patch/23.02/_detection_post_process_layer_8cpp_source.xhtml

 //
 // Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //

 #include "DetectionPostProcessLayer.hpp"

 #include "LayerCloneBase.hpp"

 #include <armnn/TypesUtils.hpp>
 #include <armnn/backends/TensorHandle.hpp>
 #include <armnn/backends/WorkloadData.hpp>
 #include <armnn/backends/WorkloadFactory.hpp>

 namespace armnn
 {

 DetectionPostProcessLayer::DetectionPostProcessLayer(const DetectionPostProcessDescriptor& param, const char* name)
     : LayerWithParameters(2, 4, LayerType::DetectionPostProcess, param, name)
 {
 }

 std::unique_ptr<IWorkload> DetectionPostProcessLayer::CreateWorkload(const armnn::IWorkloadFactory& factory) const
 {
     DetectionPostProcessQueueDescriptor descriptor;
     descriptor.m_Anchors = m_Anchors.get();
     SetAdditionalInfo(descriptor);

     return factory.CreateWorkload(LayerType::DetectionPostProcess, descriptor, PrepInfoAndDesc(descriptor));
 }

 DetectionPostProcessLayer* DetectionPostProcessLayer::Clone(Graph& graph) const
 {
     auto layer = CloneBase<DetectionPostProcessLayer>(graph, m_Param, GetName());
     layer->m_Anchors = m_Anchors ? m_Anchors : nullptr;
     return std::move(layer);
 }

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

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

     VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);

     // on this level constant data should not be released.
     ARMNN_ASSERT_MSG(m_Anchors != nullptr, "DetectionPostProcessLayer: Anchors data should not be null.");

     ARMNN_ASSERT_MSG(GetNumOutputSlots() == 4, "DetectionPostProcessLayer: The layer should return 4 outputs.");

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

     ARMNN_ASSERT(inferredShapes.size() == 4);
     ARMNN_ASSERT(inferredShapes[0].GetDimensionality() == Dimensionality::Specified);
     ARMNN_ASSERT(inferredShapes[1].GetDimensionality() == Dimensionality::Specified);
     ARMNN_ASSERT(inferredShapes[2].GetDimensionality() == Dimensionality::Specified);
     ARMNN_ASSERT(inferredShapes[3].GetDimensionality() == Dimensionality::Specified);

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

     ValidateAndCopyShape(GetOutputSlot(1).GetTensorInfo().GetShape(),
                          inferredShapes[1],
                          m_ShapeInferenceMethod,
                          "DetectionPostProcessLayer", 1);

     ValidateAndCopyShape(GetOutputSlot(2).GetTensorInfo().GetShape(),
                          inferredShapes[2],
                          m_ShapeInferenceMethod,
                          "DetectionPostProcessLayer", 2);

     ValidateAndCopyShape(GetOutputSlot(3).GetTensorInfo().GetShape(),
                          inferredShapes[3],
                          m_ShapeInferenceMethod,
                          "DetectionPostProcessLayer", 3);
 }

 std::vector<TensorShape> DetectionPostProcessLayer::InferOutputShapes(const std::vector<TensorShape>&) const
 {
     unsigned int detectedBoxes = m_Param.m_MaxDetections * m_Param.m_MaxClassesPerDetection;

     std::vector<TensorShape> results;
     results.push_back({ 1, detectedBoxes, 4 });
     results.push_back({ 1, detectedBoxes });
     results.push_back({ 1, detectedBoxes });
     results.push_back({ 1 });
     return results;
 }

 Layer::ConstantTensors DetectionPostProcessLayer::GetConstantTensorsByRef()
 {
     // For API stability DO NOT ALTER order and add new members to the end of vector
     return { m_Anchors };
 }

 void DetectionPostProcessLayer::ExecuteStrategy(IStrategy& strategy) const
 {
     ManagedConstTensorHandle managedAnchors(m_Anchors);
     std::vector<armnn::ConstTensor> constTensors { {managedAnchors.GetTensorInfo(), managedAnchors.Map()} };
     strategy.ExecuteStrategy(this, GetParameters(), constTensors, GetName());
 }

