShape> PreluLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
39 {
40  if (inputShapes.size() != 2)
41  {
42  throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
43  "\" - should be \"2\".");
44  }
45 
46  const TensorShape& inputShape = inputShapes[0];
47  const TensorShape& alphaShape = inputShapes[1];
48 
49  const unsigned int inputShapeDimensions = inputShape.GetNumDimensions();
50  const unsigned int alphaShapeDimensions = alphaShape.GetNumDimensions();
51 
52  if (inputShapeDimensions == 0)
53  {
54  throw armnn::Exception("inputShapeDimensions must be greater than 0.");
55  }
56 
57  if (alphaShapeDimensions == 0)
58  {
59  throw armnn::Exception("alphaShapeDimensions must be not be zero (\""
60  + std::to_string(alphaShapeDimensions) + "\")");
61  }
62 
63  // The size of the output is the maximum size along each dimension of the input operands,
64  // it starts with the trailing dimensions, and works its way forward
65 
66  unsigned int outputDimensions = std::max(inputShapeDimensions, alphaShapeDimensions);
67 
68  TensorShape outputShape(outputDimensions);
69 
70  int inputShapeIndex = armnn::numeric_cast<int>(inputShapeDimensions) - 1;
71  int alphaShapeIndex = armnn::numeric_cast<int>(alphaShapeDimensions) - 1;
72  unsigned int outputShapeIndex = outputDimensions - 1;
73 
74  // Loop backwards through the common part of the shapes
75  while (inputShapeIndex >= 0 && alphaShapeIndex >= 0)
76  {
77  unsigned int inputDimension = inputShape[armnn::numeric_cast<unsigned int>(inputShapeIndex)];
78  unsigned int alphaDimension = alphaShape[armnn::numeric_cast<unsigned int>(alphaShapeIndex)];
79 
80  // Check that the inputs are broadcast compatible
81  if (inputDimension != alphaDimension && inputDimension != 1 && alphaDimension != 1)
82  {
83  throw armnn::Exception("PreluLayer: Dimensions should either match or one should be of size 1");
84  }
85 
86  outputShape[outputShapeIndex] = std::max(inputDimension, alphaDimension);
87 
88  inputShapeIndex--;
89  alphaShapeIndex--;
90  outputShapeIndex--;
91  }
92 
93  // Loop backwards through the remaing part of the input shape (if any)
94  while (inputShapeIndex >= 0)
95  {
96  outputShape[outputShapeIndex] = inputShape[armnn::numeric_cast<unsigned int>(inputShapeIndex)];
97 
98  inputShapeIndex--;
99  outputShapeIndex--;
100  }
101 
102  // Loop backwards through the remaing part of the alpha shape (if any)
103  while (alphaShapeIndex >= 0)
104  {
105  outputShape[outputShapeIndex] = alphaShape[armnn::numeric_cast<unsigned int>(alphaShapeIndex)];
106 
107  alphaShapeIndex--;
108  outputShapeIndex--;
109  }
110 
111  return { outputShape };
112 }
113 
115 {
117 
118  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
119 
121 
122  std::vector<TensorShape> inferredShapes = InferOutputShapes(
123  {
126  });
127 
128  if (inferredShapes.size() != 1)
129  {
130  throw armnn::LayerValidationException("inferredShapes has "
131  + std::to_string(inferredShapes.size()) +
132  " elements - should only have 1.");
133  }
134 
135  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "PreluLayer");
136 }
137 
139 {
140  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
141 }
142 
143 } // namespace armnn
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:100
WorkloadData.hpp
armnn::PreluLayer::PreluLayer
PreluLayer(const char *name)
Constructor to create a PreluLayer.
Definition: PreluLayer.cpp:19
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::PreluLayer
Definition: PreluLayer.hpp:14
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::PreluQueueDescriptor
Definition: WorkloadData.hpp:539
armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:337
WorkloadFactory.hpp
NumericCast.hpp
armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:332
armnn::Layer
Definition: Layer.hpp:230
armnn::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:614
PreluLayer.hpp
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::TensorShape::GetNumDimensions
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174
armnn::LayerType::Prelu
@ Prelu
armnn::Layer::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: Layer.hpp:409
armnn::LayerValidationException
Definition: Exceptions.hpp:105
armnn::IWorkloadFactory
Definition: WorkloadFactory.hpp:22
armnn::PreluLayer::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the PReLU type.
Definition: PreluLayer.cpp:23
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::Exception
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:46
armnn::PreluLayer::ExecuteStrategy
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Definition: PreluLayer.cpp:138
armnn::Layer::GetParameters
virtual const BaseDescriptor & GetParameters() const override
If the layer has a descriptor return it.
Definition: Layer.hpp:378
armnn::PreluLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of PreluLayer.
Definition: PreluLayer.cpp:114
armnn::PreluLayer::Clone
PreluLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: PreluLayer.cpp:31
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::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::PreluLayer::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: PreluLayer.cpp:38
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