ArmNN
 24.08
ElementwiseBinaryLayer.cpp
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1 //
2 // Copyright © 2024 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
7 
8 #include "LayerCloneBase.hpp"
9 
10 namespace armnn
11 {
12 
14  : LayerWithParameters(2, 1, LayerType::ElementwiseBinary, param, name)
15 {
16 }
17 
18 std::unique_ptr<IWorkload> ElementwiseBinaryLayer::CreateWorkload(const IWorkloadFactory& factory) const
19 {
21  SetAdditionalInfo(descriptor);
22 
23  return factory.CreateWorkload(LayerType::ElementwiseBinary, descriptor, PrepInfoAndDesc(descriptor));
24 }
25 
27 {
28  return CloneBase<ElementwiseBinaryLayer>(graph, m_Param, GetName());
29 }
30 
31 std::vector<TensorShape> ElementwiseBinaryLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
32 {
33  if (inputShapes.size() != 2)
34  {
35  throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
36  "\" - should be \"2\".");
37  }
38 
39  TensorShape input0 = inputShapes[0];
40  TensorShape input1 = inputShapes[1];
41 
42  if (inputShapes[0].GetNumDimensions() < inputShapes[1].GetNumDimensions())
43  {
44  input1 = inputShapes[0];
45  input0 = inputShapes[1];
46  }
47 
48  unsigned int numDims = input0.GetNumDimensions();
49  unsigned int shiftedDims = input0.GetNumDimensions() - input1.GetNumDimensions();
50 
51  // Get the max of the inputs.
52  std::vector<unsigned int> dims(numDims);
53  for (unsigned int i = shiftedDims; i < numDims; i++)
54  {
55  unsigned int dim0 = input0[i];
56  unsigned int dim1 = input1[i - shiftedDims];
57 
58  // Validate inputs are broadcast compatible.
59  if (dim0 != dim1 && dim0 != 1 && dim1 != 1)
60  {
61  throw armnn::Exception("Dimensions should either match or one should be of size 1.");
62  }
63 
64  dims[i] = std::max(dim0, dim1);
65  }
66 
67  // Fill in the rest of the shifted dimensions.
68  for (unsigned int i = 0; i < shiftedDims; i++)
69  {
70  dims[i] = input0[i];
71  }
72 
73  return std::vector<TensorShape>({ TensorShape(numDims, dims.data()) });
74 }
75 
77 {
79 
80  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
81 
83 
84  auto inferredShapes = InferOutputShapes({ GetInputSlot(0).GetTensorInfo().GetShape(),
86 
87  if (inferredShapes.size() != 1)
88  {
89  throw armnn::LayerValidationException("inferredShapes has "
90  + std::to_string(inferredShapes.size()) +
91  " elements - should only have 1.");
92  }
93 
94  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, GetLayerTypeAsCString(GetType()));
95 }
96 
98 {
99  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
100 }
101 } // namespace armnn
ElementwiseBinaryLayer.hpp
armnn::GetLayerTypeAsCString
const char * GetLayerTypeAsCString(LayerType type)
Definition: InternalTypes.cpp:13
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:100
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::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::ElementwiseBinaryLayer::InferOutputShapes
std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override
Returns inputShapes by default.
Definition: ElementwiseBinaryLayer.cpp:31
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< ElementwiseBinaryDescriptor >::GetParameters
const ElementwiseBinaryDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
armnn::LayerType::ElementwiseBinary
@ ElementwiseBinary
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::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:614
armnn::ElementwiseBinaryDescriptor
A ElementwiseBinaryDescriptor for the ElementwiseBinaryLayer.
Definition: Descriptors.hpp:109
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::ElementwiseBinaryQueueDescriptor
Definition: WorkloadData.hpp:671
armnn::LayerWithParameters< ElementwiseBinaryDescriptor >::m_Param
ElementwiseBinaryDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::ElementwiseBinaryLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of ElementwiseBinaryLayer.
Definition: ElementwiseBinaryLayer.cpp:76
armnn::TensorShape::GetNumDimensions
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174
armnn::ElementwiseBinaryLayer::Clone
ElementwiseBinaryLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: ElementwiseBinaryLayer.cpp:26
armnn::LayerWithParameters< ElementwiseBinaryDescriptor >::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::ElementwiseBinaryLayer::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the elementwiseBinary type.
Definition: ElementwiseBinaryLayer.cpp:18
armnn::IWorkloadFactory
Definition: WorkloadFactory.hpp:22
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::ElementwiseBinaryLayer
This layer represents a elementwiseBinary operation.
Definition: ElementwiseBinaryLayer.hpp:14
armnn::Layer::GetType
LayerType GetType() const override
Returns the armnn::LayerType of this layer.
Definition: Layer.hpp:286
armnn::ElementwiseBinaryLayer::ExecuteStrategy
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Definition: ElementwiseBinaryLayer.cpp:97
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::ElementwiseBinaryLayer::ElementwiseBinaryLayer
ElementwiseBinaryLayer(const ElementwiseBinaryDescriptor &param, const char *name)
Constructor to create a ElementwiseBinaryLayer.
Definition: ElementwiseBinaryLayer.cpp:13
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