 } // namespace armnn
WorkloadData.hpp

-armnn::LayerWithParameters< DetectionPostProcessDescriptor >::m_Param
DetectionPostProcessDescriptor m_Param
The parameters for the layer (not including tensor-valued weights etc.).
Definition: LayerWithParameters.hpp:52

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

-armnn::DetectionPostProcessQueueDescriptor
Definition: WorkloadData.hpp:234

-TensorHandle.hpp

-WorkloadFactory.hpp

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

-armnn::DetectionPostProcessLayer::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(const IWorkloadFactory &factory) const override
Makes a workload for the DetectionPostProcess type.
Definition: DetectionPostProcessLayer.cpp:23

-armnn::DetectionPostProcessLayer::DetectionPostProcessLayer
DetectionPostProcessLayer(const DetectionPostProcessDescriptor &param, const char *name)
Constructor to create a DetectionPostProcessLayer.
Definition: DetectionPostProcessLayer.cpp:18

-armnn::DetectionPostProcessLayer
This layer represents a detection postprocess operator.
Definition: DetectionPostProcessLayer.hpp:16

-armnn::Layer::VerifyShapeInferenceType
void VerifyShapeInferenceType(const TensorShape &outputShape, ShapeInferenceMethod shapeInferenceMethod)
Definition: Layer.cpp:491

-armnn::ManagedConstTensorHandle::GetTensorInfo
const TensorInfo & GetTensorInfo() const
Definition: TensorHandle.hpp:239

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

-armnn::LayerWithParameters< DetectionPostProcessDescriptor >::GetParameters
const DetectionPostProcessDescriptor & GetParameters() const override
Definition: LayerWithParameters.hpp:19

-armnn::Dimensionality::Specified

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

-armnn::InputSlot::GetConnection
const IOutputSlot * GetConnection() const override
Definition: Layer.hpp:206

-armnn::Layer::GetNumOutputSlots
unsigned int GetNumOutputSlots() const override
Returns the number of connectable output slots.
Definition: Layer.hpp:322

-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:422

-armnn::DetectionPostProcessDescriptor::m_MaxClassesPerDetection
uint32_t m_MaxClassesPerDetection
Maximum numbers of classes per detection, used in Fast NMS.
Definition: Descriptors.hpp:715

-armnn::DetectionPostProcessLayer::InferOutputShapes
std::vector< TensorShape > InferOutputShapes(const std::vector< TensorShape > &inputShapes) const override
The model does not specify the output shapes.
Definition: DetectionPostProcessLayer.cpp:80

-armnn::IStrategy
Definition: IStrategy.hpp:16

-armnn::Layer::VerifyLayerConnections
void VerifyLayerConnections(unsigned int expectedConnections, const CheckLocation &location) const
Definition: Layer.cpp:378

-DetectionPostProcessLayer.hpp

-armnn::DetectionPostProcessDescriptor::m_MaxDetections
uint32_t m_MaxDetections
Maximum numbers of detections.
Definition: Descriptors.hpp:713

-armnn::Layer::GetInputSlot
const InputSlot & GetInputSlot(unsigned int index) const override
Get a const input slot handle by slot index.
Definition: Layer.hpp:324

-TypesUtils.hpp

-armnn::DetectionPostProcess
void DetectionPostProcess(const TensorInfo &boxEncodingsInfo, const TensorInfo &scoresInfo, const TensorInfo &anchorsInfo, const TensorInfo &detectionBoxesInfo, const TensorInfo &detectionClassesInfo, const TensorInfo &detectionScoresInfo, const TensorInfo &numDetectionsInfo, const DetectionPostProcessDescriptor &desc, Decoder< float > &boxEncodings, Decoder< float > &scores, Decoder< float > &anchors, float *detectionBoxes, float *detectionClasses, float *detectionScores, float *numDetections)
Definition: DetectionPostProcess.cpp:140

-armnn::IConnectableLayer::ConstantTensors
std::vector< std::reference_wrapper< std::shared_ptr< ConstTensorHandle > >> ConstantTensors
Definition: INetwork.hpp:124

-armnn::LayerType::DetectionPostProcess

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

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

-armnn::DetectionPostProcessLayer::GetConstantTensorsByRef
ConstantTensors GetConstantTensorsByRef() override
Retrieve the handles to the constant values stored by the layer.
Definition: DetectionPostProcessLayer.cpp:92

