patch/21.11/_logical_binary_layer_8cpp_source.xhtml

 //
 // Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //

 #include "LogicalBinaryLayer.hpp"

 #include "LayerCloneBase.hpp"

 #include <backendsCommon/WorkloadData.hpp>
 #include <backendsCommon/WorkloadFactory.hpp>

 #include <algorithm>

 namespace armnn
 {

 LogicalBinaryLayer::LogicalBinaryLayer(const LogicalBinaryDescriptor& param, const char* name)
     : LayerWithParameters(2, 1, LayerType::LogicalBinary, param, name)
 {
 }

 std::unique_ptr<IWorkload> LogicalBinaryLayer::CreateWorkload(const IWorkloadFactory& factory) const
 {
     LogicalBinaryQueueDescriptor descriptor;
     return factory.CreateLogicalBinary(descriptor, PrepInfoAndDesc(descriptor));
 }

 LogicalBinaryLayer* LogicalBinaryLayer::Clone(Graph& graph) const
 {
     return CloneBase<LogicalBinaryLayer>(graph, m_Param, GetName());
 }

 std::vector<TensorShape> LogicalBinaryLayer::InferOutputShapes(const std::vector<TensorShape>& inputShapes) const
 {
     ARMNN_ASSERT(inputShapes.size() == 2);
     const TensorShape& input0 = inputShapes[0];
     const TensorShape& input1 = inputShapes[1];

     ARMNN_ASSERT(input0.GetNumDimensions() == input1.GetNumDimensions());
     unsigned int numDims = input0.GetNumDimensions();

     std::vector<unsigned int> dims(numDims);
     for (unsigned int i = 0; i < numDims; i++)
     {
         unsigned int dim0 = input0[i];
         unsigned int dim1 = input1[i];

         ARMNN_ASSERT_MSG(dim0 == dim1 || dim0 == 1 || dim1 == 1,
                          "Dimensions should either match or one should be of size 1.");

         dims[i] = std::max(dim0, dim1);
     }

     return std::vector<TensorShape>({ TensorShape(numDims, dims.data()) });
 }

 void LogicalBinaryLayer::ValidateTensorShapesFromInputs()
 {
     VerifyLayerConnections(2, CHECK_LOCATION());

     const TensorShape& outputShape = GetOutputSlot(0).GetTensorInfo().GetShape();

     VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);

     std::vector<TensorShape> inferredShapes = InferOutputShapes({
         GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),
         GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape()
     });
     ARMNN_ASSERT(inferredShapes.size() == 1);

     ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "LogicalBinaryLayer");
 }

 ARMNN_NO_DEPRECATE_WARN_BEGIN
 void LogicalBinaryLayer::Accept(ILayerVisitor& visitor) const
 {
     visitor.VisitLogicalBinaryLayer(this, GetParameters(), GetName());
 }
 ARMNN_NO_DEPRECATE_WARN_END

 } // 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

+WorkloadData.hpp

+armnn::LogicalBinaryLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of LogicalBinaryLayer.
Definition: LogicalBinaryLayer.cpp:58

+armnn::LayerWithParameters< LogicalBinaryDescriptor >::m_Param
LogicalBinaryDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:50

+armnn::LayerWithParameters< LogicalBinaryDescriptor >::GetParameters
const LogicalBinaryDescriptor & GetParameters() const
Definition: LayerWithParameters.hpp:18

+armnn::LogicalBinaryLayer::LogicalBinaryLayer
LogicalBinaryLayer(const LogicalBinaryDescriptor &param, const char *name)
Constructor to create a LogicalBinaryLayer.
Definition: LogicalBinaryLayer.cpp:18

+armnn::TensorInfo::GetShape
const TensorShape & GetShape() const
Definition: Tensor.hpp:191

+LogicalBinaryLayer.hpp

+ARMNN_NO_DEPRECATE_WARN_BEGIN
#define ARMNN_NO_DEPRECATE_WARN_BEGIN
Definition: Deprecated.hpp:33

+WorkloadFactory.hpp

+armnn::IWorkloadFactory
Definition: WorkloadFactory.hpp:22

+armnn::LogicalBinaryDescriptor
A LogicalBinaryDescriptor for the LogicalBinaryLayer.
Definition: Descriptors.hpp:1376

+armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:433

+armnn
Copyright (c) 2021 ARM Limited and Contributors.
Definition: 01_00_quick_start.dox:6

+armnn::TensorShape
Definition: Tensor.hpp:20

+armnn::InputSlot::GetConnection
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:199

+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:393

+armnn::LayerType::LogicalBinary

+armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:349

+armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:316

+armnn::LogicalBinaryLayer
This layer represents a Logical Binary operation.
Definition: LogicalBinaryLayer.hpp:14

+ARMNN_NO_DEPRECATE_WARN_END
#define ARMNN_NO_DEPRECATE_WARN_END
Definition: Deprecated.hpp:34

+ARMNN_ASSERT_MSG
#define ARMNN_ASSERT_MSG(COND, MSG)
Definition: Assert.hpp:15

+ARMNN_ASSERT
#define ARMNN_ASSERT(COND)
Definition: Assert.hpp:14

+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, otherwise infers the output shapes from given input shapes and layer properties.
Definition: LogicalBinaryLayer.cpp:34

+CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:209

+armnn::IWorkloadFactory::CreateLogicalBinary
virtual std::unique_ptr< IWorkload > CreateLogicalBinary(const LogicalBinaryQueueDescriptor &descriptor, const WorkloadInfo &Info) const
Definition: WorkloadFactory.cpp:1688

+armnn::LogicalBinaryQueueDescriptor
Definition: WorkloadData.hpp:694

+armnn::Graph
Definition: Graph.hpp:30

+armnn::LogicalBinaryLayer::Accept
ARMNN_NO_DEPRECATE_WARN_BEGIN void Accept(ILayerVisitor &visitor) const override
Definition: LogicalBinaryLayer.cpp:76

+armnn::LogicalBinaryLayer::Clone
LogicalBinaryLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: LogicalBinaryLayer.cpp:29

+armnn::TensorShape::GetNumDimensions
unsigned int GetNumDimensions() const
Function that returns the tensor rank.
Definition: Tensor.cpp:174

+armnn::LayerWithParameters< LogicalBinaryDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *LayerCreateWorkload.
Definition: LayerWithParameters.hpp:43

+armnn::Layer::GetOutputSlot
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:318

+armnn::IOutputSlot::GetTensorInfo
virtual const TensorInfo & GetTensorInfo() const =0

+armnn::Layer::GetName
const char * GetName() const override
Returns the name of the layer.
Definition: Layer.hpp:311

+armnn::LayerWithParameters
Definition: LayerWithParameters.hpp:13

+armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:63

+armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:408

+LayerCloneBase.hpp

+armnn::LayerType
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below...
Definition: Types.hpp:443

+