ArmNN
 24.08
LogicalBinaryLayer.cpp
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1 //
2 // Copyright © 2020-2024 Arm Ltd and Contributors. All rights reserved.
3 // SPDX-License-Identifier: MIT
4 //
5 
6 #include "LogicalBinaryLayer.hpp"
7 
8 #include "LayerCloneBase.hpp"
9 
12 
13 #include <algorithm>
14 
15 namespace armnn
16 {
17 
19  : LayerWithParameters(2, 1, LayerType::LogicalBinary, param, name)
20 {
21 }
22 
23 std::unique_ptr<IWorkload> LogicalBinaryLayer::CreateWorkload(const IWorkloadFactory& factory) const
24 {
26  return factory.CreateWorkload(LayerType::LogicalBinary, descriptor, PrepInfoAndDesc(descriptor));
27 }
28 
30 {
31  return CloneBase<LogicalBinaryLayer>(graph, m_Param, GetName());
32 }
33 
34 std::vector<TensorShape> LogicalBinaryLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
35 {
36  if (inputShapes.size() != 2)
37  {
38  throw armnn::Exception("inputShapes' size is \"" + std::to_string(inputShapes.size()) +
39  "\" - should be \"2\".");
40  }
41 
42  const TensorShape& input0 = inputShapes[0];
43  const TensorShape& input1 = inputShapes[1];
44 
45  if (input0.GetNumDimensions() != input1.GetNumDimensions())
46  {
47  throw armnn::Exception("Input dimensions do not match (\""
48  + std::to_string(input0.GetNumDimensions()) +
49  "\" vs \""
50  + std::to_string(input1.GetNumDimensions()) + "\").");
51  }
52 
53  unsigned int numDims = input0.GetNumDimensions();
54 
55  std::vector<unsigned int> dims(numDims);
56  for (unsigned int i = 0; i < numDims; i++)
57  {
58  unsigned int dim0 = input0[i];
59  unsigned int dim1 = input1[i];
60 
61  if (dim0 != dim1 && dim0 != 1 && dim1 != 1)
62  {
63  throw armnn::Exception("Dimensions should either match or one should be of size 1.");
64  }
65 
66  dims[i] = std::max(dim0, dim1);
67  }
68 
69  return std::vector<TensorShape>({ TensorShape(numDims, dims.data()) });
70 }
71 
73 {
75 
76  const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();
77 
79 
80  std::vector<TensorShape> inferredShapes = InferOutputShapes({
83  });
84 
85  if (inferredShapes.size() != 1)
86  {
87  throw armnn::LayerValidationException("inferredShapes has "
88  + std::to_string(inferredShapes.size()) +
89  " elements - should only have 1.");
90  }
91 
92  ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "LogicalBinaryLayer");
93 }
94 
96 {
97  strategy.ExecuteStrategy(this, GetParameters(), {}, GetName());
98 }
99 
100 } // namespace armnn
armnn::LogicalBinaryLayer::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the LogicalBinary type.
Definition: LogicalBinaryLayer.cpp:23
armnn::LogicalBinaryLayer::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: LogicalBinaryLayer.cpp:34
armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:100
WorkloadData.hpp
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::LogicalBinaryQueueDescriptor
Definition: WorkloadData.hpp:681
armnn::IStrategy
Definition: IStrategy.hpp:16
armnn::LogicalBinaryLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of LogicalBinaryLayer.
Definition: LogicalBinaryLayer.cpp:72
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< LogicalBinaryDescriptor >::GetParameters
const LogicalBinaryDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19
WorkloadFactory.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::InputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Gets the TensorInfo for this InputSlot.
Definition: Layer.cpp:614
armnn::TensorShape
Definition: Tensor.hpp:20
armnn::LogicalBinaryLayer::LogicalBinaryLayer
LogicalBinaryLayer(const LogicalBinaryDescriptor &param, const char *name)
Constructor to create a LogicalBinaryLayer.
Definition: LogicalBinaryLayer.cpp:18
armnn::LayerWithParameters< LogicalBinaryDescriptor >::m_Param
LogicalBinaryDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52
armnn::TensorShape::GetNumDimensions
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174
armnn::LogicalBinaryLayer::Clone
LogicalBinaryLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: LogicalBinaryLayer.cpp:29
armnn::LayerType::LogicalBinary
@ LogicalBinary
armnn::LayerWithParameters< LogicalBinaryDescriptor >::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::Exception
Base class for all ArmNN exceptions so that users can filter to just those.
Definition: Exceptions.hpp:46
armnn::LogicalBinaryDescriptor
A LogicalBinaryDescriptor for the LogicalBinaryLayer.
Definition: Descriptors.hpp:1518
armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:193
LogicalBinaryLayer.hpp
armnn
Copyright (c) 2021 ARM Limited and Contributors.
Definition: 01_00_quick_start.dox:6
armnn::LogicalBinaryLayer
This layer represents a Logical Binary operation.
Definition: LogicalBinaryLayer.hpp:14
armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:410
armnn::LogicalBinaryLayer::ExecuteStrategy
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Definition: LogicalBinaryLayer.cpp:95
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