-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

-CHECK_LOCATION
#define CHECK_LOCATION()
Definition: Exceptions.hpp:203

-armnn::Graph
Definition: Graph.hpp:30

-armnn::Layer::SetAdditionalInfo
void SetAdditionalInfo(QueueDescriptor &descriptor) const
Definition: Layer.cpp:274

-armnn::DetectionPostProcessLayer::ValidateTensorShapesFromInputs
void ValidateTensorShapesFromInputs() override
Check if the input tensor shape(s) will lead to a valid configuration of DetectionPostProcessLayer.
Definition: DetectionPostProcessLayer.cpp:39

-armnn::ManagedConstTensorHandle
Definition: TensorHandle.hpp:187

-armnn::LayerWithParameters< DetectionPostProcessDescriptor >::PrepInfoAndDesc
WorkloadInfo PrepInfoAndDesc(QueueDescriptor &descriptor) const
Helper function to reduce duplication in *Layer::CreateWorkload.
Definition: LayerWithParameters.hpp:44

-armnn::Layer::GetOutputSlot
const OutputSlot & GetOutputSlot(unsigned int index=0) const override
Get the const output slot handle by slot index.
Definition: Layer.hpp:326

-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:319

-armnn::DetectionPostProcessQueueDescriptor::m_Anchors
const ConstTensorHandle * m_Anchors
Definition: WorkloadData.hpp:241

-armnn::LayerWithParameters
Definition: LayerWithParameters.hpp:14

-armnn::DetectionPostProcessLayer::Clone
DetectionPostProcessLayer * Clone(Graph &graph) const override
Creates a dynamically-allocated copy of this layer.
Definition: DetectionPostProcessLayer.cpp:32

-armnn::ManagedConstTensorHandle::Map
const void * Map(bool blocking=true)
RAII Managed resource Unmaps MemoryArea once out of scope.
Definition: TensorHandle.hpp:196

-armnn::DetectionPostProcessDescriptor
Definition: Descriptors.hpp:681

-armnn::DetectionPostProcessLayer::m_Anchors
std::shared_ptr< ConstTensorHandle > m_Anchors
A unique pointer to store Anchor values.
Definition: DetectionPostProcessLayer.hpp:20

-armnn::IWorkloadFactory::CreateWorkload
virtual std::unique_ptr< IWorkload > CreateWorkload(LayerType type, const QueueDescriptor &descriptor, const WorkloadInfo &info) const
Definition: WorkloadFactory.cpp:1561

-armnn::OutputSlot::GetTensorInfo
const TensorInfo & GetTensorInfo() const override
Definition: Layer.cpp:92

-armnn::Layer::m_ShapeInferenceMethod
ShapeInferenceMethod m_ShapeInferenceMethod
Definition: Layer.hpp:423

-LayerCloneBase.hpp

-armnn::GetTensorInfo
const TensorInfo & GetTensorInfo(const ITensorHandle *tensorHandle)
float32 helpers
Definition: RefWorkloadUtils.hpp:27

-armnn::DetectionPostProcessLayer::ExecuteStrategy
void ExecuteStrategy(IStrategy &strategy) const override
Apply a visitor to this layer.
Definition: DetectionPostProcessLayer.cpp:98

-armnn::LayerType
LayerType
When adding a new layer, adapt also the LastLayer enum value in the enum class LayerType below...
Definition: Types.hpp:466

+Go to the documentation of this file. //

+ // Copyright © 2017-2023 Arm Ltd and Contributors. All rights reserved.

+ // SPDX-License-Identifier: MIT

+ //

+

+ #include "DetectionPostProcessLayer.hpp"

+

+ #include "LayerCloneBase.hpp"

+

+ #include <armnn/TypesUtils.hpp>

+ #include <armnn/backends/TensorHandle.hpp>

+ #include <armnn/backends/WorkloadData.hpp>

+ #include <armnn/backends/WorkloadFactory.hpp>

+

+ namespace armnn

+ {

+

+ DetectionPostProcessLayer::DetectionPostProcessLayer(const DetectionPostProcessDescriptor& param, const char* name)

+     : LayerWithParameters(2, 4, LayerType::DetectionPostProcess, param, name)

