// // Copyright © 2017 Arm Ltd and Contributors. All rights reserved. // SPDX-License-Identifier: MIT // #include "DetectionPostProcessLayer.hpp" #include "LayerCloneBase.hpp" #include #include #include #include namespace armnn { DetectionPostProcessLayer::DetectionPostProcessLayer(const DetectionPostProcessDescriptor& param, const char* name) : LayerWithParameters(2, 4, LayerType::DetectionPostProcess, param, name) { } std::unique_ptr 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(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."); unsigned int detectedBoxes = m_Param.m_MaxDetections * m_Param.m_MaxClassesPerDetection; const TensorShape& inferredDetectionBoxes = TensorShape({ 1, detectedBoxes, 4 }); const TensorShape& inferredDetectionScores = TensorShape({ 1, detectedBoxes }); const TensorShape& inferredNumberDetections = TensorShape({ 1 }); ValidateAndCopyShape(outputShape, inferredDetectionBoxes, m_ShapeInferenceMethod, "DetectionPostProcessLayer"); ValidateAndCopyShape(GetOutputSlot(1).GetTensorInfo().GetShape(), inferredDetectionScores, m_ShapeInferenceMethod, "DetectionPostProcessLayer", 1); ValidateAndCopyShape(GetOutputSlot(2).GetTensorInfo().GetShape(), inferredDetectionScores, m_ShapeInferenceMethod, "DetectionPostProcessLayer", 2); ValidateAndCopyShape(GetOutputSlot(3).GetTensorInfo().GetShape(), inferredNumberDetections, m_ShapeInferenceMethod, "DetectionPostProcessLayer", 3); } Layer::ConstantTensors DetectionPostProcessLayer::GetConstantTensorsByRef() { // For API stability DO NOT ALTER order and add new members to the end of vector return { m_Anchors }; } ARMNN_NO_DEPRECATE_WARN_BEGIN void DetectionPostProcessLayer::Accept(ILayerVisitor& visitor) const { ManagedConstTensorHandle managedAnchors(m_Anchors); ConstTensor anchorTensor(managedAnchors.GetTensorInfo(), managedAnchors.Map()); visitor.VisitDetectionPostProcessLayer(this, GetParameters(), anchorTensor, GetName()); m_Anchors->Unmap(); } ARMNN_NO_DEPRECATE_WARN_END void DetectionPostProcessLayer::ExecuteStrategy(IStrategy& strategy) const { ManagedConstTensorHandle managedAnchors(m_Anchors); std::vector constTensors { {managedAnchors.GetTensorInfo(), managedAnchors.Map()} }; strategy.ExecuteStrategy(this, GetParameters(), constTensors, GetName()); } } // namespace armnn