+ {

+ }

+

+ std::unique_ptr<IWorkload> DetectionPostProcessLayer::CreateWorkload(const armnn::IWorkloadFactory& factory) const

+ {

+     DetectionPostProcessQueueDescriptor descriptor;

+     descriptor.m_Anchors = m_Anchors.get();

+     SetAdditionalInfo(descriptor);

+

+     return factory.CreateWorkload(LayerType::DetectionPostProcess, descriptor, PrepInfoAndDesc(descriptor));

+ }

+

+ DetectionPostProcessLayer* DetectionPostProcessLayer::Clone(Graph& graph) const

+ {

+     auto layer = CloneBase<DetectionPostProcessLayer>(graph, m_Param, GetName());

+     layer->m_Anchors = m_Anchors ? m_Anchors : nullptr;

+     return std::move(layer);

+ }

+

+ void DetectionPostProcessLayer::ValidateTensorShapesFromInputs()

+ {

+     VerifyLayerConnections(2, CHECK_LOCATION());

+

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

+

+     VerifyShapeInferenceType(outputShape, m_ShapeInferenceMethod);

+

+     // on this level constant data should not be released.

+     ARMNN_ASSERT_MSG(m_Anchors != nullptr, "DetectionPostProcessLayer: Anchors data should not be null.");

+

+     ARMNN_ASSERT_MSG(GetNumOutputSlots() == 4, "DetectionPostProcessLayer: The layer should return 4 outputs.");

+

+     std::vector<TensorShape> inferredShapes = InferOutputShapes(

+             { GetInputSlot(0).GetConnection()->GetTensorInfo().GetShape(),

+               GetInputSlot(1).GetConnection()->GetTensorInfo().GetShape() });

+

+     ARMNN_ASSERT(inferredShapes.size() == 4);

+     ARMNN_ASSERT(inferredShapes[0].GetDimensionality() == Dimensionality::Specified);

+     ARMNN_ASSERT(inferredShapes[1].GetDimensionality() == Dimensionality::Specified);

+     ARMNN_ASSERT(inferredShapes[2].GetDimensionality() == Dimensionality::Specified);

+     ARMNN_ASSERT(inferredShapes[3].GetDimensionality() == Dimensionality::Specified);

+

+     ValidateAndCopyShape(outputShape, inferredShapes[0], m_ShapeInferenceMethod, "DetectionPostProcessLayer");

+

+     ValidateAndCopyShape(GetOutputSlot(1).GetTensorInfo().GetShape(),

+                          inferredShapes[1],

+                          m_ShapeInferenceMethod,

+                          "DetectionPostProcessLayer", 1);

+

+     ValidateAndCopyShape(GetOutputSlot(2).GetTensorInfo().GetShape(),

+                          inferredShapes[2],

+                          m_ShapeInferenceMethod,

+                          "DetectionPostProcessLayer", 2);

+

+     ValidateAndCopyShape(GetOutputSlot(3).GetTensorInfo().GetShape(),

+                          inferredShapes[3],

+                          m_ShapeInferenceMethod,

+                          "DetectionPostProcessLayer", 3);

+ }

+

+ std::vector<TensorShape> DetectionPostProcessLayer::InferOutputShapes(const std::vector<TensorShape>&) const

+ {

+     unsigned int detectedBoxes = m_Param.m_MaxDetections * m_Param.m_MaxClassesPerDetection;

+

+     std::vector<TensorShape> results;

+     results.push_back({ 1, detectedBoxes, 4 });

+     results.push_back({ 1, detectedBoxes });

+     results.push_back({ 1, detectedBoxes });

+     results.push_back({ 1 });

+     return results;

+ }

+

+ Layer::ConstantTensors DetectionPostProcessLayer::GetConstantTensorsByRef()

+ {

+     // For API stability DO NOT ALTER order and add new members to the end of vector

+     return { m_Anchors };

+ }

+

+ void DetectionPostProcessLayer::ExecuteStrategy(IStrategy& strategy) const

+ {

+     ManagedConstTensorHandle managedAnchors(m_Anchors);

+     std::vector<armnn::ConstTensor> constTensors { {managedAnchors.GetTensorInfo(), managedAnchors.Map()} };

+     strategy.ExecuteStrategy(this, GetParameters(), constTensors, GetName());

+ }

+

+ } // namespace armnn